U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2011–1057

U.S. Geological Survey (USGS) Earth Resources

Observation and Science (EROS) Center—

Fiscal Year 2010 Annual Report
On the cover: When the U.S. Geological Survey (USGS) opened the Landsat archive to users at no charge in October 2008, nobody 

could have predicted that three million scenes would have been distributed by August 2010. The main image on the cover is the three 

millionth Landsat scene downloaded from the (USGS) Earth Resources Observation and Science (EROS) Center. What’s unique about the 

image is that it shows an area within the Wrangell-St. Elias Park and Wilderness Reserve of Alaska acquired by Landsat 1 on July 8, 1973, 

which shows the value of the long-term archive. Imagery from the Landsat archive, spanning more than 38 years, provide continuous data 

of the Earth’s land mass, coastal boundaries, and coral reefs – creating an unprecedented comprehensive record of landscape dynamics.

The smaller images on the front cover are Landsat 5 scenes of (from left to right) Washington, DC; Red River flooding at Fargo, North 

Dakota; Long Butte fire, Idaho; California fires; irrigation expansion in Chihuahua, Mexico. 

On the back cover, the images are (from left to right) forest fires near Nizhniy Novgoro, near the Volga River in Russia; Lake Powell and 

Glen Canyon National Recreation Area, Utah and Arizona; Rio De Janeiro, Brazil; Las Vegas, Nevada; Mar Chiquita, Argentina; artificial 

Palm Islands in Dubai, United Arab Emirates; Beijing, China; Gran Canaria, Canary Islands; eastern Tennessee; and the eruption of 

Mt. Redoubt volcano, Alaska.
U.S. Geological Survey (USGS) Earth 

Resources Observation and Science 

(EROS) Center—Fiscal Year 2010 

Annual Report

Compiled by Janice S. Nelson

Open-File Report 2011–1057

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

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Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Nelson, J.S. comp., 2011, U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—

fiscal year 2010 annual report: U.S. Geological Survey Open-File Report 2011–1057, 118 p.
iii

Contents

Acronyms .....................................................................................................................................................xiv

Introduction.....................................................................................................................................................1

Fiscal Year 2010 in Review............................................................................................................................1

Science and Applications Activities...........................................................................................................1

Fire Science...........................................................................................................................................2

Forest Change Detection using ICESat Data and VCT Output..............................................2

The LANDFIRE Program: Consistent and Comprehensive National Vegetation and 

Wildland Fuel Mapping .................................................................................................2

Monitoring Trends in Burn Severity..........................................................................................3

Land Characterization and Trends .....................................................................................................5

The 2006 National Land Cover Database Reaches 80 Percent Completion.......................5

USGS Delivers New Sagebrush Characterization and Monitoring for Wyoming.............6

USGS Collaborates with Canada and Mexico to Produce the North American Land 

Change Monitoring System ..........................................................................................7

Land Cover Forecasting Methodology and Prototype Developed for Ecological 

Carbon Assessment.......................................................................................................7

Historical Land Use and Land Cover Modeling in the Western High Plains......................8

National Assessment of Land Use and Land Cover Change ................................................9

Land Cover Applications and Global Change.................................................................................10

Ecosystem Performance Assessment for the Greater Platte River Basin: 

Applications on Optimal Land Uses for Bioenergy.................................................10

Carbon Fluxes in the Great Plains...........................................................................................11

eMODIS: Useful MODIS Products for Alaskan Vegetation Studies ..................................11

Mapping Aboveground Biomass for the Yukon Flats using Landsat Images, 

Ancillary Data, and Field Measurements.................................................................12

Lidar-Derived Biomass in the Yukon River Basin .................................................................13

Estimating Big Sagebrush Productivity Decline in the Owyhee Uplands ........................13

Ecosystem Performance Anomalies in the Owyhee Uplands............................................14

Dynamic Monitoring of Ecosystem Performance for Upper Colorado River Basin........15

Climate Change: Are High Latitude Lakes Drying?...............................................................15

Boreal Forest Performance Anomalies in the Yukon River Basin .....................................16

Adapting to Climate Change by Re-Greening Landscapes in West Africa’s Sahel ........17

Monitoring Biodiverse Forests and Protected Areas in West Africa’s Upper 

Guinean Forest Ecoregion ..........................................................................................19

Assessing Human Impacts on Critical Environments in Senegal......................................20

Mapping Land Cover through the Decades in East Africa .................................................22

Topographic Processing Service for South America – Andean Development Bank 

GeoSUR Program .........................................................................................................23

EcoServ: An Integrated Web-Services-Based Ecosystem Services Modeling

 System...........................................................................................................................24

Collateral Effects of Carbon Sequestration on Ecosystem Services ................................25

Quantifying Water Storage Capacity of Topographic Depressions in the Prairie 

Pothole Region from Lidar and National Wetland Inventory Datasets ...............25

The Methodology Development for the USGS Land Carbon Project................................27

GEMS Simulation Results for the Land Carbon Pilot Study Area ......................................27
iv

Simulation of Lateral Movement of Soil and Carbon on Landscape.................................29

Contemporary Carbon Dynamics in U.S. Eastern Terrestrial Ecosystems.......................30

Spatiotemporal Dynamics of Water Loss because of Evapotranspiration in the Great 

Plains..............................................................................................................................30

Modeling Gross Primary Productivity in the Mid-Continent Intensive Campaign 

Region of the North American Carbon Program.....................................................31

Computing Seasonal Evapotranspiration in the Great Plains Using Satellite Images ...32

Effects of Spatial Resolution of Satellite Sensors on Seasonal Evapotranspiration 

Estimates .......................................................................................................................34

Sensitivity of Hydrological Processes to Climate Change in the Upper Mississippi 

River Basin ....................................................................................................................34

Hydrological Responses to Rising Atmospheric Carbon Dioxide (CO2) Concentration in 

the Upper Mississippi River Basin ............................................................................35

Grazing Affects DOI Land Carbon Dynamics, but with High Uncertainty.........................36

General Ensemble Biogeochemical Modeling System (GEMS) Development................37

Impacts of Management Practices on Cropland Carbon Sequestration in MidContinent Intensive Region.........................................................................................38

Will Climate Change Stimulate Greenhouse Gas Fluxes in Wetlands? Greenhouse Gas 

Research in the Prairie Pothole Region ...................................................................38

Evaluating Ecosystem Sustainability under Biofuel Pressure ...........................................39

A New Approach for Estimating Global Evapotranspiration and Gross Primary 

Production .....................................................................................................................39

Improving Biogeochemical Simulations with Data Assimilation in the Yukon River 

Basin...............................................................................................................................40

Topographic Science, Elevation, and Lidar....................................................................................41

The Global Multi-Resolution Terrain Elevation Data (GMTED2010)...................................41

Hydrologic Derivatives Extracted from High-Resolution Lidar Elevation Data: USGS 

Scientific Investigations Report 2010–5059 .............................................................42

Geographic Information System Tools for Estimating Post-Wildfire Debris Flow 

Inundation......................................................................................................................44

National Atlas Million Scale Mapping ...................................................................................44

The National Elevation Dataset: Lidar for Science ..............................................................45

CLICK Passes a One-Trillion Milestone..................................................................................46

Lidar Research Highlighted in Prestigious Industry Journal..............................................47

Early Warning, Environmental Monitoring, and Hazards Management....................................48

Global Environmental Alert Service........................................................................................48

Africa Water Atlas .....................................................................................................................48

Radar Applications Development ...........................................................................................49

Mapping Irrigated Agriculture across the Country..............................................................50

U.S. Evapotranspiration Project ..............................................................................................50

eMODIS Normalized Difference Vegetation Index for Food Security Monitoring..........51

The USGS FEWS NET Informing Climate Adaptation Series..............................................53

Crop Area Estimation for Haiti with Very High Resolution Satellite Imagery...................55

Remote Sensing Activities..........................................................................................................................56

Landsat Program.................................................................................................................................57

Survey of Landsat Users Demonstrates Value of Landsat Data........................................57
v

Landsat Users Break Records—Over 2.4 Million Images Delivered ................................58

Landsat Data Revival—Multispectral Scanner Data Improvements................................59

Landsat Saves the Orphans .....................................................................................................60

Landsat Global Archive Consolidation—The World at EROS.............................................60

New Missions......................................................................................................................................61

LDCM Ground Network Element Critical Design Review....................................................61

LDCM Ground Network Element (GNE) Testing with Spacecraft Engineering Model 

(EM) Hardware .............................................................................................................62

LDCM Collection Activity Planning Development Element.................................................62

Landsat Science Team Activities ............................................................................................62

Data Processing and Archive System Critical Design Review..........................................63

Landsat Data Continuity Mission Ground System Critical Design Review ......................64

EROS LDCM Test Infrastructure..............................................................................................65

EROS LDCM Ground Readiness Tests ....................................................................................65

Calibration and Validation Technical Interchange Meetings.............................................66

Phase 2 Algorithms for Operational Land Imager and Thermal Infrared Sensor 

Delivered to Development ..........................................................................................67

International Cooperator Meeting: 38th Landsat Ground Station Operators Working 

Group..............................................................................................................................67

International Cooperator Meeting: 19th Landsat Technical Working Group...................68

Land Satellites Data System Consolidated Exhibit 300........................................................69

Data Management and Distribution ................................................................................................69

Image Server/ArcGIS Server Now Providing NAIP Web Mapping Service and 

Downloads.....................................................................................................................69

DATA.gov: Access to High Resolution Orthoimagery ..........................................................70

Hazards Data Distribution System Graphical User Interface.............................................71

New EarthExplorer Implementation .......................................................................................72

SPOT 1–3 Historical Archive L1G Processing.......................................................................72

SPOT North America Data Buy ...............................................................................................73

Phoenix V Archive Scanning ...................................................................................................73

eMODIS System Enhancements Support New Users.........................................................74

NASA EOS Terra Mission Celebrates 10 Years at LP DAAC...............................................74

LP DAAC Moves Entire Archive Online..................................................................................75

LP DAAC Supports Emergency Response Activities ...........................................................75

LP DAAC Develops ASTER GDEM Case Study .....................................................................77

Interagency Agreement Signed for FY 2010–14 Operation of LP DAAC at EROS............78

Distribution of Earth Science Data .........................................................................................78

Archive Strategic Direction Committee .................................................................................79

Scientific Records Appraisal ...................................................................................................79

DoD Corps of Engineers Aerial................................................................................................80

Represent USGS Records Management ...............................................................................80

USGS Data Rescue Initiatives .................................................................................................81

EROS History Project.................................................................................................................81

Consolidated Archive and Distribution Data Report: A Monthly “Consolidated Report” 

for All Data Managed and Distributed at EROS ......................................................81
vi

Calibration and Validation .................................................................................................................86

Satellite Data Characterization and Joint Agency Civil Imagery Evaluation (JACIE) 

Team ...............................................................................................................................86

USGS Quality Assurance Plan for Digital Aerial Imagery...................................................88

Aerial Mapping Camera Calibration and Characterization.................................................89

Coordination and Collaboration........................................................................................................90

Haiti Earthquake Response......................................................................................................90

Chile Earthquake Response .....................................................................................................91

Deepwater Horizon Oil Spill Response ..................................................................................92

Facilitating Access to Landsat Data for Developing Countries .........................................93

USGS Supports CEOS Working Group on Information Systems and Services................93

Coordinating a Successful CEOS WGCV Plenary Meeting.................................................94

Coordinating a Successful QA4EO Workshop ......................................................................94

First Ever GEO Work Plan Symposium....................................................................................94

USGS Supports CEOS Working Group on Education: Fourth Jay Feuquay Memorial 

Workshop.......................................................................................................................95

CEOS Land Surface Imaging Constellation Portal for GEOSS............................................95

Coordination of Space Data Acquisition in Support of GEO Forest Carbon Tracking ....97

GEO Forest Carbon Tracking Science and Data Summit and Space Data Coordination 

Meeting..........................................................................................................................98

UNEP 3D Tours and Videos ......................................................................................................98

Center Support Activities ..................................................................................................................99

Communications and Outreach Project.................................................................................99

Preparing for the Financial Business Management System Implementation...............102

Partnering..................................................................................................................................102

Student and Volunteer Programs..........................................................................................103

Facility Updates........................................................................................................................103

Support Service Contracts at the USGS EROS ...................................................................103

Selected Research and Technical Publications...................................................................................104

Journal Articles.................................................................................................................................104

Book Chapters...................................................................................................................................110

Reports................................................................................................................................................110

USGS Fact Sheets....................................................................................................................110

USGS Open-File Reports.........................................................................................................111

USGS Scientific Investigations Reports...............................................................................111

Non-USGS Discussion Paper .........................................................................................................112

Conference Papers...........................................................................................................................112

Conference Presentations ..............................................................................................................112

Conclusion...................................................................................................................................................118

References Cited........................................................................................................................................118
vii

Figures

1. Transect line of photon-counting lidar data flown over SERC is shown in yellow (left). 

The yellow circle indicates the area of data extracted and histogrammed (right). The 

histogram shows that for this area a clear ground signal is difficult to identify................2

2. Illustrates the level of landscape change resulting from wildland fire since LANDFIRE 

national datasets were produced..............................................................................................3

3. The graphic illustrates the number and extent of the fires (more than 13,000) assessed 

by the Monitoring Trends in Burn Severity project from 1984 to 2008 (northeast historical not yet complete)....................................................................................................................4

4. The graphic illustrates the number and extent of the fires (more than 900) in Alaska 

assessed by the Monitoring Trends in Burn Severity project from 1984 to 2003. Assessments of historical fires in Alaska, Hawaii, and the Northeast is scheduled to be 

completed by May 2011 ...............................................................................................................4

5. Example of NLCD 2006 and NLCD 2001 land cover change in Houston, Texas ..................5

6. Example of four statewide primary components from combined Landsat and Advanced 

Wide Field Sensor predictions including percent estimates of shrub, herbaceous, litter, 

and bare ground for each 30-meter cell ...................................................................................6

7. Completed 2005 land cover map produced for the North American Land Change Monitoring System.................................................................................................................................7

8. Land use and land cover modeling prototype results for the reference (R) and mitigation (L) scenarios for two Level III ecoregions, the Mississippi Valley Alluvial Plain and 

the Mississippi Valley Loess Plain. Obvious differences between the R and L scenarios 

are evident in the 2010 to 2050 land cover change images. The scenario-based LULC 

forecasts can be utilized to assess carbon sequestration and other greenhouse gas 

mitigation strategies on a regional basis..................................................................................8

9. The amount of change between 1973 and 2000 as a percent of each ecoregion for 

the conterminous United States. Results show the variability in the amount of overall 

change across the United States and point out how responses to various economic, 

policy, technological, and social driving forces differ substantially based on the unique 

environmental and socioeconomic factors shaping each ecoregion.................................9

10. Site potential map for grassland in Greater Platte River Basin. The areas in blue represent pixels that either overperformed or normally performed for three of four years 

from 2005 to 2008. Overperforming and normal performing areas are where productivity is greater or similar to a weather-based estimate and represent good condition 

vegetation and fair condition vegetation................................................................................10

11. Photosynthetic capacity (Amax) for grassland systems (2000–2008) (left) and grassland 

mean annual ecosystem exchange (2000–2008) and flux tower locations (right)...........11

12. Grayscaled 250-meter Normalized Difference Vegetation Index calculated from Terra 

MODIS data acquired 

August 20–26, 2007, over Alaska and the adjacent Canadian Yukon River Basin ...........12

13. The map of 30-meter resolution aboveground biomass for the Yukon Flats, Alaska ......12

14. Location of lidar data acquisition within the Yukon River Basin study area and preliminary biomass product generated from lidar canopy height data and height-based 

allometric biomass equations...................................................................................................13

15. The time-series cluster analysis reveals a long-term decline of higher producing Big 

Sagebrush areas, especially from the present time (2010) to 2040. Trends of similar or 

slightly increased productivity levels were predicted for the lowest producing areas. 

Areas of moderate productivity trended downward or remained at similar productivity 

levels.............................................................................................................................................14
viii

16. The persistent anomaly map displays areas that overperformed or underperformed 

at least 6 of 9 years studied. Areas on the map in shades of red or gray show areas of 

possible concern for land managers.......................................................................................14

17. Example Ecosystem Performance for Big Sagebrush in the Upper Colorado River 

 Basin (2006).................................................................................................................................15

18. An example of a lake (name unknown, Yukon Flats, Alaska) with no significant surface 

water change between May 1979 and May 2009..................................................................16

19. An example of a lake (Twelve Mile Lake, Yukon Flats, Alaska) with significant drying 

between May 1979 and May 2009............................................................................................16

20. Time series analysis of boreal forest performance anomalies to identify linear and 

nonlinear trends..........................................................................................................................17

21. General location (white areas) of landscape regreening, where farmers have 

adopted practices that have substantially improved environmental and agricultural 

conditions.....................................................................................................................................18

22. Hand-irrigated vegetable cultivation surrounded by dense tree parkland dominated 

by the winter thorn tree (Faidherbia albida). Tree parklands have increased in density 

and extent across 5 million hectares of southern Niger. The winter thorn tree provides 

many benefits, including boosting crop yields by fixing nitrogen in the soil, and provid-

ing fodder for livestock. Adouna Valley, Niger. Photo: C. Reij.............................................18

23. Comparison of an aerial photograph (left, 1975) and a QuickBird satellite image (right, 

2005) showing the much increased tree cover of agricultural landscapes in southern 

Niger. Note that the large village in the 2005 image did not yet exist when the 1975 

photograph was taken ...............................................................................................................18

24. A view of the cloud forest near the top of Mount Nimba. The Mount Nimba range is a 

transboundary reserve located on the border between Guinea, Cote d’Ivoire, and Libe-

ria. It preserves unusually rich flora and fauna including a number of endemic species. 

It is one of the hotspots in the Upper Guinea Forest Ecoregion.........................................19

25. This pair of maps compares primary and secondary dense forest cover in Sierra Leone 

from 1976 (left) to 2005–2009 (right). The remaining forest fragments and blocks are 

islands of biodiversity. Forest cover during this period declined from about 6 percent 

to just more than 2 percent of the national land area. Forest cover was mapped using 

Landsat and ASTER imagery.....................................................................................................20

26. One of 13 ASTER-based image maps produced of eastern Sierra Leone where existing 

maps are 30 years out-of-date. The maps are being used by the PAGE Project in sup-

port of formulating land use and forest management plans with local communities.....20

27. EROS environmental scientists and their counterparts from CSE are monitoring vegeta-

tion structure and biodiversity changes at hundreds of ground sites across Senegal, 

including sites like this one in southeast Senegal. This photo pair compares the same 

landscape in 1995 (top) and 2006 (bottom). Woody species inventories show significant 

decline in biodiversity and habitat quality. The team is revisiting sites they originally 

established in 1983 .....................................................................................................................21

28. This map is a small portion of a Land Cover Map of the Kedougou Region of Senegal. 

The map is being prepared from ASTER and Landsat imagery. The map and support-

ing field work will be used to produce several derivative themes, including a Relative 

Wildness Map and a Biodiversity Hotspot Map....................................................................22

29. Participants from five East African countries attended the workshop in time-series 

land cover mapping at the Regional Centre for Mapping of Resources for Develop-

ment, Nairobi, May 2010 ............................................................................................................22

30. Participants field-checked their draft land cover maps at a study area near Lake 

Naivasha, in Kenya’s Rift Valley ...............................................................................................23
ix

31. Composite image of Topographic Processing Services available as digital elevation 

model derivative products.........................................................................................................23

32. GeoSUR geoprocessing web interface...................................................................................24

33. EcoServ Online Modeling System in a pilot study area of the Prairie Pothole Region...24

34. Ecosystem Services Change Indicator of the reference and optimized scenarios compared to the baseline .................................................................................................................25

35. Prairie Pothole storage capacity and the capability of floodwater regulation. a) Floodwater potential distribution. Blue indicates the water when individual and isolated 

wetlands are full. Red indicates extended water when the wetland connectivity is 

considered. b) With the water level of May 17, 2008, before the flood event, the 

absolute and relative floodwater regulation under different precipitation events was 

modeled........................................................................................................................................26

36. Flow chart of the GEMS. LANDFIRE, Landscape Fire and Resource Management Planning Tools Project; VCT, vegetation change tracker; MTBS, Monitoring Trends in Burn 

Severity Project; FIA, Forest Inventory and Analysis Program (U.S. Forest Service); C, 

carbon; K, potassium; USPED, unit stream power-based erosion and deposition; NASS, 

National Agricultural Statistics Service; NASWQ, National Action Plan for Salinity 

and Water Quality; MODIS, moderate resolution imaging spectroradiometer; JDF, 

joint frequency distribution; BGC, biogeochemical; EDCM, erosion deposition carbon 

model; DNDC, denitrification-decomposition; IBIS, integrated biosphere simulator; 

EnKF, ensemble Kalman filter; NetCDF, network common data form; NLCD, national 

land cover database; DEM, digital elevation model; STATSGO, U.S. general soil map; 

SSURGO, soil survey geographic database; NWI, national wetland inventory; CO2, 

carbon dioxide; Ndep, nitrogen deposition ............................................................................27

37. Total ecosystem carbon stock simulated by GEMS-CENTURY in the pilot study area...28

38. Comparisons of annual carbon sequestration rates of biomass carbon stock among 

three methods (GEMS-spreadsheet, GEMS-CENTURY, and GEMS-EDCM) using the 

“enhanced land use and land cover with reference land management” (L) scenario for 

the whole pilot study area from 2001 to 2050. Comparison made using the same models 

and the “reference land use, land cover, and land management” (R) scenario yielded 

similar results. Tg C/yr, teragrams of carbon per year.........................................................28

39. Spatial distribution of soil erosion and deposition is shown on the left. Trends of total 

soil erosion are shown on the right with blue lines indicating business as usual and 

purple lines indicating reduced forest cutting and increased wetland restoration........29

40. Panel A displays the annual variation of carbon fluxes in the Ridge and Valley ecoregion from 1973 to 2000, where total carbon sink refers to the net carbon uptake by terrestrial ecosystems (that is, increase of plant biomass carbon and soil organic carbon 

(SOC), and harvest carbon in grain and wood). Panel B shows the impact of land cover 

change on net ecosystem exchange (NEE) in 40 sample blocks each year, where Cs 

and Cd denotes NEE under static and dynamic land covers, respectively ......................30

41. Evapotranspiration maps showing the water loss because of evapotranspiration on 

(a) July 4, (b) August 5, (c) August 13, (d) August 29, (e) September 30, (f) October 16, 

(g) October 24, and (h) December 11, 2001. Location of the study area and legend for 

evapotranspiration maps are shown in the lower-right corner..........................................31

42. Gross primary productivity maps derived from Landsat (path 28, row 31) for (a) July 

4, (b) August 5, (c) August 29, (d) September 30, (e) October 16, and (f) December 11, 

2001. The GPP values are in g C m–2 day–1 ..............................................................................32

43. Cumulative seasonal evapotranspiration (July–December) for 2001 growing season 

using (a) cubic, (b) fixed, and (c) linear methods ..................................................................33

44. Density plot of seasonal evapotranspiration for (a) cubic and fixed methods, (b) cubic 

and linear methods, and (c) fixed and linear methods. ........................................................33
x

45. Seasonal evapotranspiration (millimeters) from July to December 2001 growing season 

using (a) Landsat and (b) MODIS images ...............................................................................34

46. Effect of spatial resolution on estimated seasonal evapotranspiration............................34

47. Comparison of simulated streamflow and soil water content under changing precipitation and temperature scenarios...............................................................................................35

48. Simulation of streamflow increase because of the elevated atmospheric CO2 concentration and contribution percentage since 1987....................................................................36

49. Relation between the increase in streamflow per unit precipitation and the increase in 

CO2 concentration.......................................................................................................................36

50. Spatial distribution of carbon sinks and sources in the Green River Basin simulated by 

General Ensemble Biogeochemical Modeling System from 1970 to 2000 ........................37

51. Structure of the General Ensemble Biogeochemical Modeling System...........................37

52. Annual soil organic carbon (SOC) changes in the top 20 centimeters between 2000 and 

2007 per county in the Mid-Continent Intensive region for three tillage scenarios. .......38

53. 2007 Prairie Pothole Region ......................................................................................................38

54. Top: Soil organic carbon (SOC) stock in 1972. Bottom: Total change in soil organic 

carbon (SOC) from 1972 to 2007................................................................................................39

55. Top: Simulated global evapotranspiration (ET) pattern. Bottom: Simulated global Gross 

Primary Production (GPP) distribution ....................................................................................40

56. Upper panel shows comparisons of net ecosystem exchange (NEE) simulated by data 

assimilation (that is, SEnKF) (blue diamond) and by GEMS alone (green triangle: with 

pre-determined parameters, blue triangle: with parameters adjusted by data assimilation) against eddy covariance measurements (red square) at a boreal forest tower 

site in Alaska. Lower panel shows comparisons of corresponding ensemble-based 

standard deviations of NEE against errors of eddy covariance measurements .............40

57. The Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) replaces 

GTOPO30 as the elevation dataset of choice for global and continental scale applications...............................................................................................................................................41

58. GMTED2010 Spatially Referenced Metadata.........................................................................42

59. The U.S. Geological Survey developed selective drainage methods to extract hydrologic information from high-resolution, high-vertical accuracy light detection and ranging (lidar) digital elevation models in Minnehaha County, South Dakota .........................43

60. Cover of U.S. Geological Survey Scientific Investigations Report 2010–5059 “Using 

Selective Drainage Methods to Extract Continuous Surface Flow From 1-Meter LidarDerived Digital Elevation Data.” The selective drainage methods that the U.S. Geological Survey tested and developed for Minnehaha County, South Dakota, are published 

in this Scientific Investigations Report ...................................................................................43

61. This aerial view is an example of an inundation zone for 10,000-cubic-meter debris 

flow volume produced using the LAHARZ tool. Zones like these are typically compiled 

as a series to show a range of magnitudes for conveying risk to decision makers. ......44

62. The image shows mapping that has been completed for the western half of the conterminous United States, or about 7,950 waterbodies...............................................................45

63. Fiscal year 2011 holds great promise for the amount of available high-resolution lidar 

data to be added to the National Elevation Dataset collection. ........................................46

64. The image depicts approximately 20,000 lidar points in downtown Sioux Falls, South 

Dakota...........................................................................................................................................46

65. Lidar featured on PE&RS covers depicting Mount Rainier, Washington, (left) and Falls 

Park in Sioux Falls, South Dakota (right).................................................................................47
xi

66. Screenshot of the Global Environmental Alert Service website (http://www.na.unep.

net/geas) ......................................................................................................................................48

67. Cover of the Africa Water Atlas ...............................................................................................49

68. InSAR image of Dec 6, 2006–June 8, 2007, showing land surface subsidence because 

of mining activity over Utah ......................................................................................................49

69. The 2002 irrigated agriculture results from the MIrAD-US model. The six inset boxes 

show MIrAD-US model results next to 2002 mid-summer Landsat scenes......................50

70. Annual evapotranspiration for three study regions showing spatial distribution of vegetation water use across different landscapes in the United States, northeast Africa, 

Iraq, and surrounding regions. Green indicates high water use in high rainfall and 

irrigated regions. Brown indicates low water use in arid and semiarid regions.............51

71. An example of the improvement in spatial resolution with the expedited MODIS (eMODUS) Normalized Difference Vegetation Index (NDVI) (upper right) compared to coarse 

resolution Advanced Very High Resolution Radiometer data (lower right). The Haiti 

land cover map (left) shows an area of dense agriculture along the west central coast 

that, when compared to the NDVI maps, illustrates the benefits that eMODIS quality 

and resolution will provide for improved agricultural monitoring in current Famine Early 

Warning Systems Network countries and other remote monitoring locales...................52

72. A 10-day eMODIS NDVI composite of Africa at 250-meter resolution..............................52

73. Suitable crop growing areas shrink in central Kenya. The backdrop image shows key 

crop surplus and crop deficit areas. The three overlain polygons show areas typically 

receiving enough rain to support a healthy crop (areas receiving, on average, more 

than 500 millimeters of rainfall) during 1960–1989, 1990–2009, and 2010–2039 ................54

74. Observed and projected change in rainfall and temperature (left), together with 

smoothed central Kenyan rainfall and a smoothed version of the Indian-Pacific-Area 

climate index (right)....................................................................................................................54

75. WorldView panchromatic image of Central Haiti, L’Artibonite Department from November 23, 2009. This image captures agricultural areas (green points) and nonagricultural 

areas (orange points) as interpreted by expert image analysts in the region .................56

76. Preliminary survey information shown by this scatter diagram indicates that Landsat 

data are very important and valuable to a broad user community ....................................58

77. Increased data delivery into fiscal year 2010 ........................................................................59

78. Landsat scenes (left to right) illustrate improved research capabilities with increased 

availability and use of free data. Hansen, and others, 2008 ................................................59

79. Example Multispectral Scanner image includes a JPEG of geometrical accuracy........59

80. Example of a recovered image (Landsat 2, path 40, row 35, June 27, 1978) not 

previously archived at EROS, but processed using the updated MSS processing software ..............................................................................................................................................60

81. Graphic of unique Landsat 1–3 image data held at international ground stations 

(IGS) ..............................................................................................................................................60

82. High-level architectural diagram of the LDCM Ground Network Element........................61

83. Illustration of the equipment used in the June 2010 test (image courtesy of Orbital Sciences Corporation).....................................................................................................................62

84. No-charge Landsat time series datasets contribute to natural resources management 

by providing an affordable means to detect threats to resources. The images show 

areas of forest change associated with western spruce budworm (yellow and red) at 

San Pedro Peaks, New Mexico and was produced by Landsat Science Team member 

Jim Vogelmann (USGS). The two images represent a 1998 Landsat 5 image (left) and a 

1998 to 2008 land change map (right)......................................................................................63
xii

85. Browse image of a sample Level 1 user product..................................................................64

86. High-level architectural diagram of the Landsat Data Continuity Mission Ground 

System..........................................................................................................................................64

87. LDCM Data Processing and Archive System housed in a secure, climate controlled 

equipment room. Computer operators will test the system from the operations room 

adjacent to the computer room................................................................................................65

88. This is a graphical representation of the configuration needed for Ground Readiness 

Test 1, where the Mission Operation Center will generate commands that the EROS 

Ground Station will transmit to a spacecraft simulator. Simulated telemetry will be 

received and verified as valid responses by the flight operation team.............................65

89. The Operational Land Imager design concept by Ball Aerospace and Technology Corporation ........................................................................................................................................66

90. The algorithm maturity level is mapped from the instrument provider to the Calibration 

and Validation Team for algorithm design to Data Processing and Archive Segment 

development. The green box (across center of diagram) identifies the phase of development along with interfaces and a rough event synchronization....................................67

91. Group photogrpah from the 38th Landsat Ground Station Operators Working Group 

(LGSOWG #38) meeting held in Berlin, Germany, September 28–October 5, 2009 ..........68

92. Group photograph from the 19th Landsat Technical Working Group Meeting held in 

Phuket, Thailand, March 22–26, 2010 ......................................................................................69

93. The map illustrates the coverage area in the continental 48 states of NAIP imagery. ..70

94. Search page at DATA.gov..........................................................................................................70

95. Downloaded image from search results. Pierre, South Dakota, 0.30-meter resolution 

natural color, April 2005 acquisition ........................................................................................71

96. The new graphical user interface in the Hazards Data Distribution System. ..................71

97. The new EarthExplorer System................................................................................................72

98. A sampling of one of the 814,424 images out of the SPOT 1, 2, and 3 archive recently 

processed and now available for download by authorized users. (Copyright 2010 CNES 

Distribution Spot Image)............................................................................................................72

99. A sampling of the moderate-resolution optical imagery being received from the SPOT 4 

and SPOT 5 satellites. (Copyright 2010 CNES Distribution Spot Image)............................73

100. A sampling of one of the 260,000+ digital high-resolution images that originated from 

the USGS film collection that was scanned, archived, and made available for download................................................................................................................................................73

101. Famine Early Warning System implementation of LANCE-based eMODIS expedited VI 

time series....................................................................................................................................74

102. Land Processes Distributed Active Archive Center team shown inside and alongside 

one of the three tape silos removed from the system architecture...................................75

103. Trends indicate LP DAAC data distribution will continue to increase as the archive 

grows and is available on demand ..........................................................................................75

104. LP DAAC ASTER California Station Fire poster......................................................................76

105. LP DAAC ASTER Machu Picchu, Peru, poster.......................................................................76

106. LP DAAC ASTER Eyjafjallajökull Volcano, Iceland, poster...................................................77

107. ASTER global digital elevation model visualization ..............................................................78

108. Quantity and percentage of traffic through DOI’s four nodes for August 2010 ................79

109. Total inbound and outbound data flow for the past eight years .........................................79

110. Total outbound data only for the same time period...............................................................79

111. Fiscal year 2010 Land Processes Distributed Active Archive Center, Landsat, other 

satellite, non-satellite, and geospatial data distributed.......................................................81
xiii

112. Fiscal year 2010 Land Processes Distributed Active Archive Center, Landsat, other 

satellite, non-satellite, and geospatial data distributed.......................................................82

113. Fiscal year 2010 Land Processes Distributed Active Archive Center, Landsat, other 

satellite, non-satellite, and geospatial data 

managed.......................................................................................................................................82

114. Fiscal year 2010 Land Processes Distributed Active Archive Center, Landsat, other 

satellite, non-satellite, and geospatial data 

managed.......................................................................................................................................82

115. Fiscal year 2010 Landsat data distributed ..............................................................................83

116. Fiscal year 2010 Landsat data managed.................................................................................83

117. Fiscal year 2010 Land Processes Distributed Active Archive Center data distributed...83

118. Fiscal year 2010 Land Processes Distributed Active Archive Center data managed.....84

119. Fiscal year 2010 other satellite data distributed....................................................................84

120. Fiscal year 2010 other satellite data managed ......................................................................84

121. Fiscal year 2010 non-satellite data distributed ......................................................................85

122. Fiscal year 2010 non-satellite data managed.........................................................................85

123. Fiscal year 2010 geospatial data distributed..........................................................................85

124. Fiscal year 2010 geospatial data managed ............................................................................86

125. The ninth Joint Agency Civil Imagery Evaluation Workshop, Fairfax, Virginia, 

March 2010. .................................................................................................................................87

126. An illustration of the web-based “Spec & Check Tool” developed as the basis of standard digital aerial imagery specifications and imagery product verification...................88

127. The graphic shows the number of film mapping cameras calibrated at the OSL for the 

last four years..............................................................................................................................89

128. The illustration depicts the 10 International Charter members and satellite imagery 

showing the Presidential Palace at Port-au-Prince, Haiti, before (IKONOS data) and 

immediately after (GEOEYE-1 data) the January 12, 2010, earthquake..............................90

129. This map illustrates an overview damage assessment for the area of Concepcion and 

Talcahuano, Chile........................................................................................................................91

130. Experimental Marine Pollution Surveillance Report provided by National Oceanic and 

Atmospheric Administration on May 8, 2010, used in analysis of the Deepwater Horizon 

Oil Spill. Data source: RADARSAT2. ........................................................................................92

131. Oil swirls in the Gulf of Mexico off the Mississippi Delta in this natural-color image 

from Landsat 5, May 25, 2010....................................................................................................92

132. The Working Group on Calibration and the Validation and Working Group on Information Systems and Services participants at the Canadian Space Agency, Montreal, 

Canada..........................................................................................................................................94

133. Screenshot of QA4EO website banner....................................................................................94

134. Training session during the Fourth Jay Feuquay Memorial Workshop, Santa Maria, 

Brazil, 2010 ...................................................................................................................................95

135. Participants of the Fourth Jay Feuquay Memorial Workshop ............................................95

136. Example browse image that includes the Vancouver, Canada, region, acquired by 

Landsat 7 on September 22, 2002.............................................................................................96

137. Committee on Earth Observation Satellites Land Surface Imaging Constellation Portal 

web page for additional information about mid-resolution, optical satellites and sensors................................................................................................................................................96

138. National Institute for Space Research (INPE) web page linked from CEOS LSI Constellation Portal for access to CBERS-2 browse images and data...........................................97
xiv

Tables

1. Predicted relative changes in annual average hydrological components for the climate 

change sensitivity simulations. ................................................................................................35

2. Cropped area estimates for all of Haiti and broken down by Department. Area estimates are in thousands of hectares........................................................................................56

3. UNEP 3-D environmental change videos and YouTube viewer statistics. ........................98

Acronyms

AAG Association of American Geographers

ARRA American Recovery and Reinvestment Act

ARTS ASRC Research and Technology Solutions

ASB Administrative Service Branch

ASPRS American Society for Photogrammetry and Remote Sensing

ASRC Arctic Slope Regional Corporation

ASTER Advanced Spaceborne Thermal Emission and Reflection Radiometer

AVHRR Advanced Very High Resolution Radiometer

BATC Ball Aerospace and Technologies Corporation

BER bit error rate

BFRI Basin Floodwater Regulation Index

BLM Bureau of Land Management

C&DH command and data handling

C&O Communications and Outreach

CAF Andean Development Bank

CCSDS Consultative Committee on Space Data Systems

139. Group on Earth Observation established the Forest Carton Tracking national demonstrators .........................................................................................................................................97

140. Participants at Group on Earth Observation established the Forest Carton Tracking 

meetings in Woods Hole Research Center ............................................................................98

141. Communications and Outreach designed the National Land Cover Dataset 2001 

display, which now hangs outside the training rooms at EROS..........................................99

142. The new display at Sioux Falls Regional Airport shows satellite and high-resolution 

orthoimagery ...............................................................................................................................99

143. Example from the Earth As Art 3 image gallery ...................................................................100

144. Screenshot of new internal home page................................................................................100

145. Communications and Outreach designed the National Land Cover Dataset 2001 

display, which now hangs outside the training rooms at EROS........................................101

146. Image of the Week poster depicting the shrinking of the Aral Sea as revealed by Landsat imagery ................................................................................................................................101

147. C&O developed posters of the Gulf Oil Spill to show the public how satellite imagery 

was helping responders assess the crisis ...........................................................................102
xv

CDR Critical Design Review

CEN Climate Effects Network

CEOS Committee on Earth Observation Satellites

CFDP CCSDS File Data Protocol

CIDR CRSSP Imagery Derived Requirements

CLICK Center for Lidar Information Coordination and Knowledge

CNES Centre National d’Etudes Spatiales

CO2 carbon dioxide

COE Corps of Engineers

CONAE Comisión Nacional de Actividades Espaciales

CRICKet Center for Radar Information Coordination and Knowledge et al

CRP Conservation Reserve Program

CRSSP Commercial Remote Sensing Space Policy

CSA Canadian Space Agency

CSE Center for Ecological Monitoring

CSW Catalog Service for the Web

CVT Calibration and Validation Team

CWIC CEOS/WGISS Integrated Catalog

DCRS Data Collection and Routing Subsystem

DEM Digital Elevation Model

DIQAP Digital Imagery Quality Assurance Plan

DIRSIG Digital Imaging and Remote Sensing Image Generation

DLR German Aerospace Center

DNDC Denitrification-Decomposition

DOD Department of Defense

DOI Department of the Interior

DPAS Data Processing and Archive System

DSTF Data Sharing Task Force

ECHO/WIST EOS ClearingHOuse/Warehouse Inventory Search Tool

EC-LUE Eddy Covariance-Light Use Efficiency

EDCM Erosion-Deposition-Carbon-Model

EDU Engineering Development Unit

EISA Energy Independence and Security Act

EM engineering model

eMODIS “enhanced” Moderate Resolution Imaging Spectroradiometer
xvi

EOS Earth Observing System

EOSDIS EOS Data and Information System

EPA ecosystem performance anomaly

EPA Environmental Protection Agency

EROS Earth Resources Observation and Science

ERSDAC Earth Remote Sensing Data Analysis Center

ERTS-1 Earth Resources Technology Satellite 1

ES Ecosystem Services

ESA European Space Agency

ESCI ES Change Indicator

ESDIS Earth Science Data and Information System

ESRI Environmental Systems Research Institute

ET Evapotranspiration

ETM+ Enhanced Thematic Mapper Plus

EVI enhanced vegetation index

FAO Food and Agriculture Organization

FBMS Financial Business Management System

FCT Forest Carbon Tracking

FEC forward error correction

FEWS NET Famine Early Warning System Network

FEWS Famine Early Warning System

FFP Food for Peace

FORE-SCE Forecasting Scenarios

FRED Framed Raw Expanded Data

FY fiscal year

GALS Geoscience Laser Altimeter System

GDEM Global Digital Elevation Model

GEMS General Ensemble biogeochemical Modeling System

GEO Group on Earth Observation

GEOSS Global Earth Observation System of Systems

GeoTIFF Georeferenced Tagged Image File Format

GHG greenhouse gas

GINA Geographic Information Network of Alaska

GIS Geographic Information System

GISTDA Geo-Informatics and Space Technology Development Agency
xvii

GMTED2010 Global Multi-Resolution Terrain Elevation Data

GNE Ground Network Element

GOFC/GOLD Global Observation of Forest Cover/Global Observation of Land 

 scape Dynamics

GOS Geospatial One Stop

GPP gross primary productivity

GPRB Greater Platte River Basin

GRB Green River Basin

GRID Global Resource Information Database 

GS NDVI growing season Normalized Difference Vegetation Index

GSFC Goddard Space Flight Center

HRO High Resolution Orthoimagery

ICESat Ice, Cloud, and land Elevation Satellite

IGARSS International Geoscience and Remote Sensing Symposium

INPE Instituto Nacional de Pesquisas Espaciais

InSAR interferometric SAR

IPCC Intergovernmental Panel on Climate Change

ISO International Standards Organization

ISPRS International Society of Photogrammetry and Remote Sensing

ISRO Indian Space Research Organisation

IVOS Infrared and Visible Optical Sensors

JACIE Joint Agency Civil Imagery Evaluation

JAXA Japan Aerospace Exploration Agency

LAADS Level 1 and Atmospheric Distribution System

LANCE Land and Atmosphere Near real time Capability for EOS

LANDFIRE Landscape Fire and Resource Management Planning Tools

LCLUC Land Cover Land Use Change

LDCC Landsat Data Continuity Contract

LDCM Landsat Data Continuity Mission

LDPC Low Density Parity Check

LGAC Landsat Global Archive Consolidation

LGN LDCM ground network

LGSOWG Landsat Ground Station Operators Working Group

lidar light detection and ranging

LLNL Lawrence Livermore National Labs

LMI Landsat Metadata Initiative
xviii

LP DAAC Land Processes Distributed Active Archive Center

LPGS Level-1 Product Generation System

LPSO Landsat Project Science Office

LSDS Land Satellites Data System

LSI Land Surface Imaging

LST land surface temperature

LTAP-8 Long Term Acquisition Plan 8

LULC land use and land cover

MAPPS Management Association for Private Photogrammetric Surveyors

MCI Mid-Continent Intensive

METI Ministry of Economy Trade and Industry

MIrAD-US MODIS Irrigated Agriculture Dataset

MISR Multiangle Imaging SpectroRadiometer

MOC mission operations center

MOD17A2 MODIS Gross Primary Production

MODIS Moderate Resolution Imaging Spectroradiometer

MRLC Multi-Resolution Land Characteristics Consortium

MSS Multispectral Scanner

MTBS Monitoring Trends in Burn Severity

N2O nitrous oxide

NAIP National Agriculture Imagery Program

NALCMS North American Land Change Monitoring System

NASA National Aeronautics and Space Administration

ND “National Demonstrator”

NDII normalized difference infrared index

NDVI Normalized Difference Vegetation Index

NED National Elevation Dataset

NEE net ecosystem exchange

NEPA National Environmental Policy Act

NGA National Geospatial-Intelligence Agency

NGB National Guard Bureau

NGP National Geospatial Program

NIH National Institutes of Health

NIST National Institute of Standards and Technology

NLAPS National Landsat Archive Processing System
xix

NLCD National Land Cover Database

NPWRC Northern Prairie Wildlife Research Center

NSLRSDA National Satellite Land Remote Sensing Data Archive

NSTA National Science Teacher Associa¬tion

O&M Operations and Maintenance

OGC Open Geospatial Consortium

OSL Optical Science Laboratory

PE&RS Photogrammetric Engineering and Remote Sensing

PPR Prairie Pothole Region

QA Quality Assurance

QA4EO Quality Assurance Framework for Earth Observation

RCMRD Regional Centre for Mapping of Resources for Development

RFA request for action

RIT Rochester Institute of Technology

RSAC Remote Sensing Applications Center

RSS Rich Site Summary

RST Remote Sensing Technologies

SAN Storage Area Network

SAR synthetic aperture radar

SBA Societal Benefit Area

SDE Spatial Database Engine

SDSU South Dakota State University

SDT Science Definition Team

SERC Smithsonian Environmental Research Station

SERVIR Regional Visualization and Monitoring System for environmental 

 management and disaster response

SOC Soil organic carbon

SPOT Satellite Pour l’Observation de la Terre

SRTM Shuttle Radar Topography Mission

SSEB Simplified Surface Energy Balance

SWAT Soil and Water Assessment Tool

TAA Technical Assistance Agreements 

TIM Technical Interchange Meetings

TIR thermal infrared

TIRS Thermal Infrared Sensor

TM Thematic Mapper
xx

TPS Topographic Processing Service

TSSC Technical Support Services Contract

UA University of Arizona

UAVs Unmanned Aerial Vehicles

UNFCCC United Nations Framework Convention on Climate Change

USAF U.S. Air Force

USAID U.S. Agency for International Development

USDA U.S. Department of Agriculture

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

USPED Unit Stream Power-based Soil Erosion and Deposition model

VCT Vegetation Change Tracker

Vis vegetation indices

VNIR visible and near-infrared

WBVT Wide Band Video Tape

WCS Web Coverage Service

WGCV Working Group on Calibration and Validation

WGISS Working Group on Information Systems and Services

WHRC Woods Hole Research Center

WMS Web Mapping Service

YRB Yukon River Basin
U.S. Geological Survey (USGS) Earth Resources 

Observation and Science (EROS) Center—

Fiscal Year 2010 Annual Report

Compiled by Janice S. Nelson

Introduction

The Earth Resources Observation and Science (EROS) Center is a U.S. Geological Survey (USGS) facility focused on providing science and imagery to better understand our Earth. The work of the Center is shaped by the earth sciences, the missions 

of our stakeholders, and implemented through strong program and project management, and application of state-of-the-art information technologies. Fundamentally, EROS contributes to the understanding of a changing Earth through “research to operations” activities that include developing, implementing, and operating remote-sensing-based terrestrial monitoring capabilities 

needed to address interdisciplinary science and applications objectives at all levels—both nationally and internationally. 

The Center’s programs and projects continually strive to meet, and where possible exceed, the changing needs of the 

USGS, the Department of the Interior, our Nation, and international constituents. The Center’s multidisciplinary staff uses their 

unique expertise in remote sensing science and technologies to conduct basic and applied research, data acquisition, systems 

engineering, information access and management, and archive preservation to address the Nation’s most critical needs. Of particular note is the role of EROS as the primary provider of Landsat data, the longest comprehensive global land Earth observation record ever collected. 

This report is intended to provide an overview of the scientific and engineering achievements and illustrate the range and 

scope of the activities and accomplishments at EROS throughout fiscal year (FY) 2010. Additional information concerning the 

scientific, engineering, and operational achievements can be obtained from the scientific papers and other documents published 

by EROS staff or by visiting our web site at http://eros.usgs.gov. 

We welcome comments and follow-up questions on any aspect of this Annual Report and invite any of our customers or 

partners to contact us at their convenience. To communicate with us, or for more information about EROS, contact: Communications and Outreach, USGS EROS Center, 47914 252nd Street, Sioux Falls, South Dakota 57198, jsnelson@usgs.gov, http://eros.

usgs.gov/.

Fiscal Year 2010 in Review

Science and Applications Activities

The Center’s science and applications activities include multidisciplinary earth science research, remote sensing applications development, and generation of associated products such as oral presentations, publications, workshops, databases, and 

websites. EROS science and applications activities are aligned with the USGS strategic science goals and priorities. 

Disciplines and skills represented in science activities at EROS include geography, cartography, geology, soil science, 

hydrology, biology, ecology, forestry, range management, geochemistry, computer science, applied physics and remote sensing, 

mathematics, and statistics. 

Science partners and collaborators include the USGS science centers, other USGS mission areas and offices and their 

associated bureau programs, other bureaus and agencies within the U.S. Department of the Interior (DOI), bureaus and agencies 

in other departments of the Federal Government, State agencies, tribal governments and universities, non-Government agencies, 

academic institutions, and international organizations.

The Center’s research and applications activities are conducted via five teams and take full advantage of the Center’s extensive national and global archive of remotely sensed data. On the following pages, the science and applications teams’ primary 

objectives are highlighted followed by key accomplishments of each. 
2 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Fire Science

The Fire Science Team conducts, applies, leads, and advances fire science by supporting the DOI, other land management 

agencies, and their fire management programs with scientifically credible, timely, reliable, and nationally consistent data, and 

constructive collaboration with other partners. Key accomplishments are given in the following sections. 

Forest Change Detection using ICESat Data and VCT Output

The research encompassed by this work plan is being conducted in support of the ICESat-2 Science Definition Team 

(SDT). The work outlined in the proposal used large-footprint, waveform lidar data collected by the Geoscience Laser Altimeter 

System (GLAS) instrument onboard Ice, Cloud and land Elevation Satellite (ICESat) as well as products from the Vegetation 

Change Tracker (VCT) to study forest vegetation structure and change. The main objectives of this research are twofold: 

(1) demonstrate that when used in combination with geospatial layers of change the three-dimensional information provided by 

GLAS waveform data will enable the characterization of the effects of that change on vegetation structure and (2) provide a set 

of data requirements in terms of lidar footprint size, density, and spacing needed to address the above. The EROS project lead 

serves on the ICESat-2 SDT. The ICESat-2 project decision to employ a photon-counting lidar system on ICESat-2 has resulted 

in the need for the SDT to conduct basic research into the expected performance of such an instrument from space, over different surfaces, and under different configurations. This has resulted in an additional work effort than initially anticipated based on 

the original proposal to the National Aeronautics and Space Administration (NASA). 

In FY 2010, work has proceeded on the original proposed work including downloading and processing GLAS data for the 

study area on the southeastern coastal plain of the United States. The VCT outputs have been generated and the results largely 

validated for the study area. Work has also progressed in the analysis of airborne photon-counting data sub-canopy ground 

detection capability. The airborne data were collected over two study areas, the Pine Barrens in New Jersey and the Smithsonian 

Environmental Research Station (SERC) in Maryland. Early results indicate that in more open canopies ground-finding performance will be sufficient to meet the science requirements of the mission. However, finding sub-canopy ground is substantially 

more challenging in denser canopies (fig. 1), such as those found at SERC, and continued research is being done using the airborne data to test other instrument design configurations and to develop better algorithms. For further information, contact Matt 

Rollins, USGS EROS, mrollins@usgs.gov.

The LANDFIRE Program: Consistent and Comprehensive National Vegetation and Wildland Fuel 

Mapping

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) project was a 5-year (2004–2009), multipartner project that produced consistent and comprehensive maps and data describing vegetation, wildland fuel, and fire regimes 

Figure 1. Transect line of photon-counting lidar data flown over SERC is shown in yellow (left). The yellow circle indicates 

the area of data extracted and histogrammed (right). The histogram shows that for this area a clear ground signal is difficult to 

identify.
Science and Applications Activities 3

across the United States. The LANDFIRE project produced national data products that included layers of vegetation composition and structure, surface and canopy fuel characteristics, and historical fire regimes. Having met the original mandate, the 

LANDFIRE Program now enters a phase that protects the significant investment of the original development project by updating 

products. Most importantly, the program will provide for data timeliness, quality, and distribution services to support Department and Agency mission needs across the country. 

The LANDFIRE program supports and provides for updated data products that reflect dynamic changes in large landscape 

condition because of natural and human-caused environmental events. The level of landscape change resulting from wildland 

fire since LANDFIRE national datasets were produced is illustrated in figure 2. A key component in the development of the 

LANDFIRE project for existing vegetation and fuel layers has been satellite imagery; however, these originated from image 

acquisitions collected from 1999 to 2002. The LANDFIRE Program updates are based on disturbance information collected 

from a variety of different information sources including the Monitoring Trends in Burn Severity Project, from the analysis of 

remote sensing information that captures detectable changes (change vector analysis of Landsat data stacks), and from ground 

truthed data supplied by land managers. The updates will continue on a regular yearly schedule until a new National remapping 

can be scheduled. For further information, contact Donald Ohlen, USGS EROS, ohlen@usgs.gov.

Monitoring Trends in Burn Severity

The USGS EROS and the U.S. Forest Service Remote Sensing Applications Center (RSAC) share responsibility to carry 

out the mandate of the Monitoring Trends in Burn Severity (MTBS) project to map and assess all large fires that occurred in 

the United States since 1984 (figs. 3 and 4). FY 2010 marked the last year of a 5-year reimbursable agreement to implement the 

program. This FY, USGS EROS completed the assessment of historical South Central fires and its allotment of calendar year 

2008 fires across the United States and Alaska. At the end of FY 2010, more than 14,000 fire assessments were available at the 

MTBS website (http://mtbs.gov/). To reduce database duplication/synchronization issues and save costs, it was decided to retire 

the USGS data distribution website and concentrate MTBS website development resources at http://mtbs.gov. USGS EROS 

continued development of software to automate the post-processing of the free Level-1 Product Generation System (LPGS) data 

into standard products (reflectance, normalized burn ratio, tassel cap, and temperature) and populate the Multi-Resolution Land 

Characteristics (MRLC) image archive. Various formats of Landsat 4, 5, and 7 Thematic Mapper imagery can now be processed 

Figure 2. Illustrates the level of landscape change resulting from wildland fire since LANDFIRE national datasets 

were produced.
4 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

by the software. This year, more than 4,000 LPGS scenes were processed and added to the MRLC archive bringing the total to 

more than 13,000.

In November 2009, the MTBS project conducted a day-long workshop at the Fourth International Fire Ecology and Management Congress in Savannah, Georgia. Workshop participants were given an overview of the project goals and procedures 

and were instructed on how to access MTBS datasets, modify the burn severity thresholds if necessary, and utilize the data for 

specific applications. The workshop slides form the basis of a web-enabled tutorial about MTBS applications.

The free Landsat data policy of the USGS has advanced the MTBS project. Analysts no longer face a constraint on the 

number of scenes that can be acquired. Early in the project, analysts were limited to two scenes per year and had to make 

compromises on the selection of the best scene to map a particular fire. The new policy has allowed the MTBS project the 

opportunity to review and revise previously mapped fires. Using automated techniques, all previously mapped fires throughout 

Figure 3. The graphic illustrates the number and extent of the fires (more than 13,000) 

assessed by the Monitoring Trends in Burn Severity project from 1984 to 2008 (northeast 

historical not yet complete).

Figure 4. The graphic illustrates the number and extent of the fires (more than 900) in Alaska 

assessed by the Monitoring Trends in Burn Severity project from 1984 to 2003. Assessments of 

historical fires in Alaska, Hawaii, and the Northeast is scheduled to be completed by May 2011.
Science and Applications Activities 5

the United States were assessed to flag fires that need a second look to confirm the suitability of image pairs, burn severity 

thresholds, and perimeters. For USGS, about 1,000 fires were flagged, reviewed, and revised as necessary. Similarly, a review of 

MTBS products created for the Southeast revealed that a change in assessment protocol was needed. Vegetation in the southeast grows so quickly that most fires require an “initial” assessment as soon as possible after the fire, rather than an “extended” 

assessment up to a year later. This change of strategy required that hundreds of previously mapped fires be revised. The free 

Landsat data policy makes revision economically feasible and new assessments more reliable.

A 5-year follow-on agreement was signed to continue MTBS activities until 2015 to include yearly updates of fire assessments and extending the satellite-derived historical fire record back to the early 1970s using Multispectral Scanner imagery from 

Landsats 1, 2, and 3. For further information, contact Stephen Howard, USGS EROS, smhoward@usgs.gov.

Land Characterization and Trends

The Land Characterization and Trends Team develops solutions for characterizing land cover at multiple temporal and spatial scales that enable subsequent analysis, monitoring, forecasting, and reporting of land cover processes. Key accomplishments 

are given in the following sections.

The 2006 National Land Cover Database Reaches 80 Percent Completion

The National Land Cover Database (NLCD) project provides consistent public domain information on the Nation’s current 

and historical land cover characteristics that are applicable at national, regional, and local scales. Much of this work is accomplished through partnerships with Federal, State, and local government agencies, private industry, and nongovernmental organizations. NLCD represents three major land cover data releases including a 1992 conterminous U.S. land cover dataset (NLCD 

1992); a 2001 land cover database for all 50 states with three thematic layers including land cover, percent imperviousness, 

and percent tree canopy (NLCD 2001); and a land cover change product that identifies land cover change between the two eras 

(NLCD 1992/2001 Retrofit Land Cover Change Product). 

In FY 2010, production of NLCD 2006 (fig. 5) (updated land cover for the nominal year of 2006) continues for the conterminous United States. NLCD 2006 updates the 2001 land cover and percent imperviousness to the year 2006 and details the type 

Figure 5. Example of NLCD 2006 and NLCD 2001 land cover change in Houston, Texas.
6 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

and amount of land cover and imperviousness change between 2001 and 2006. During FY 2010, 80 percent of the conterminous 

United States has been completed. These comprehensive sets of scientifically credible land cover data layers are used to support 

thousands of applications in land management, environmental studies, and modeling and policy decisions. All NLCD products 

are web-enabled for download at the MRLC website at http://www.mrlc.gov. For further information, contact Collin Homer, 

USGS EROS, homer@usgs.gov.

USGS Delivers New Sagebrush Characterization and Monitoring for Wyoming

Sagebrush ecosystems in North America have experienced extensive degradation since European settlement and continue 

to degrade from a variety of factors. Understanding the distribution of system components such as shrub density, bare ground 

amounts, and grass and forb cover is critical for successful land management. 

In Wyoming, widespread oil and gas development is exerting additional pressure on land managers to better understand 

the distribution of sagebrush habitats. Using three spatial scales of satellite remote sensing, the USGS developed new methods 

to characterize and monitor change of sagebrush system components (fig. 6). Four primary components (percent bare ground, 

percent herbaceous cover, percent litter, and percent shrub) and four secondary components (percent sagebrush, percent big 

sagebrush, percent Wyoming sagebrush, and shrub height) have been mapped with 30-meter pixels. These products are designed 

to provide maximum flexibility for a wide variety of ecosystem applications such as wildlife habitat and grazing and climate 

change assessments, and to provide a sagebrush monitoring database that is sensitive enough to discriminate significant change 

through time. For further information, contact Collin Homer, USGS EROS, homer@usgs.gov.

Figure 6. Example of four statewide primary 

components from combined Landsat and 

Advanced Wide Field Sensor predictions 

including percent estimates of shrub, 

herbaceous, litter, and bare ground for each 

30-meter cell.
Science and Applications Activities 7

USGS Collaborates with Canada and Mexico to Produce the North American Land Change 

Monitoring System

A digital database (and a paper map) of North American land cover, circa 2005, at a spatial resolution of 250 meters was 

completed and released (fig. 7). This product provides a harmonized view of the physical land cover across the continent. 

Nineteen land cover classes were defined using standard definitions from the Food and Agriculture Organization (FAO) of the 

United Nations by using monthly composites of 2005 Moderate Resolution Imaging Spectroradiometer satellite imagery. This 

product represents the first in a series of products that will be produced by the North American Land Change Monitoring System 

(NALCMS). 

NALCMS is a collaborative initiative between Canada, Mexico, and the United States to monitor land cover and its change 

through time. Information provided by this land cover database can be used to address issues such as climate change, carbon 

sequestration, biodiversity loss, and changes in ecosystem structure and function through better understanding of the dynamics 

and continental-scale patterns of North America’s changing land cover. For further information, contact Collin Homer, USGS 

EROS, homer@usgs.gov.

Land Cover Forecasting Methodology and Prototype Developed for Ecological Carbon Assessment

A methodology for the development of realistic, scenario-based, land use and land cover (LULC) forecasts was developed 

to support a national assessment of ecological carbon sequestration and greenhouse gas flux mitigation. The methodology was 

developed in response to section 712 of the Energy Independence and Security Act (EISA) of 2007, which mandates the Department of the Interior to assess carbon sequestration and methane (CH4

) and nitrous oxide (N2O) emissions from ecosystems. 

The LULC modeling team developed the methodology to support this work and tested it in two Environmental Protection Agency (EPA) Level III ecoregions in the southeastern United States (fig. 8). One reference scenario (“R” scenario) was 

developed to portray likely future LULC trajectories from 2010 to 2050 under the Intergovernmental Panel on Climate Change 

(IPCC) “A1B” scenario. A second scenario, portraying LULC mitigation strategies for sequestering additional carbon above and 

beyond the reference scenario “R” was also developed (“L” scenario). The reference scenario “R” is devoid of explicit carbon 

sequestration policy or mitigation actions and portrays the continuation of a dynamic forest industry with moderate urban expansion and little change in the fertile agricultural lands of the Mississippi Alluvial Plains. The “L” scenario portrayed multiple 

mitigation strategies to increase carbon sequestration, including significant wetland restoration in the Mississippi Alluvial Plains, 

Figure 7. Completed 2005 land cover 

map produced for the North American 

Land Change Monitoring System.
8 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

reduced forest cutting, and increased forest rotation cycles. Spatially explicit forecasts of LULC change from 2010 to 2050 were 

developed for each scenario. 

These scenarios were utilized by the Ecological Carbon Sequestration project’s biogeochemical modeling team to assess 

impacts of LULC change under each scenario on carbon and other greenhouse gas fluxes. As mandated by EISA, a comprehensive methodology document was published which describes all components of the Ecological Carbon Sequestration project, 

including the LULC modeling component. Starting in FY 2011, the methodology will be utilized for a National assessment of 

carbon and greenhouse gas fluxes in support of EISA. For further information, contact Terry Sohl, USGS EROS, sohl@usgs.gov.

Historical Land Use and Land Cover Modeling in the Western High Plains

In order to understand the impacts of future land use and land cover (LULC) change on issues such as biodiversity, water 

quality, carbon dynamics, and climate, it is often useful to examine past system response to LULC change. A spatially explicit 

and consistent LULC database such as the National Land Cover Database (NLCD) can be utilized to examine contemporary 

relations with LULC patterns, while the USGS Land Cover Trends database can be utilized to examine effects of historical 

(1973 to 2000) land use and land cover change. However, the Land Cover Trends database only goes back to 1973, is samplebased, and does not provide wall-to-wall LULC change data. Many applications require LULC data before 1973 or require 

Figure 8. Land use and land cover modeling prototype results for the reference (R) and mitigation (L) scenarios for two 

Level III ecoregions, the Mississippi Valley Alluvial Plain and the Mississippi Valley Loess Plain. Obvious differences 

between the R and L scenarios are evident in the 2010 to 2050 land cover change images. The scenario-based LULC 

forecasts can be utilized to assess carbon sequestration and other greenhouse gas mitigation strategies on a regional 

basis.
Science and Applications Activities 9

wall-to-wall LULC data. This work is the first attempt to develop historical, wall-to-wall LULC databases consistent with the 

NLCD framework. 

The Forecasting Scenarios (FORE-SCE) land cover model was utilized to provide a historical “backcast” of spatially 

explicit LULC for the western High Plains. A combination of sample-based Land Cover Trends data, historical county-level 

agricultural statistics, and historical census data was used to reconstruct county- or ecoregion-level proportions of specific land 

use and land cover classes back to 1955. The FORE-SCE model was then used to create spatially explicit LULC maps with 

a thematic resolution comparable to the NLCD. Continued development of historical backcast modeling of LULC provides a 

capability to recreate historical, spatially explicit, wall-to-wall LULC maps for a fraction of the cost of developing such databases through comprehensive mapping programs. These efforts also provide a rich source of data for applications requiring 

historical LULC data. For further information, contact Terry Sohl, USGS EROS, sohl@usgs.gov.

National Assessment of Land Use and Land Cover Change

Scientists from the U.S. Geological Survey completed the initial data collection for the first ever national assessment of 

land use and land cover (LULC) change. Geographers manually interpreted 429 100-kilometer (km)2 (10-km by 10-km) blocks 

of up to 11 classes of LULC for 5 dates (1973, 1980, 1986, 1992, and 2000) of archived Landsat Multispectral Scanner (MSS), 

Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) satellite imagery. The block interpretations completed 

the collection of a stratified random sample of 2,756 blocks allocated across 84 U.S. EPA Level III ecoregions. 

In addition to Landsat data, interpreters used historical aerial photographs, topographic maps, and various ancillary data 

sources to aid in image interpretation. Using a 60‐meter minimum mapping unit, interpreters would use manual onscreen photo 

interpretation techniques to develop an initial baseline land cover map followed by forward and backward classifications of any 

changes seen in the Landsat images for the other core dates. Change matrix images, block interpretation notes, and time series 

animation of the land cover changes also were generated for each sample block. The LULC mapping effort yields five individual 

dates and four discrete periods for analysis. Change analysis uses post-classification comparison of the five dates of thematic 

LULC data for each sample block to generate estimates of LULC change for each ecoregion in the United States along with corresponding margins of error at an 85 percent confidence level. 

This work was established in the early 2000s for the purpose of improving the understanding of the geographic variability 

and characteristics of 1973 to 2000 U.S. land cover change and for providing a scientific foundation for assessing the environmental consequences of past, present, and future land change. The assessment is based on an ecoregions framework and uses 

probability sampling and historical Landsat imagery to document the geographical variability of land change (fig. 9). Results 

from all 84 conterminous U.S. ecoregions show that the responses to various economic, policy, technological, and social driving 

forces differ substantially based on the unique environmental and socioeconomic factors shaping each ecoregion. Analysis and 

national synthesis of the data will be conducted in FY 2011. A full explanation of the Land Cover Trends project is provided at 

http://landcovertrends.usgs.gov. For further information, contact William Acevedo, USGS EROS, wacevedo@usgs.gov.

Figure 9. The amount of change between 

1973 and 2000 as a percent of each 

ecoregion for the conterminous United 

States. Results show the variability in the 

amount of overall change across the United 

States and point out how responses to 

various economic, policy, technological, 

and social driving forces differ substantially 

based on the unique environmental and 

socioeconomic factors shaping each 

ecoregion.
10 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Land Cover Applications and Global Change

The Landscape Dynamics and Global Change Team integrates remote sensing resources with simulation models of natural 

and managed ecosystems to understand environmental change across landscape units, ecological systems, and multitemporal/

spatial scales in support of a sustainable Earth. Key accomplishments are given in the following sections.

Ecosystem Performance Assessment for the Greater Platte River Basin: Applications on Optimal 

Land Uses for Bioenergy 

Bioenergy (biofuels) has been used recently and will grow substantially in the future as an energy alternative to fossil fuels. 

The environmental effects caused by the increase in biofuels development can be large and include increased soil and wind erosion, water quality impairment because of the greater usages of pesticide and fertilizer, and more demand for water for irrigation. 

The objective of this study is to evaluate the effects of an expanded agricultural land use for biofuels with concurrent 

changes in climate on ecosystem sustainability across the Northern Great Plains. The initial focus was on the Greater Platte 

River Basin (GPRB) with the first study targeting the implementation of a dynamic monitoring of ecosystem performance for 

grasslands and croplands in the GPRB using nine-years (2000–2008) of satellite observations, climate data, and ecosystem models. The dynamic monitoring of ecosystem performance can identify low performing croplands or high performing grasslands 

which can be potentially converted to biofuels crops. Maps were generated of areas which may be suitable regions to be converted from grassland to biofuels feedstock in the GPRB (fig. 10). These resulting maps can be used by land managers, decision 

makers, and biogeochemical modelers for making optimal land uses decisions for biofuel development and sustainability. 

Future plans for this project include performing dynamic ecosystem performance analysis for other land cover types (for 

example, shrub and forest) and identifying regions which may be suitable for biofuels development within the entire GPRB 

region; extending the study area and performing ecosystem performance analysis for the Northern Great Plains; evaluating the 

short-term and long-term environmental impacts on the local ecosystem because of the development of the biofuel product; and 

producing publications on the research results. For further information, contact Bruce Wylie, USGS EROS, wylie@usgs.gov.

Figure 10. Site potential map for grassland in Greater Platte River Basin. The areas in blue 

represent pixels that either overperformed or normally performed for three of four years from 2005 to 

2008. Overperforming and normal performing areas are where productivity is greater or similar to a 

weather-based estimate and represent good condition vegetation and fair condition vegetation.
Science and Applications Activities 11

Carbon Fluxes in the Great Plains

Grasslands are among the most altered ecosystems in the world with large areas converted to cropland. A changing and 

more variable future climate will affect grasslands dramatically because they are responsive to prolonged periods of drought 

or wet conditions and illustrate major biodiversity and compositional changes along moisture gradients. Grasslands have lower 

aboveground carbon storage compared to forests but cover vast areas of the globe and store most of their carbon belowground. 

These grassland soil carbon stocks will reduce in areas which may experience future climatic drying and warming. Synoptic 

monitoring and comprehensive analysis of current and historical grassland carbon fluxes in the Great Plains provide information on interannual variability, expected drought responses, and regional grassland carbon sink and source magnitudes. Detailed 

light-temperature-vapor pressure deficit-response analysis of the Great Plains and other global flux tower datasets showed consistent patterns for gross photosynthesis, ecosystem respiration, photosynthetic capacity, quantum yield, and light-use efficiency. 

Algorithms were derived for estimating these parameters annually and used to produce maps for the Great Plains (fig. 11, 

left). Daily flux tower net ecosystem exchange (NEE) from the flux tower analysis, synoptic weather data, synoptic photosynthetically active radiation, and other data were temporally summarized to correspond to “enhance” Moderate Resolution Imaging Spectrometer (eMODIS) Normalized Difference Vegetation Index (NDVI) seven-day composites at a spatial resolution of 

250 meters. A regression tree model was developed to estimate grassland NEE weekly from 2000 to 2008 (fig. 11, right). Ecoregions within the Great Plains most affected by changing current carbon sinks were identified. For further information, contact 

Bruce Wylie, USGS EROS, wylie@usgs.gov.

eMODIS: Useful MODIS Products for Alaskan Vegetation Studies

In 2008, the U.S. Geological Survey prototyped Normalized Difference Vegetation Index (NDVI) products that combine 

the advantages of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) with user-specific processing options to 

enhance the use of MODIS data in the Alaskan vegetation monitoring community. As NASA’s high-level MODIS products are 

constrained to programmatic standards that hinder their usability particularly in high-latitude regions, USGS eMODIS Alaska 

(fig. 12) offers timely 7-day composites projected to the Alaska Albers Equal Area mapping grid in Georeferenced Tagged Image 

File Format (GeoTIFF) files. These products enable researchers and monitoring agencies to utilize near-daily, 250-, 500-, or 

1,000-meter MODIS observations to study short- and long-term changes without significant high-latitude geometric distortion 

(Ji and others, 2010) or the need for mosaicking, reprojecting, or reformatting in preparation for data application. 

Through the USGS National Climate Effects Network (CEN), continued eMODIS Alaska production is supporting vegetation change research at the University of Alaska Fairbanks (Verbyla) and the USGS Alaska Field Office (Selkowitz, 2010). In 

collaboration with the Geographic Information Network of Alaska (GINA), use of eMODIS data also have operationalized the 

decision support activities of the Bureau of Land Management and the National Park Service to monitor and respond to vegetation related events such as fire and insect infestation. eMODIS data have likewise served USGS Carbon Cycle, Climate Change, 

and Geographic Analysis and Monitoring Program activities in the conterminous United States with the addition of near-real 

time NDVI products for the lower 48 states. For further information, contact Bruce Wylie, USGS EROS, wylie@usgs.gov.

Figure 11. Photosynthetic capacity (Amax) 

for grassland systems (2000–2008) (left) 

and grassland mean annual ecosystem 

exchange (2000–2008) and flux tower 

locations (right).
12 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Mapping Aboveground Biomass for the Yukon Flats using Landsat Images, Ancillary Data, and Field 

Measurements

Terrestrial plant biomass is a key biophysical parameter in the studies of Alaskan ecological and environmental systems. 

In this study, a preliminary map was generated of 30-meter aboveground biomass for the Yukon Flats, Alaska area based on 

Landsat images, Digital Elevation Model (DEM) data, and field measurements. The ground biomass (including tree, shrub, and 

herbaceous biomass) data were collected during August 28–September 9, 2009, by a field team.

A multiple regression model was created based on the ground-measured biomass, spectral variables derived from the 

Landsat data acquired on September 3, 2009 and DEM data. The model, with R2=0.61, uses the normalized difference vegetation 

index (NDVI), normalized difference infrared index (NDII), land surface temperature (LST), and elevation as predictor variables. To map the biomass for the entire Yukon Flats, six cloud-free Landsat 5 images were selected from August 21–September 

1, 2008, and generated into a mosaicked Landsat image. By applying the regression model to the Landsat mosaic and the DEM 

data, a 30-meter total aboveground biomass map (fig. 13) was produced. The ongoing studies include estimation of live and dead 

biomass and accuracy assessment of the biomass map using a Lidar-derived biomass product. For more information, contact 

Bruce Wylie, USGS EROS, wylie@usgs.gov.

Figure 12. Grayscaled 250-meter 

Normalized Difference Vegetation Index 

calculated from Terra MODIS data acquired 

August 20–26, 2007, over Alaska and the 

adjacent Canadian Yukon River Basin.

Figure 13. The map of 30-meter resolution aboveground 

biomass for the Yukon Flats, Alaska.
Science and Applications Activities 13

Lidar-Derived Biomass in the Yukon River Basin

Biomass levels in the Yukon River Basin (YRB) are being assessed both on the ground and through remote sensing techniques. Lidar data over the YRB were acquired in the fall of 2009 as were an initial set of field sampling data. Additional field 

data were collected during two 2010 field campaigns. Using the canopy height data derived from the lidar dataset and a set of 

height-based biomass equations (Yarie and others, 2007), a preliminary map of biomass (fig. 14) was generated for the YRB 

study area. 

The allometric biomass equations published in Yarie and others (2007) are species-specific, so a cover type map provided 

by the LANDFIRE Project was used to divide the landscape as the most appropriate biomass equation for a given location. 

Additional work is being done to refine the lidar-derived biomass product. In particular, the biomass map will need to be validated using field-based estimates of biomass. Furthermore, additional metrics will be derived from the lidar dataset to be used 

as independent variables in a plot-level, regression-based effort to predict biomass for the sampled areas within the YRB. The 

information obtained through that exercise can then be used to develop a new biomass map for the YRB study area from the 

complete lidar dataset. Lidar digital elevation model (DEM) derivatives (catchments, compound terrain index, flow direction, 

shaded relief) were also generated and shared with National Resources Conservation Service, Yukon Flats National Wildlife 

Refuge, and fellow scientists. For further information, contact Bruce Wylie, USGS EROS, wylie@usgs.gov.

Estimating Big Sagebrush Productivity Decline in the Owyhee Uplands

The Big Sagebrush ecosystem is critical for many species’ survival in the Owyhee Uplands (Oregon, Idaho, and Nevada) 

because it provides them with winter forage and essential cover from predators and for reproductive activities. However, a 

changing climate is expected to affect Big Sagebrush productivity. A regression-tree model was used to estimate Big Sagebrush 

productivity based on site potential, where site potential is understood as a measure of an ecosystem’s inherent productivity, and 

seasonal historical and current weather, and a projected moderate emissions near-future climate scenario. 

A time-series cluster analysis was performed to delineate ten classes of low to high Big Sagebrush productivity. The technique estimates that the six most productive Big Sagebrush areas in the Owyhee Uplands will experience declining productivity 

between the present time (2010) and the year 2040 (fig. 15). Overall, average Big Sagebrush productivity for this area from the 

present time to 2040 will decline about 20 percent. In the figure, productivity points derived from the weather-related models are 

Figure 14. Location of lidar data acquisition within the Yukon River Basin study area and preliminary biomass 

product generated from lidar canopy height data and height-based allometric biomass equations.
14 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

shown, and lines that were fit to the data points display the mean productivity trend for the landscape through time. Projecting 

future productivity of Big Sagebrush in the Owyhee Uplands and being able to compare that productivity to past levels can be 

tools used to formulate adaptive range, wildlife and watershed management strategies. For further information, contact Bruce 

Wylie, USGS EROS, wylie@usgs.gov.

Ecosystem Performance Anomalies in the Owyhee Uplands

Ecosystem performance monitoring using remote sensing, geospatial analyses, and modeling technologies provide a valuable tool for researchers and land managers, especially when they are faced with a changing global climate that presents new 

threats to ecosystem stability. The monitoring of ecosystem performance can be difficult to interpret and put into an appropriate 

context if management decisions and disturbances cannot be separated from an ecosystem’s climate. Ecosystem performance 

anomaly (EPA) studies conducted in the Owyhee Uplands do separate effects of climate from effects of management decisions 

and disturbances like overgrazing and fire. 

The Bureau of Land Management (BLM) is responsible for the sustainable management for most of the Owyhee Uplands, 

a shrub-steppe environment located in the Great Basin of the western United States, and USGS EROS provided the BLM with 

results from EPA studies for this area for the years 2000–2008. Products delivered to the BLM include annual maps of ecosystem performance anomalies and areas of persistent ecosystem overperformance and underperformance. These areas of persistent 

anomalies are shown in the map (fig. 16). The annual and persistent anomaly maps from these studies can assist the BLM by 

identifying areas for field visits and possible range interventions, helping to maximize the effectiveness of limited resources. For 

further information, contact Bruce Wylie, USGS EROS, wylie@usgs.gov.

Figure 15. The time-series cluster analysis 

reveals a long-term decline of higher 

producing Big Sagebrush areas, especially 

from the present time (2010) to 2040. Trends 

of similar or slightly increased productivity 

levels were predicted for the lowest producing 

areas. Areas of moderate productivity trended 

downward or remained at similar productivity 

levels.

Figure 16. The persistent anomaly map displays areas that overperformed or 

underperformed at least 6 of 9 years studied. Areas on the map in shades of red 

or gray show areas of possible concern for land managers.
Science and Applications Activities 15

Dynamic Monitoring of Ecosystem Performance for Upper Colorado River Basin 

Ecosystem performance (a surrogate for ecosystem productivity) provides important information to decision makers for 

land management. Currently, the growing season-integrated Normalized Difference Vegetation Index (NDVI) derived from 

satellite observations is used as a proxy for ecosystem performance. Interpreting ecosystem performance variation is complex 

because of the effects of weather, site potential, natural disaster, and anthropogenic effects. For moisture-limited rangelands, 

the interannual variation in vegetation productivity is substantially related to the local weather conditions, management, and 

disturbances. The approach is to separate weather- and nonweather-related variations in growing season NDVI (for example, 

annual ecosystem performance) and make historical trend maps in weather- and nonweather-related variations. Identification and 

quantification of areas with long-term persistent ecosystem performance anomaly (EPA) within the Upper Colorado River Basin 

based on satellite observations, weather data, and ecosystem models is shown in figure 17. The EPA maps were validated using 

“percentage of bare soil” ground observations. The validation results at comparable site potential indicated that regions identified as persistently underperforming (over-performance) tended to have a higher (lower) percentage of bare soil, suggesting that 

our EPA maps agree with ground-based observations. The resulting EPA maps can be used by the Bureau of Land Management 

and other land managers for making optimal land management decisions. 

Future work for this study includes generating 10-year (2001–2010) EPA maps within the Upper Colorado River Basin 

using 10-year satellite observations, climate data, and ecosystem models, and identifying long-term (that is, 10-year) persistent 

EPA areas and trends as well as weather-based variations in vegetation production. Investigation of ecosystem performance 

anomalies for the other vegetation cover types (for example, black sagebrush, mixed desert shrub, per the request of BLM and 

other land managers) are also planned for the future. For further information, contact Bruce Wylie, USGS EROS, wylie@usgs.

gov. 

Climate Change: Are High Latitude Lakes Drying?

Several recent studies report that changing climate at high latitudes impacts lakes, causing an increase in lake drying. If 

permafrost continues degrading in a warming climate, researchers expect many lakes to decrease in size until they eventually 

disappear. This decrease in the number of lakes may have a negative effect on wildlife. To aid in predicting future water levels 

and the locations of drying lakes under multiple climate scenarios, measurements of recent surface water changes are needed. 

The results will provide information for land managers.

Many of the recent studies that documented decreases in surface water were based on temporally and seasonally limited 

remotely sensed measurements. The measurements of the lakes occurred on only two or three dates and compared aerial photos 

and satellite data from different sensors. Since many lakes and wetlands have high seasonal or annual variability, measurements 

Figure 17. Example 

Ecosystem Performance for 

Big Sagebrush in the Upper 

Colorado River Basin (2006).
16 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

were made of the surface water on 20 dates from a single source, Landsat. The 20 Landsat scenes capture surface water throughout the growing season during a 30-year period, from 1979 to 2009. Indications were that during this 30-year period, more than 

96 percent of lakes did not significantly change in size (fig. 18). Only 2.5 percent of lakes significantly decreased in size (fig. 

19) while just less than 1 percent significantly increased in size. This results in a net decrease of 1.6 percent. After future climate 

scenarios are integrated, estimations will be presented of when each of the drying lakes will disappear and the amount of carbon 

that could be exposed from each drying lake’s sediments. For further information, contact Bruce Wylie, USGS EROS, wylie@

usgs.gov.

Boreal Forest Performance Anomalies in the Yukon River Basin

Climate change impacts in high northern latitudes are greater than other areas of the globe and have resulted in record fire 

years as well as insect infestations and permafrost degradation. High latitude soils in the Yukon River Basin hold large amounts 

of organic matter in both the surface organic layer and in permafrost. Organic carbon in these layers may be vulnerable to emission into the atmosphere in a changing climate. 

The growing season Normalized Difference Vegetation Index (GS NDVI) was used as a proxy for boreal forest production 

or the performance of the boreal ecosystem. Interannual variations in GS NDVI are affected by variations in weather conditions 

and disturbances. Because weather affects GS NDVI, weather was accounted for with regression tree models that predict GS 

NDVI. The residuals of this model provide weather de-trend GS NDVI anomalies. The model residuals were mapped annually from 2000 to 2008 and represent ecosystem performance anomalies where a site is either underperforming relative to its 

weather-based potential, responding normally to its weather-based potential (normal or within the 90 percent confidence intervals), or overperforming relative to its weather-based potential. 

Time series analysis was used to effectively identify disturbance and weather-related variations. Linear time series analysis 

of the performance anomalies (disturbances) clearly identified known disturbances such as fires which occurred late in the study 

period while nonlinear analysis identified disturbance date and post disturbance recovery rates (fig. 20). This approach provides 

a useful method for monitoring and understanding burned and unburned boreal systems responses to a variable and changing 

climate. For more information, contact Bruce Wylie, USGS EROS, wylie@usgs.gov.

Figure 18. An example of a lake (name unknown, Yukon Flats, Alaska) with no significant surface water 

change between May 1979 and May 2009.

Figure 19. An example of a lake (Twelve Mile Lake, Yukon Flats, Alaska) with significant drying between 

May 1979 and May 2009.
Science and Applications Activities 17

Adapting to Climate Change by Re-Greening Landscapes in West Africa’s Sahel

The Sahel, the semiarid strip of land along the southern fringe of the Sahara, is known for its harsh environment. Low 

annual rainfall, poor soils, locusts, and drought are all problems faced by millions of farmers who strive to produce enough 

food to feed a growing population. Throughout the past 30 years, however, hundreds of thousands of farmers in Burkina Faso 

and Niger have transformed large swaths of the region’s arid lands into a greener landscape, improving food security for about 

3 million people (fig. 21). Once-degraded and denuded landscapes are now transformed into open tree parklands that provide a 

much improved environment for crops, livestock, and people. Sahelian farmers achieved their success through innovations that 

modify traditional agroforestry, water, and soil management practices. Having lived through the terrible droughts of the 1970s 

and 1980s, farmers are adapting to climate change by taking new approaches to farming, encouraging natural regeneration of 

on-farm tree cover, and diversifying production (fig. 22).

With support from the U.S. Agency for International Development, USGS EROS scientists have teamed up with African 

and European geographers and ecologists to document and study the re-greening of the Sahel’s landscapes. The EROS team 

used time-series, high-resolution remote sensing and field studies to map the extent and impact of the agro-environmental transformation, including increases in biomass, carbon, biodiversity, and food and fodder production (fig. 23). The team’s findings 

suggest a human and environmental success story at a scale not seen anywhere else in Africa. 

In the coming year, the EROS team will continue to work with African and European partners and the World Agroforestry 

Center to better understand the driving factors of re-greening, and to seek ways of promoting the adoption of these practices into 

other regions still plagued by land degradation. This is part of a new vision for agricultural landscapes across Africa, conservation farming that integrates trees with annual food crops. This combination of practices is now referred to as Evergreen Agriculture. The objective is to build a healthy soil and environment to enhance food crop production, increase household income, 

increase on-farm biomass and carbon, and increase resilience of agricultural communities to climate change. EROS expertise in 

remote sensing and other geospatial tools will play an increasingly vital role in monitoring the extent and impacts of Evergreen 

Agriculture, and for effective targeting of investments to expand it. Two recent publications on this work include: 

Reij, C., Tappan, G.G., and Smale, M., 2009, Agroenvironmental transformation in the Sahel–another kind of “Green Revolution”: Discussion Paper, 914, 52 p. (Also available online at http://www.ifpri.org/book-5826/millionsfed/pubs).

Reij, C., Tappan, G.G., and Smale, M., 2009, Re-Greening the Sahel–farmer-led innovation in Burkina Faso and Niger, chap. 7 

in Spielman, D.J., and Pandya-Lorch, R., eds., Millions fed–proven successes in agricultural development: Washington, D.C., 

International Food Policy Research Institute, p. 53-58. (Also available online at http://www.ifpri.org/book-5826/millionsfed/

pubs).

For further information, contact Gray Tappan, USGS EROS, tappan@usgs.gov.

Figure 20. Time series analysis of boreal 

forest performance anomalies to identify 

linear and nonlinear trends.
18 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Figure 21. General location (white areas) of 

landscape regreening, where farmers have 

adopted practices that have substantially improved 

environmental and agricultural conditions. 

Figure 22. Hand-irrigated vegetable cultivation 

surrounded by dense tree parkland dominated 

by the winter thorn tree (Faidherbia albida). Tree 

parklands have increased in density and extent 

across 5 million hectares of southern Niger. The 

winter thorn tree provides many benefits, including 

boosting crop yields by fixing nitrogen in the soil, and 

providing fodder for livestock. Adouna Valley, Niger. 

Photograph: C. Reij. 

Figure 23. Comparison of an aerial photograph (left, 1975) and a QuickBird satellite image (right, 2005) 

showing the much increased tree cover of agricultural landscapes in southern Niger. Note that the large 

village in the 2005 image did not yet exist when the 1975 photograph was taken.
Science and Applications Activities 19

Monitoring Biodiverse Forests and Protected Areas in West Africa’s Upper Guinean Forest 

Ecoregion

The Upper Guinean Forest Ecosystem is a priority for biodiversity conservation (fig. 24). It is also a region of strategic 

importance in terms of peace building, extractive industries, and as a source of valuable ecosystem services and products. The 

forests are fundamental to the welfare of West African societies, have great cultural importance, and have considerable value 

for mitigating climate change. This unique, fragile block of forest is contained within Guinea, Sierra Leone, Liberia, and Côte 

d’Ivoire. Several USGS EROS scientists are working closely with partners in the four countries to monitor land cover, biodiversity, deforestation, and a variety of land management practices that aim to strengthen natural resource management and 

sustainable livelihoods. Funding for this activity is from USAID/Guinea and USAID/West Africa. The project targets biodiverse 

habitats within protected and nonprotected transboundary areas along country borders. Major partners include the existing 

government initiatives such as the Mano River Union, national forestry departments, the U.S. Forest Service, the World Agroforestry Center, the Wild Chimpanzee Foundation, and the PAGE Project (Promoting Agriculture, Governance, and the Environment, Sierra Leone). 

Throughout the past year, the EROS team provided satellite imagery, produced land cover and forest maps, and provided 

landscape assessments to:

• Map and quantify the remaining dense forest cover in Sierra Leone (fig. 25);

• Provide scientific support for establishment of wildlife migration corridors between the Taï Forest and Sapo Forests of 

Cote d’Ivoire and Liberia;

• Provide scientific support for creation of a network of protected areas along the Guinea-Sierra Leone border;

• Provide training on assessing land cover with satellite imagery;

• Provide land use and land cover data for sustainable land and forest management plans and implementing activities in 

forestry, agroforestry, protected area management, and biodiversity conservation within communities along the GuineaSierra Leone border; and

• Provide image-maps of a large part of Sierra Leone in support of the PAGE Project’s work with communities to engage 

in forest management (fig. 26).

For further information, contact Gray Tappan, USGS EROS, tappan@usgs.gov.

Figure 24. A view of the cloud forest near the top of Mount Nimba. The Mount 

Nimba range is a transboundary reserve located on the border between Guinea, Cote 

d’Ivoire, and Liberia. It preserves unusually rich flora and fauna including a number 

of endemic species. It is one of the hotspots in the Upper Guinea Forest Ecoregion. 
20 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Assessing Human Impacts on Critical Environments in Senegal

USGS EROS geographers are working with Senegal’s Center for Ecological Monitoring (CSE) to monitor, map, and assess 

the extent and condition of the country’s ecosystems, including critical biodiverse hotspots, deforestation, and rapid land use 

change. The team is building on a rich experience of work in Senegal since 1982, using remote sensing and GIS to provide 

unique information to resource managers, development practitioners, wildlife conservationists, and ecotourists. A number of 

geographic products will allow them to “see” the land resources, both in their current state and through time. 

During the past year, the team focused on the Kedougou Region of southeastern Senegal. The region stands out for its 

relatively pristine landscapes—the last major refuge for wildlife and unbroken expanses of Sudanian zone vegetation. Some of 

Senegal’s most critical and biodiverse habitats are found there. It also includes the large Niokolo-Koba National Park, established in 1951 and more recently classified as both a biosphere reserve and as a World Heritage for Humanity site. Throughout 

Figure 25. This pair of maps compares primary and secondary dense forest cover in Sierra Leone from 1976 (left) to 2005–2009 (right). 

The remaining forest fragments and blocks are islands of biodiversity. Forest cover during this period declined from about 6 percent 

to just more than 2 percent of the national land area. Forest cover was mapped using Landsat and Advanced Spaceborne Thermal 

Emission and Reflection Radiometer (ASTER) imagery. 

Figure 26. One of 13 ASTER-based image maps produced of eastern 

Sierra Leone where existing maps are 30 years out-of-date. The maps 

are being used by the PAGE Project in support of formulating land use 

and forest management plans with local communities.
Science and Applications Activities 21

the past three decades, the biological resources of this enclave have been buffeted by degradation that threatens this fragile ecosystem (fig. 27). The region is experiencing a gold rush, with an influx of major international mining companies. Pristine areas 

are being opened up by new roads. There is an urgent need to balance economic exploitation with preserving ecosystem services 

and wildlife conservation. 

The EROS/CSE team has nearly completed a detailed land cover map of the Kedougou Region using Landsat, Advanced 

Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and high-resolution imagery (fig. 28). Several derived 

maps are being prepared, including a relative wildness map important for identifying undisturbed areas and wildlife corridors, a 

biodiversity hotspot map, and an ecotourism map of Niokolo Koba National Park. EROS is working with a number of partners 

in Senegal who will use the geographic products for numerous applications, including:

• Work with chimpanzee conservation groups to map areas of five known chimpanzee populations and assess the threat of 

habitat fragmentation from farming and logging; prepare maps for ecotourism;

• Work with the Directorate of Mines to help them monitor the impact of industrial mining on the environment, including 

deforestation and downstream pollution;

• Work with the Forest Department and rural community governments to produce forest management plans for unprotected 

community forests;

• Work with the National Directorate of Parks to promote development of the Niokolo Koba National Park and to promote 

ecotourism; and

• Work with the National Directorate of Parks and local authorities to assist in the creation of a new protected area—the 

Dindefelo Nature Reserve.

For further information, contact Gray Tappan, USGS EROS, tappan@usgs.gov.

Figure 27. EROS environmental scientists and their counterparts from CSE are monitoring vegetation 

structure and biodiversity changes at hundreds of ground sites across Senegal, including sites like this 

one in southeast Senegal. This photograph pair compares the same landscape in 1995 (top) and 2006 

(bottom). Woody species inventories show significant decline in biodiversity and habitat quality. The team 

is revisiting sites they originally established in 1983. 
22 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Mapping Land Cover through the Decades in East Africa

EROS scientists teamed up with counterparts from the Regional Centre for Mapping of Resources for Development 

(RCMRD) in Nairobi, Kenya to bring the experience of time-series land cover mapping from West Africa to East Africa. The 

primary goal is to build capacity among environmental institutions in East Africa to use Landsat and other imagery to map and 

monitor land cover through time. Monitoring trends in land cover also is an important goal of SERVIR-Africa, which integrates geographic data from many sources to provide decision makers with a synthesized view of their regions. SERVIR is the 

Regional Visualization and Monitoring System for environmental management and disaster response. This effort culminated in 

a workshop facilitated by two EROS geographers at RCMRD in May 2010 (fig. 29). National Aeronautics and Space Administration’s SERVIR-Africa Program funded this activity. RCMRD is one of three regional remote sensing and mapping centers 

in sub-Saharan Africa and has a long history of collaboration with EROS. The workshop provided an opportunity to share the 

experiences and approach of time-series mapping that EROS developed and used for mapping a vast area of West Africa. Twelve 

participants from five countries (Kenya, Uganda, Rwanda, Ethiopia, and Tanzania) attended the training, along with RCMRD 

staff. 

EROS facilitators introduced the Rapid Land Cover Mapper tool. Participants used it to produce time-series maps of two 

areas in Kenya. The resulting land cover maps were checked and validated during a short field trip (fig. 30). The Rapid Land 

Cover Mapper provides a unique and practical way of mapping land cover over large areas through time. It is particularly wellsuited to incorporating a wide variety of image sources, ranging from digital multispectral imagery to analog panchromatic 

photography. Users can reach back in time to map land cover in the 1940s and 1950s with aerial photography, and potentially 

worldwide in the 1960s using Corona satellite photography. The conceptually simple 

approach produces raster format land cover maps that can easily be compared to 

assess change. There is much interest on the part of RCMRD and the participating 

institutions in completing time-series land cover maps for their respective countries. 

For further information, contact Gray Tappan, USGS EROS, tappan@usgs.gov. 

Figure 28. This map is a small portion of a Land Cover Map of the Kedougou Region of Senegal. The 

map is being prepared from ASTER and Landsat imagery. The map and supporting field work will be 

used to produce several derivative themes, including a Relative Wildness Map and a Biodiversity 

Hotspot Map.

Figure 29. Participants from five East African countries attended the workshop in 

time-series land cover mapping at the Regional Centre for Mapping of Resources for 

Development, Nairobi, May 2010.
Science and Applications Activities 23

Topographic Processing Service for South America – Andean Development Bank GeoSUR Program

The USGS collaborated with the Andean Development Bank (CAF) GeoSUR program and released a web service tool 

that provides access to Shuttle Radar Topography Mission (SRTM) 30-meter resolution elevation derivative products for the 

continent of South America. Designed and implemented at the USGS EROS Center, this tool allows these countries to securely 

access SRTM’s full 1-arc-second (30-meter) resolution digital elevation model (DEM) via the Internet to produce elevationderived products. These higher resolution products allow users to extract detailed information allowing better natural disaster 

prevention and mitigation, natural resource management, and local and international infrastructure development.

The GeoSUR program optimized access to and the use of the derivative products by developing a dynamic geoprocessing 

web service that allows users to dynamically request derivative products from restricted SRTM source data in a secure environment, evaluated and approved by the National Geospatial-Intelligence Agency (NGA). Labeled as the Topographic Processing 

Service (TPS), it initially offers tools (models) to allow users to request slope, aspect, shaded relief (hillshade), and an elevation 

reclassification from a gap-filled SRTM 30-meter data source (fig. 31). 

The USGS EROS Center is hosting the service for GeoSUR in order to meet the security requirements defined by NGA and 

has implemented the Environmental Systems Research Institute’s (ESRI’s) ArcGIS Server for handling geoprocessing requests. 

By using the ArcGIS Server, the program can offer multiple methods of accessing the derivative tools. Not only can users 

request data products from the web-mapping interface (fig. 32), they can access the same tool through ESRI’s ArcGIS desktop 

products or from the ArcGIS JavaScript application programming interface, allowing users to build custom tools and web application. For further information, contact Larry Tieszen, USGS EROS, tieszen@usgs.gov.

Figure 30. Participants field-checked their draft land cover maps 

at a study area near Lake Naivasha, in Kenya’s Rift Valley.

Figure 31. Composite image of Topographic Processing 

Services available as digital elevation model derivative 

products.
24 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

EcoServ: An Integrated Web-Services-Based Ecosystem Services Modeling System

Many people are interested in natural resources management. The consequences of related policy decisions are multidimensional and often conflicting. A scenario “optimized” to one group might be a “risk” to another; therefore, models are needed that 

simultaneously quantify the impacts of management practices, policies, and climate change on diverse ecosystem services. EcoServ is such a modeling system; it was developed using data and model sharing technology and web services to accommodate 

a variety of users and purposes. EcoServ simulates more than 12 major ecosystem services related to water resources, wildlife, 

plants, soils, and greenhouse gas (GHG) emissions. It takes advantage of existing databases and disciplinary models by sharing 

them on the Internet. Scenarios of land cover and land use can be created easily in EcoServ by using the online Land Cover Editor. This feature allows users to simulate and analyze the impacts of management activities on ecosystem services under different climate change scenarios. EcoServ is especially suited for evaluating, understanding, diagnosing, monitoring, and forecasting changes of multiple ecosystem services in response to future changes in policy, climate, and land use (for example, biofuel 

production). EcoServ is being developed and applied in the Prairie Pothole Region (fig. 33) of the United States to quantify the 

impacts of U.S. Department of Agriculture’s programs (for example, Conservation Reserve Program and Wetland Reserve Program) and practices (for example, perennial grass, contour buffer strips, critical plantings, grassed waterways, biofuel production) on a wide range of ecosystem services. For further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov. 

Figure 32. GeoSUR geoprocessing web 

interface.

Figure 33. EcoServ Online Modeling System in 

a pilot study area of the Prairie Pothole Region.
Science and Applications Activities 25

Collateral Effects of Carbon Sequestration on Ecosystem Services

Many participants are involved in ecosystem management simultaneously affecting a myriad of Ecosystem Services (ES). 

However, a “good” option from the perspective of one user may be “bad” for another. Therefore, single land use evaluations 

may be misleading if the overall impact on the ecosystem is not evaluated. In Tensas Parish, Louisiana, and Claiborne County, 

Mississippi, 10 ecosystem services were simultaneously evaluated and compared under two management scenarios of R and 

L where R was a reference scenario, and L was an optimized land use scenario to enhance carbon sequestration for mitigating 

global warming. The major differences between R and L were with the land use, land cover, and land management (for example, 

wetland restoration, forest clear cutting). The outputs of these two scenarios were compared to the baseline (2001–2010). Since 

different ES have different definitions, ranges, and meanings, a ES Change Indicator (ESCI) was used to normalize all ES and 

made them comparable:

ESCI = (ES – ES0) / ES0

where ES refers to the output value of a selected ES, and ES0 is the corresponding baseline value of 2001–2010. However, to 

those ES where a higher ESCI value indicates a reduction in ES, “–1” was multiplied. Results determined the optimized L scenario improves the ecosystem carbon storage; however, it also shows reductions in grain and timber production, and increased 

CH4 emissions (fig. 34). This leaves the policy makers with two questions. Will the increased CH4 emissions, which are almost 

25 times that of CO2 in the greenhouse warming effect, offset efforts to mitigate global warming through carbon sequestration? 

Will this “optimized” scenario be acceptable by timber and agricultural stakeholders? Hence, a broader perspective and context 

with social and economic analysis is needed to evaluate and understand the concurrent effects of the optimized carbon sequestration on other ES. For further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Quantifying Water Storage Capacity of Topographic Depressions in the Prairie Pothole Region from 

Lidar and National Wetland Inventory Datasets

Recent flood events in the Prairie Pothole Region of North America have stimulated interest in modeling water storage 

capacities of wetlands and surrounding catchments to facilitate flood mitigation efforts. Accurate measurements of basin storage 

capacities have been hampered by a lack of high-resolution elevation data. A 0.5-meter bare earth model was developed from 

lidar data in combination with National Wetlands Inventory data. These data were used to delineate wetland catchments and 

spilling points within a 196-square-kilometer study area. 

Figure 34. Ecosystem Services Change 

Indicator of the reference and optimized 

scenarios compared to the baseline.
26 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

From the delineated catchments and spill points, the water storage capacity of individual basins was calculated; and since 

wetlands could be merged to create a larger wetland through “spill and overflow,” wetland connectivity also was modeled. However, storage capacity of basins does not fully translate into floodwater regulation because some wetlands are easily filled and 

overflow while others may never overflow. Therefore, the Basin Floodwater Regulation Index (BFRI) was calculated as the division of volume and catchment area. Based on the BFRI, the absolute and relative water that could be held by the wetlands over a 

landscape could be modeled if the water level before a flood was available, which was demonstrated with the water condition of 

May 17, 2008 (fig. 35). Being able to estimate the water holding capacity of the Prairie Pothole Region basins will aid efforts in 

quantifying the role that these basins play in mitigating downstream flooding. 

This work is in collaboration with the USGS Northern Prairie Wildlife Research Center. For further information, contact 

Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 35. Prairie Pothole storage capacity and the capability of floodwater regulation. a) Floodwater potential 

distribution. Blue indicates the water when individual and isolated wetlands are full. Red indicates extended water when 

the wetland connectivity is considered. b) With the water level of May 17, 2008, before the flood event, the absolute and 

relative floodwater regulation under different precipitation events was modeled.
Science and Applications Activities 27

The Methodology Development for the USGS Land Carbon Project

The 2007 Energy Independence and Security Act mandated that the USGS develop a methodology for assessing the 

nation’s ecosystem capacity for carbon sequestration and mitigation of greenhouse gas (GHG) fluxes, including carbon dioxide (CO2

), CH4, and N2O. The USGS Land Carbon Project, created from this mandate, developed a methodology document 

describing the outline and necessary approaches for conducting this national assessment. Major components of the methodology 

framework include scenario development, land use and land cover change modeling, terrestrial and aquatic carbon and GHG 

modeling, uncertainty assessment, and analysis of management activities and ramifications.

The General Ensemble biogeochemical Modeling System (GEMS) plays a key role in the Land Carbon Project. The GEMS 

group has concentrated on the writing of Section 3.3.4 (Carbon Stocks, Carbon Sequestration, and GHG Fluxes of Terrestrial 

Ecosystems) and Appendix D (Methods for Carbon Stock, Carbon Sequestration, and GHG Fluxes of Terrestrial Ecosystems). 

The flowchart of GEMS is shown in figure 36. For more information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

GEMS Simulation Results for the Land Carbon Pilot Study Area

Estimating ecosystem carbon sequestration and greenhouse gas (GHG) emissions under various scenarios of future land 

cover and land use change is one of the key focuses of the Land Carbon Project. A pilot study area was chosen in the Land Carbon Project, which includes Tensas Parish, Louisiana, and Claiborne County, Mississippi. Three biogeochemical modeling methods (GEMS-spreadsheet, GEMS-CENTURY, and GEMS-EDCM) were used to estimate carbon change under future land use 

and land cover change scenarios, which were generated by the FORE-SCE model at 250-meter resolution from 2001 to 2050.

Figure 36. Flow chart of the GEMS. LANDFIRE, Landscape Fire and Resource Management 

Planning Tools Project; VCT, vegetation change tracker; MTBS, Monitoring Trends in Burn Severity 

Project; FIA, Forest Inventory and Analysis Program (U.S. Forest Service); C, carbon; K, potassium; 

USPED, unit stream power-based erosion and deposition; NASS, National Agricultural Statistics 

Service; NASWQ, National Action Plan for Salinity and Water Quality; MODIS, moderate resolution 

imaging spectroradiometer; JDF, joint frequency distribution; BGC, biogeochemical; EDCM, 

erosion deposition carbon model; DNDC, denitrification-decomposition; IBIS, integrated biosphere 

simulator; EnKF, ensemble Kalman filter; NetCDF, network common data form; NLCD, national land 

cover database; DEM, digital elevation model; STATSGO, U.S. general soil map; SSURGO, soil 

survey geographic database; NWI, national wetland inventory; CO2, carbon dioxide; Ndep, nitrogen 

deposition.
28 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

As an example, the spatial distribution of total ecosystem carbon stock simulated by GEMS-CENTURY is shown in figure 

37. Regional biomass carbon change simulated by the three biogeochemical models is summarized in figure 38. The model intercomparison provides a way to quantify modeling uncertainty. For more information, contact Shuguang Liu, USGS EROS, sliu@

usgs.gov.

Figure 37. Total ecosystem carbon stock simulated by 

GEMS-CENTURY in the pilot study area.

Figure 38. Comparisons of annual carbon 

sequestration rates of biomass carbon stock 

among three methods (GEMS-spreadsheet, 

GEMS-CENTURY, and GEMS-EDCM) using 

the “enhanced land use and land cover with 

reference land management” (L) scenario for 

the whole pilot study area from 2001 to 2050. 

Comparison made using the same models and 

the “reference land use, land cover, and land 

management” (R) scenario yielded similar 

results. Tg C/yr, teragrams of carbon per year.
Science and Applications Activities 29

Simulation of Lateral Movement of Soil and Carbon on Landscape

Lateral movement of ecosystem carbon across landscape and changes in vertical soil profile are important aspects in ecosystem carbon accounting; however, few biogeochemical carbon cycle models are capable of simulating carbon changes related 

to soil erosion. The USGS Land Carbon Project is attempting to link the Unit Stream Power-based Soil Erosion and Deposition 

model (USPED) with the Erosion-Deposition-Carbon-Model (EDCM) to make more detailed carbon estimates at watershed 

to regional levels. The soil erosion and deposition map created by USPED for the Mississippi Alluvial Plain Ecoregion and 

the Mississippi Valley Loess Plains Ecoregion is shown in figure 39. Results indicate that the 50-year trend of soil and carbon 

erosion is affected by land use activities. Decreased forest cutting and increased wetland restoration reduced soil erosion by 

approximately 20,000 tons per year. The next step is applying USPED and EDCM to dynamically update vertical soil profile and 

soil carbon content for the conterminous United States. For more information, contact Shuguang Liu, USGS EROS, sliu@usgs.

gov.

Figure 39. Spatial distribution of soil erosion and deposition is shown on the left. Trends of total soil erosion are shown on 

the right with blue lines indicating business as usual and purple lines indicating reduced forest cutting and increased wetland 

restoration.
30 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Contemporary Carbon Dynamics in U.S. Eastern Terrestrial Ecosystems

Carbon sequestration in terrestrial ecosystems is an important part of an overall carbon management strategy to help reduce 

CO2 concentrations in the atmosphere. U.S. terrestrial ecosystems may contribute substantially to global carbon sequestration; 

however, the magnitude, locations, underlying mechanisms, and temporal trends of terrestrial carbon sinks are highly uncertain. 

In order to resolve these challenging issues, the U.S. Carbon Trends Project at USGS quantifies the spatial and temporal changes 

of carbon sources and sinks in the conterminous United States from the 1970s to the 2000s using the General Ensemble Biogeochemical Modeling System (GEMS) developed at EROS.

GEMS uses Monte Carlo sampling and ensemble Kalman filter techniques to incorporate land use and land cover change, 

climate variation, soil variability, and land management practices into a biogeochemical model. In this study, simulations were 

carried out in sample blocks (10x10 km or 20x20 km) from the USGS Land Cover Trends Project.

Panel A (fig. 40) shows the Ridge and Valley ecoregion removed CO2 from the atmosphere from 1973 to 2000 at a rate of 

about 97 grams of carbon per square meter per year (g C m–2 yr–1) with a strong interannual variability. Soils were a small carbon 

sink, and the sink strength was not sensitive to the interannual variability of disturbances and climate. Panel B (fig. 40) shows 

that ignoring land cover change leads to overestimation of net ecosystem exchange (NEE) or the strength of carbon sinks. For 

further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Spatiotemporal Dynamics of Water Loss because of Evapotranspiration in the Great Plains

Evapotranspiration (ET), one of the major components of the water cycle, accounts for about 70 percent of precipitation in 

the United States. Though ET is expected to alter because of climate change, its intensity and spatial patterns will depend upon 

local variables and forcings. An energy balance modeling approach was used to quantify the spatial and temporal distribution of 

ET for the 2001 growing season with Landsat (path 28, row 31) images. Temporal progression of ET captured the phenological 

stages during the crop growing season (fig. 41). During 2001, in general, crops had higher ET during July and August, and lower 

ET with maturity in September and harvest in October. Spatial distribution of ET showed lower ET from urban settlement (lower 

middle part) and barren land (lower left part) than from crop and grasslands. Results were validated with eddy covariance measurements. ET at an irrigated continuous maize site was estimated with a standard error of 0.7 millimeter (mm) day-1 (R2

 =0.93), 

while ET at a rain-fed maize-soybean rotation site was estimated with a standard error of 0.6 mm day–1 (R2 = 0.89). For further 

information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 40. Panel A displays the annual variation of carbon fluxes in the Ridge and Valley ecoregion from 1973 to 2000, where total 

carbon sink refers to the net carbon uptake by terrestrial ecosystems (that is, increase of plant biomass carbon and soil organic carbon 

(SOC), and harvest carbon in grain and wood). Panel B shows the impact of land cover change on net ecosystem exchange (NEE) in 40 

sample blocks each year, where Cs and Cd denotes NEE under static and dynamic land covers, respectively.
Science and Applications Activities 31

Modeling Gross Primary Productivity in the Mid-Continent Intensive Campaign Region of the North 

American Carbon Program

Primary production is the process of synthesis and storage of organic molecules during the growth and reproduction of 

photosynthetic organisms. Better understanding of primary productivity is important for sustainable ecosystems at regional and 

global scales because all forms of life on Earth depend on it. This study was carried out using the Eddy Covariance-Light Use 

Efficiency (EC-LUE) model for estimating gross primary productivity (GPP) in the Mid-Continent Intensive campaign region. 

The EC-LUE model was selected because of its ability to compute GPP across the biomes. Landsat images from Nebraska (path 

28, row 31), Illinois (path 23, row 31), and Wisconsin (path 25, row 28) were used for this study. Spatial and temporal progression of GPP depicted the dynamics of primary productivity in the region. GPP dynamics for the Nebraska site are shown in 

figure 42. Validation of GPP estimates with eddy covariance estimated GPP indicated that more than 90 percent of the variability 

can be explained. For further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 41. Evapotranspiration maps showing the water loss because of evapotranspiration on (a) July 4, (b) 

August 5, (c) August 13, (d) August 29, (e) September 30, (f) October 16, (g) October 24, and (h) December 11, 

2001. Location of the study area and legend for evapotranspiration maps are shown in the lower-right corner.
32 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Computing Seasonal Evapotranspiration in the Great Plains Using Satellite Images

Evapotranspiration (ET) plays an important role in water balance studies at local, regional, and global scales. Estimates of 

seasonal ET have many applications in water resources planning and management, including hydrological and ecological modeling. However, computing seasonal ET from temporal satellite images is very challenging because of either limited availability 

of cloud-free images or long repeat cycle of satellite overpass. This study was conducted to determine the suitability of three different methods (cubic spline, fixed, and linear interpolation) for estimating seasonal ET from temporally sparse Landsat images 

(path 28, row 31). All three methods resulted in a similar pattern of seasonal ET distribution (fig. 43). However, the density plot 

of seasonal ET indicated that the linear method was in closer agreement with the fixed method than the cubic spline (fig. 44).

Seasonal ET estimated using cubic spline was in better agreement with the eddy covariance measured seasonal ET, particularly if no or only one image per month was available. However, the fixed and linear methods resulted in comparable performance when two or more images per month were available. Validation of seasonal ET using eddy covariance tower measurements indicated that all three methods resulted in higher (18 percent) seasonal ET. For further information, contact Shuguang 

Liu, USGS EROS, sliu@usgs.gov.

Figure 42. Gross primary productivity maps derived from Landsat (path 28, row 31) for (a) July 4, (b) August 

5, (c) August 29, (d) September 30, (e) October 16, and (f) December 11, 2001. The GPP values are in grams of 

carbon per square meter per day (g C m–2 day–1).
Science and Applications Activities 33

Figure 43. Cumulative seasonal evapotranspiration (July–December) for 2001 

growing season using (a) cubic, (b) fixed, and (c) linear methods.

Figure 44. Density plot of seasonal evapotranspiration for (a) cubic and fixed methods, 

(b) cubic and linear methods, and (c) fixed and linear methods.
34 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Effects of Spatial Resolution of Satellite Sensors on Seasonal Evapotranspiration Estimates

Seasonal evapotranspiration (ET) was estimated in the Great Plains using 30-meter Landsat (path 28, row 31) and 1-kilometer MODIS images. These images were acquired on July 4, August 5, August 13, August 29, September 30, October 16, October 24, and December 11, 2001. Daily ET on the days of the satellite overpass was computed using an energy balance approach, 

and seasonal ET was computed using cubic spline interpolation of daily ET. The spatial resolutions of Landsat and MODIS data 

affected the seasonal ET distribution and magnitude as shown in figure 45.

The mean seasonal ET from July to December was 422 millimeters and 431 millimeters using MODIS and Landsat images, 

respectively. Though the mean seasonal ET using Landsat images was close to the ET using MODIS images, the spatial distribution was quite different (fig. 46). The higher spatial resolution of Landsat shows the variation of ET even at field scale, which 

cannot be seen from MODIS-estimated ET. For further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Sensitivity of Hydrological Processes to Climate Change in the Upper Mississippi River Basin

Global warming has become more apparent in recent decades, 

as evident from observations of increasing global average air and 

ocean temperatures, widespread melting of snow and ice, and rising 

global sea levels. Future warming because of increasing anthropogenic 

releases of CO2 is projected to alter potential evapotranspiration (ET) 

with the most immediate effect being an increase in the ability of air to 

absorb water as temperature rises. Therefore, potential consequences 

of an elevated atmospheric CO2 concentration may change the temporal and spatial distribution of precipitation. 

Sensitivity studies of temperature and precipitation variations can 

provide important information regarding the responses and vulnerabilities of different hydrologic systems to climate change. Using the Soil 

and Water Assessment Tool (SWAT), the hydrological responses to 

changing climate variables (for example, CO2, precipitation, and temperature) in the Upper Mississippi River Basin were estimated. Eight 

model setups were used to test model sensitivities. The study results 

show that water yield changed linearly with precipitation (fig. 47 and 

table 1). However, water yield and soil water content decreased dramatically when temperature increased, while simulated ET remained 

proportional to the temperature rise. For further information, conta 

Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 45. Seasonal evapotranspiration 

(millimeters) from July to December 2001 growing 

season using (a) Landsat and (b) MODIS images.

Figure 46. Effect of spatial resolution on estimated 

seasonal evapotranspiration.
Science and Applications Activities 35

Hydrological Responses to Rising Atmospheric Carbon Dioxide (CO2) Concentration in the Upper 

Mississippi River Basin

Increased atmospheric CO2 concentration and future climate change will have significant impacts on hydrological systems. 

Quantifying and understanding the hydrological responses to an elevated ambient CO2 and climate change is critical for formulating adaptive strategies to manage water resources. This study examined the impacts of increased CO2

 in the Upper Mississippi 

River Basin using a modified Soil and Water Assessment Tool (SWAT). To adequately estimate the impacts of increased CO2

in past decades, the constant CO2 in the original SWAT was replaced with historical monthly CO2 concentration observations. 

Vegetation responses to elevated CO2 such as vegetation-specific stomatal conductance reduction and leaf area increase have 

been implemented in the revised model. 

The results indicate that streamflow has increased by 1 to 8 millimeters per year (1 to 4 percent) from 1987 to 2008 because 

of CO2 increase (fig. 48). A strong relation between the increase in streamflow and the increase in CO2 concentration is shown 

in figure 49. Specifically, a doubling of current CO2 concentration may lead to an increase of about 50 millimeters in streamflow 

under current climate conditions in this Basin. For further information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 47. Comparison of simulated streamflow and soil water content under changing precipitation and 

temperature scenarios.

Table 1. Predicted relative changes in annual average hydrological components for the climate change sensitivity 

simulations.

[CO2, carbon dioxide; %, percent; °C, celsius]

Hydrological

components

Reference 

(mm/yr)

Climate sensitivity simulations

CO2 Precipitation Air tempurature

600 +10% +20% +30% +40% +1oC +2oC +4oC

Percentage change

Water yield 244 23 28 57 -26 -50 -7 -14 -33

Evapotranspiration 561 -11 2 4 -3 -6 3 7 15

Soil water content 190* 7 3 6 -5 -13 -1 -3 -9

Groundwater recharge 129 31 25 50 -25 -49 -5 -12 -35

*

Unit of soil water content is millimeters.
36 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Grazing Affects DOI Land Carbon Dynamics, but with High Uncertainty

Twenty-five percent of the Nation’s lands are managed by the Department of Interior (DOI). DOI lands store a large 

amount of carbon, but no systematic research has been performed on carbon status and trends. To study the current carbon status 

and address the impacts of different management practices on these public lands, USGS EROS is using the General Ensemble 

Biogeochemical Modeling System (GEMS) and existing regional databases (such as land cover, soil, and climate) to quantify 

ecosystem carbon dynamics for historical, current, and future carbon stocks in vegetation and soils. 

For example, the carbon status of the Green River Basin (GRB) in Wyoming, which is largely managed by the Bureau of 

Land Management (BLM) in DOI, was studied. Grazing management is a dominant driving force affecting carbon dynamics 

in GRB. To evaluate the impacts of different grazing management practices, we used GEMS to simulate the ecosystem carbon 

sequestration under different scenarios. The simulated vegetation production agreed with MODIS vegetation production and 

U.S. Department of Agriculture census hay production from pasture lands. 

The spatial distribution of ecosystem carbon sinks (carbon gain) and sources (carbon loss) in GRB is shown in figure 50. As 

a whole, GRB was a weak carbon sink of 6 g C m–2 yr–1 from 1970 to 2000. Model simulations indicated grazing intensity had 

different impacts on production and ecosystem carbon dynamics in this area, but the uncertainty of the impacts was high mainly 

because of the lack of grazing information (such as location, time period, and animal type). For further information, contact 

Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 49. Relation between the 

increase in streamflow per unit 

precipitation and the increase in carbon 

dioxide concentration.

Figure 48. Simulation of streamflow increase because of the elevated atmospheric carbon dioxide 

concentration and contribution percentage since 1987.
Science and Applications Activities 37

General Ensemble Biogeochemical Modeling System (GEMS) Development

Ecosystem carbon sequestration has been recognized by international communities as a major means of reducing atmospheric CO2

 concentration. Estimating the impacts of changes on land use, land cover, and climate on carbon sequestration, 

while important to decision and policy makers, is challenging. To quantify carbon sequestration over large areas, we have 

developed and successfully applied GEMS in multiple terrestrial ecosystems (such as forest, cropland, and grassland) around the 

world (fig. 51).

GEMS has been selected by the USGS Land Carbon Project as the backbone biogeochemical modeling system for assessing the Nation’s ecosystem capacity for carbon sequestration and reduction of greenhouse gas emissions (CH4

 and N2O). Further 

development of GEMS in areas such as parallel computing, model integration, model ensemble, data assimilation, and webservices-based application will substantially help to fulfill the USGS Land Carbon Project’s missions. For further information, 

contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 50. Spatial distribution of carbon 

sinks and sources in the Green River 

Basin simulated by General Ensemble 

Biogeochemical Modeling System from 

1970 to 2000.

Figure 51. Structure of the General Ensemble Biogeochemical Modeling System.
38 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Impacts of Management Practices on Cropland Carbon Sequestration in Mid-Continent Intensive 

Region

Large discrepancies usually exist between atmospheric and ecosystem model results in quantifying carbon fluxes over vast 

areas. As part of the North American Carbon Program, the Mid-Continent Intensive (MCI) Campaign compares and reconciles 

regional carbon flux estimates by “top-down” atmospheric models and “bottom-up” ecosystem models to identify the dominant 

mechanism of regional carbon flux. Collaborative work activities occurred with scientists from universities and other agencies 

to provide ecosystem carbon flux estimations with uncertainties in the MCI region using the General Ensemble Biogeochemical 

Modeling System (GEMS). 

Cropland soil carbon changes under different tillage management scenarios is shown in figure 52. This research will not 

only improve scientific understanding of carbon dynamics in MCI but also will benefit land resource managers in choosing proper management practices to enhance the cropland carbon sequestration in the region. For further information, contact Shuguang 

Liu, USGS EROS, sliu@usgs.gov.

Will Climate Change Stimulate Greenhouse Gas Fluxes in Wetlands? Greenhouse Gas Research in 

the Prairie Pothole Region

The Prairie Pothole Region (PPR) contains a large number of freshwater wetlands. Greenhouse gas (GHG) emissions of 

CO2, CH4, and N2O from these wetlands are poorly understood and quantified. Work is ongoing in cooperation with the USGS 

Northern Prairie Wildlife Research Center (NPWRC) to simulate GHG emissions from wetland catchments for estimating 

spatial and temporal global warming potential in the PPR. This research will not only help to quantify the wetland contributions 

to global warming but also will help to understand climate change impacts on GHG emissions. The results can provide valuable 

information for resource managers and government agencies to apply proper management practices to reduce the GHG emissions from wetlands in the PPR.

The NPWRC collected GHG emissions data in more than 130 wetland catchments across the PPR region. Focusing on 

wetlands dominated by grass in upland catchments, scientists integrated MODIS Gross Primary Production data into a processbased biogeochemical model DNDC (Denitrification-Decomposition) to simulate the GHG emissions. Simulation results agreed with field measurements and 

explained seasonal changes in GHG emissions (fig. 53). This research indicates 

that the seasonal GHG emissions from PPR wetland catchments were determined 

by the upland vegetation growth and wetland hydrological conditions. For further 

information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov. 

Figure 52. Annual soil organic carbon (SOC) changes in the top 20 centimeters between 

2000 and 2007 per county in the Mid-Continent Intensive region for three tillage scenarios.

Figure 53. Green indicates the location of the Prairie Pothole Region.
Science and Applications Activities 39

Evaluating Ecosystem Sustainability under Biofuel Pressure

The demand for agricultural biomass for energy is expanding cropland into grassland-dominated systems, altering traditional crop rotations, and exploiting grassland and Conservation Reserve Program (CRP) systems. The societal need for renewable energy from the agricultural sector offers new opportunities and challenges. This project is designed to evaluate impacts of 

current land use and projected biofuel production scenarios on ecosystem services and sustainability across the Northern Great 

Plains by developing a modeling system to integrate GEMS, FORE-SCE, and economic models. 

Model simulation results are shown in figure 54 for a 260-square-kilometer Prairie Pothole area in North Dakota: (1) annual 

ecosystem carbon fluxes and soil carbon budgets were mainly regulated by land use and management practices; and (2) the rate 

of soil carbon stock change was dependent mainly on the soil carbon stock level. Ecosystem sustainability mainly depends on 

land use and biomass removal intensity. Simulation results suggest that the current modeling system is capable of evaluating 

changes of ecosystem goods and services related to land use activities for biofuel production. For more information, contact 

Shuguang Liu, USGS EROS, sliu@usgs.gov.

A New Approach for Estimating Global Evapotranspiration and Gross Primary Production

To quantify and assess how climate change affects carbon, energy, and water budgets, a light use efficiency model, called 

EC-LUE, was developed and driven by MODIS Normalized Difference Vegetation Index (NDVI), photosynthetically active 

radiation, air temperature, and the Bowen ratio. The impacts of precipitation seasonality on evapotranspiration (ET) and Gross 

Primary Production (GPP) was examined using 54 towers’ eddy covariance observations worldwide from 2000 to 2003. Results 

showed that the estimates of ET and GPP agreed with those from other global models, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas (fig. 55). Results also imply the importance of seasonal variations 

of precipitation in regulating annual ET and the dependency of ET on ecosystem types. The EC-LUE, along with the revised 

Remote Sensing Penman-Monteith model, will provide an alternative approach to map ET and GPP over large areas. For more 

information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 54. Top: Soil organic carbon (SOC) stock in 1972. Bottom: Total change in soil organic carbon (SOC) from 

1972 to 2007.
40 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Improving Biogeochemical Simulations with Data Assimilation in the Yukon River Basin

Adequate quantification of the behavior of model parameters and the assessment of model output uncertainty are challenging in regional carbon cycle modeling efforts. To address these challenges, parameter optimization and data assimilation algorithms (SEnKF) were integrated into the General Ensemble Biogeochemical Model System (GEMS). Some results at a boreal 

forest eddy covariance site within the Alaskan Yukon River Basin are presented in figure 56. GEMS predictions of net ecosystem 

exchange (NEE) can be improved by adjusting model parameters dynamically and/or updating system states using data assimilation. Predicted NEE uncertainties stemming from errors of parameters, input, and model structure can also be reduced. The new 

knowledge gained from data assimilation on parameter behavior can be used to evaluate errors in GEMS structure and representations of fundamental biogeochemical processes. For more information, contact Shuguang Liu, USGS EROS, sliu@usgs.gov.

Figure 55. Left: Simulated global evapotranspiration (ET) pattern. Right: Simulated global Gross Primary Production (GPP) 

distribution.

Figure 56. Upper panel shows comparisons of net ecosystem exchange (NEE) 

simulated by data assimilation (that is, SEnKF) (blue diamond) and by GEMS alone 

(green triangle: with pre-determined parameters, blue triangle: with parameters 

adjusted by data assimilation) against eddy covariance measurements (red 

square) at a boreal forest tower site in Alaska. Lower panel shows comparisons of 

corresponding ensemble-based standard deviations of NEE against errors of eddy 

covariance measurements.
Science and Applications Activities 41

Topographic Science, Elevation, and Lidar

The Topographic Science, Elevation, and Light Detection and Ranging (lidar) Team establishes partnerships and conducts 

research, technique development, dataset development, and applications focused on the study of the topographic land surface. 

Key accomplishments are given in the following sections. 

The Global Multi-Resolution Terrain Elevation Data (GMTED2010) Model

Many of the fundamental geophysical processes active at the Earth’s surface are controlled or strongly affected by topography, thus the critical need for high-quality terrain data. The USGS and the National Geospatial-Intelligence Agency (NGA) 

have collaborated on the development of a notably enhanced global elevation model named the Global Multi-resolution Terrain 

Elevation Data 2010 (GMTED2010) that replaces GTOPO30 as the elevation dataset of choice for global and continental scale 

applications. This new dataset will be useful in many hydrological, climatological, and geomorphological applications at both 

the regional and global scales. The new model is complete and has been generated at three separate resolutions (horizontal post 

spacings) of 30 arc-seconds (1 kilometer), 15 arc-seconds (500 meters), and 7.5 arc-seconds (250 meters) from the best available 

higher resolution data sources. The GMTED2010 product resolutions also match the resolutions of the Land Processes Distributed Active Archive Center (LP DAAC) Moderate-resolution Imaging Spectroradiometer (MODIS) data products. This new global 

elevation product suite will provide global coverage from 83°N to 90°S. The primary data source for this project is the voidfilled 1 arc-second Shuttle Radar Topography Mission (SRTM) dataset. In addition to providing a multiresolution data structure, 

seven new products have been generated at each resolution (7.5, 15, and 30 arc-seconds). The following elevation products 

have been produced: minimum, maximum, mean, median, standard deviation, systematic subsample, and breakline emphasis. 

Detailed spatially referenced metadata have been produced for all the data sources that constitute GMTED2010. 

Project accomplishments in FY 2010 included the completion of the GMTED2010 (fig. 57) data suite with products 

delivered to NGA for final review and acceptance. In addition, a final spatially referenced metadata dataset was completed that 

documents the input data sources used in the global model (fig. 58). Furthermore, a final accuracy assessment was completed 

that evaluated the GMTED2010 products against a global set of absolute photogrammetric control points provided to the USGS 

by NGA. Currently, final project documentation was delivered to NGA in October and the GMTED2010 products were released 

December 31, 2010. GMTED2010 has no redistribution restrictions and will be publicly available. For further information, contact Jeff Danielson, USGS EROS, daniels@usgs.gov.

Figure 57. The Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) replaces 

GTOPO30 as the elevation dataset of choice for global and continental scale applications.
42 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Hydrologic Derivatives Extracted from High-Resolution Lidar Elevation Data: USGS Scientific 

Investigations Report 2010–5059

As the need for flood hazard mapping and emergency response intensifies, more accurate hydrologic information is essential to improve the understanding of surface water movements, drainage patterns, flood inundation, and coastal erosion. Highresolution, high-vertical accuracy bare earth digital elevation models (DEMs) generated from light detection and ranging (lidar) 

data have become instrumental in extracting this valuable hydrologic derivative information. 

As lidar data become more prevalent for generating highly detailed DEMs, there is an increasing demand for lidar-derived 

hydrologic information. Because of lidar’s fine-scale ability to represent the surface of the Earth, a vast amount of detail is 

captured in the lidar-DEM. Although this detail is desirable for incorporating the best available elevation data into the National 

Elevation Dataset, extracting hydrologic information from high-resolution, high-vertical accuracy lidar-DEMs presents some 

challenges. 

Because lidar-DEMs are complex elevation surfaces, geographic features such as elevation data representing bridges, railroads, roads, or other elevated surfaces, are more prominent in lidar-DEMs than they are in coarse (30-meter) resolution elevation data. These geographic features result in obstructed hydrologic information that misrepresents the true surface flow on the 

landscape. Although the methods to extract hydrologic information from coarse (30-meter) DEMs are well documented in the 

scientific community, the methods to extract hydrologic information from high-resolution, high-vertical accuracy lidar-DEMs 

are less documented and are more complex. 

To accommodate the increasing need for hydrologic information extracted from high-resolution, high-vertical accuracy 

lidar-DEMs, the U.S. Geological Survey has ongoing research to develop selective drainage methods. These methods provide 

the capability to extract valuable and integrated hydrologic information from lidar-DEMs. The selective drainage methods have 

been developed and tested in Minnehaha County, South Dakota (fig. 59) and are published in a USGS Scientific Investigations 

Report (fig. 60). For further information, contact Sandra Poppenga, USGS EROS, spoppenga@usgs.gov.

Figure 58. GMTED2010 Spatially Referenced Metadata.
Science and Applications Activities 43

Figure 59. The U.S. Geological Survey developed selective drainage methods to extract 

hydrologic information from high-resolution, high-vertical accuracy light detection and 

ranging (lidar) digital elevation models in Minnehaha County, South Dakota.

Figure 60. Cover of U.S. Geological Survey Scientific 

Investigations Report 2010–5059 “Using Selective Drainage 

Methods to Extract Continuous Surface Flow From 1-Meter 

Lidar-Derived Digital Elevation Data.” The selective drainage 

methods that the U.S. Geological Survey tested and developed 

for Minnehaha County, South Dakota, are published in this 

Scientific Investigations Report.
44 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Geographic Information System Tools for Estimating Post-Wildfire Debris Flow Inundation

Terrain and land surface conditions after wildfire events can create ideal conditions for rainfall-induced debris flow events 

that endanger lives and property. The USGS has ongoing research in southern California to understand the probability and 

magnitude of debris flow events; however, no tools were available for mapping the inundation extent of debris flow estimates. 

To address this shortcoming, LAHARZ, a menu-driven software function that runs within a Geographic Information System 

(GIS) that is used for estimating inundation from volcanic lahars, or debris flow, has been modified for use in post-wildfire areas. 

Digital Elevation Model (DEM) data available from the USGS Topographic Science Project and from local partners are necessary to operate the tool.

The debris flow inundation tool provides an important mapping capability needed to visually communicate the model results to municipal and emergency response planners (fig. 61). The tool is also valuable to researchers because it allows examination of the spatial extent of modeling results and makes comparisons with historical debris flow inundations needed to revise and 

improve the models. For further information, contact Vivian Queija, USGS EROS, vqueija@usgs.gov.

National Atlas Million Scale Mapping

The National Atlas of the United States has a goal to develop 1:1,000,000-scale cartographic frameworks for use in new 

National Atlas products and to submit as the U.S. contribution to Global Map, an international effort to develop seamless million 

scale datasets. In FY 2010, the top priority for National Atlas work at EROS was the review and edit of 1:1,000,000-scale waterbodies data that were developed by staff at the USGS Texas Water Science Center. By July 1, 2010, the task was completed for 

the western half of the conterminous United States, or about 7,950 waterbodies (fig. 62). For further information, contact John 

Hutchinson, USGS EROS, hutch@usgs.gov.

Figure 61. This aerial view is an example of an inundation 

zone for 10,000-cubic-meter debris flow volume produced 

using the LAHARZ tool. Zones like these are typically 

compiled as a series to show a range of magnitudes for 

conveying risk to decision makers. 
Science and Applications Activities 45

The National Elevation Dataset: Lidar for Science

The National Elevation Dataset (NED) is a science-ready multiresolution elevation dataset that serves as the elevation layer 

of The National Map. The resolution of NED data has improved as production methods have evolved and new technologies 

have been developed. In FY 2010, lidar has been the main data source and is the source for an additional 111,200 square miles 

of high-quality and high-resolution bare-earth elevation data. This brings the total area of the NED 1/9-arc-second collection to 

338,153 square miles. Lidar datasets are collected from a variety of providers, including Federal, State, local governments and 

the private sector. The lidar data are received and assessed for quality and merged into a common projection, datum, and vertical 

units. Lidar data provide basic elevation information for earth science studies and mapping applications in the United States (fig. 

63). Scientists and resource managers use lidar-derived NED data for global change research, hydrologic modeling, resource 

monitoring, mapping and visualization, and many other applications. 

The American Recovery and Reinvestment Act (ARRA) Stimulus funds, in addition to Survey Investigation and Research 

(SIR) funds, have enabled data collection via multiple funding mechanisms, larger area acquisitions, interdisciplinary partnerships, and newer and better data. Both ARRA and SIR funds have been awarded to acquire elevation, lidar in particular, 

emphasizing those areas that support USGS Science Strategy and DOI program activities (such as coastal watersheds, USGS 

Multi-Hazards Program, and DOI Healthy Lands) and other priority areas around the Nation. The resulting data will improve 

the resolution, quality, consistency, and coverage of existing data assets. The funded acquisitions will add to the 1/9-arc-second 

elevation data coverage in the NED, and, in turn, revise and improve the 1/3- and 1-arc-second elevation layer of the NED.

Although lidar is a priority, there is also work being done to improve areas which only have 30-meter source data. The standard 10-meter Digital Elevation Models (DEMs) are being developed through cartographic contours and mapped hydrography. 

By the end of calendar year 2011, the source data of the conterminous NED multiresolution layers are projected to be of 10-meter or better resolution. This activity supports contour generation and hydrographic integration. An additional 250,732 square 

miles were added to the NED 1- and 1/3-arc-second layers in FY 2010 either by migration of the NED 1/9-arc-second source or 

standard 10-meter DEM production. 

The U.S. Geological Survey (USGS)-National Geospatial Program (NGP) Lidar Guidelines and Base Specification has 

been written and extensively reviewed in an effort to assist the elevation community in establishing a consistent and reliable 

lidar source dataset. Topics addressed in this document include collection criteria, data processing and data handling, and deliverables. This specification is also being used as the basis for the Federal Emergency Management Agency and Natural Resources 

Conservation Service’s new Guidelines, as well as the American Society for Photogrammetry and Remote Sensing Best Practices for the lidar profession. Final editing and formal USGS publication is expected in FY 2011. 

Several lidar workshops, presentations, and panel discussions were led during FY 2010 in support of the lidar specification, 

lidar processing, and status of lidar datasets destined for the NED collection. EROS also hosted the Elevation Business Process 

Reengineering meeting last February and continues to respond to the resulting action items. The NED team is always looking for 

new and better ways to provide the nation with the best available science-ready digital elevation data. For further information, 

contact Gayla Evans, USGS EROS, gevans@usgs.gov.

Figure 62. The image shows mapping that has been 

completed for the western half of the conterminous United 

States, or about 7,950 waterbodies.
46 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

CLICK Passes a One-Trillion Milestone

The USGS Center for Lidar Information Coordination and Knowledge (CLICK) passed the trillion lidar point mark in FY

2010 by housing approximately 1.1-trillion lidar points across the United States—that is more than 1,100,000,000,000 threedimensional georeferenced coordinate records that describe parts of the United States in 3-D. Trees, buildings, volcanoes, fault 

lines, bridges, power lines, bare earth are among the features represented by a 3-D point cloud in CLICK (fig. 64). Currently, 

CLICK is providing more than 25 terabytes of 3-D data from lidar for approximately 7 percent of the United States. Also, since 

its inception in 2006, the CLICK bulletin board, which provides lidar information to users across the world, has been viewed 

more than 2.7 million times and has 1,400 registered members. For further information, contact Jason Stoker, USGS EROS, 

jstoker@usgs.gov.

Figure 63. Fiscal year 2011 holds great promise for the amount of available high-resolution lidar data 

to be added to the National Elevation Dataset collection. 

Figure 64. The image depicts 

approximately 20,000 lidar points in 

downtown Sioux Falls, South Dakota. 
Science and Applications Activities 47

Lidar Research Highlighted in Prestigious Industry Journal

Light detection and ranging (lidar) research at EROS was highlighted in an article and on the cover of the journal Photogrammetric Engineering and Remote Sensing (PE&RS) in FY 2010. Jason Stoker, author of the paper, has developed a new 

and novel approach to processing, representing, and modeling lidar data. The March 2010 journal article, “Making Lidar More 

Photogenic: Creating Band Combinations from Lidar Information,” documented a new technique that could have very strong 

implications on how lidar is used, manipulated, and fused with other data for classification, analysis, and modeling. 

The methodology demonstrates how to use lidar point cloud information and develop a multiband image stack similar to 

Landsat bands. By creating bands from information such as slope, elevation, laser intensity, and other lidar properties inherent in 

the data, users can now visualize and classify lidar data using the same software, algorithms, and methodology used for passive 

optical data. Users can directly fuse spectral information from instruments such as Landsat with lidar-derived information into a 

single file, which provides the opportunity to perform classifications and models on imagery with aided by the vertical dimension provided by lidar. The significant findings from this research have been recognized by Lidar News: http://www.lidarnews.

com. 

The February 2010 PE&RS cover (fig. 65) featured a lidar dataset of Mount Rainier, Washington, thus continuing attention 

on EROS lidar activities first shown by the September 2008 PE&RS cover of downtown Sioux Falls, South Dakota. For further 

information, contact Jason Stoker, USGS EROS, jstoker@usgs.gov.

Figure 65. Lidar featured on PE&RS covers depicting Mount Rainier, Washington, (left) and Falls Park in 

Sioux Falls, South Dakota (right).
48 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Early Warning, Environmental Monitoring, and Hazards Management

The Early Warning, Environmental Monitoring, and Hazards Mitigation Team conducts research on and implements new 

approaches for monitoring environmental hazards and mitigating their impact through creative applications of geographic analysis and modeling of Earth processes. Key accomplishments are given in the following sections.

Global Environmental Alert Service

The United Nation Environmental Program’s (UNEP) Global Environmental Alert Service (GEAS) continuously scans the 

scientific literature and analyzes results of earth observations and other data sources to produce widely distributed alerts, focusing on policy relevant Environmental Hotspots, Environmental Science, and Near Real-Time Environmental Event Alerts in an 

easily understandable format. GEAS monitors the planet and enhances UNEP’s ability to provide regular, science-based updates 

to its member states and the international community on the status and trends of the global environment.

The staff at UNEP Global Resource Information Database (GRID) - Sioux Falls produced 5 environmental Hotspot Alerts, 

5 Environmental Science Alerts, and 4 Near-Real Time Environmental Event Alerts, which included the most current issues 

such as the Deepwater Horizon oil spill, wildland fires in Russia, and Pakistan flooding. At the same time, the GEAS website 

(http://www.na.unep.net/geas) was redesigned with state-of-the-art technologies engaging the popular social tools to provide this 

invaluable information in the most interesting way (fig. 66). For further information, contact Charles Trautwein, USGS EROS, 

trautwein@usgs.gov.

Africa Water Atlas

At the request of the African Ministers’ Council on Water, the team at UNEP GRID Sioux Falls published the Africa Water 

Atlas in late 2010.

The Africa Water Atlas provides decision makers, interested readers, and others who care about the future of the continent 

with invaluable information concerning the state of water resources through illustration with more than 100 satellite images, 225 

maps, 500 graphics, 250 ground photographs, and a brief profile of the water situation in every country (fig. 67). In addition, 

the Atlas provides reason for optimism about addressing water issues – although the population is challenged by the presence 

of “hot” spots where rain-fed agriculture is constrained and food security is tenuous. The Atlas highlights Africa’s many “hope” 

spots where long-practiced water-harvesting coping strategies can be expanded and new practices adopted, especially in light of 

the changing climate. The Atlas vividly illustrates the importance of Africa’s water towers in supplying millions of people with 

Figure 66. Screenshot of the Global 

Environmental Alert Service website (http://www.

na.unep.net/geas).
Science and Applications Activities 49

life-giving water and in supporting activities that are crucial to our ecosystems and economies.

This Atlas balances the many challenges Africa faces in dealing with water problems by stressing the opportunities to 

improve the quantity, quality, and use of water resources. One example is the huge opportunity to develop untapped water 

resources for electricity, irrigation, industry, and tourism. There are also opportunities to support exciting innovations, such as 

revolutionizing toilets to conserve water, investing in small-scale hydropower projects and fostering the greening of the Sahel. 

For further information, contact Charles Trautwein, USGS EROS, trautwein@usgs.gov.

Radar Applications Development

Supported by the USGS Land Remote Sensing Program, this project focuses on the development of state-of-the-art synthetic aperture radar (SAR), interferometric SAR (InSAR) technologies and the transfer of satellite radar remote sensing into 

bureau-wide applications. Project members actively collaborate with USGS scientists on monitoring natural and man-made 

hazards, and imaging landscape characteristics with all-weather radar and InSAR imagery. Project activities provide fundamental research and technologies on mapping and monitoring the Nation’s 

ecosystem function, water availability, natural hazards, and climate changes 

of USGS science in the coming decade. Project scientists have authored 

and co-authored several manuscripts on volcano deformation monitoring, 

wetland and flood mapping, InSAR technique development, radar remote 

sensing of natural hazards, and land subsidence mapping (fig. 68). Staff 

members have developed and refined a website for the Center for Radar 

Information Coordination and Knowledge et al (CRICKet)—a USGS 

Center for SAR technology that seeks to expand the application and use of 

satellite radar technology by scientists and managers within the USGS and 

other DOI agencies. Project scientists have given support and guidance to 

scientists from USGS and other Federal agencies on exploring SAR and 

InSAR technologies, and provided support to the LRS Program on radar 

related activities. For further information, contact Zhong Lu, USGS EROS,

lu@usgs.gov.

Figure 67. Cover of the Africa Water Atlas.

Figure 68. InSAR image of Dec 6, 2006–June 8, 2007, showing land surface 

subsidence because of mining activity over Utah. 
50 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Mapping Irrigated Agriculture across the Country

Accurate, detailed, and timely geospatial information on the extent of irrigated lands improves understanding of national 

agricultural water use, local land surface processes, conservation or depletion of water resources, and climate conditions. It is an 

important component for modeling the hydrologic budget. A new method for mapping in a geospatial modeling framework assimilates three data sources to produce a national map of irrigated agriculture at a 250-meter resolution across the entire conterminous United States. 

The geospatial model, referred to as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture 

Dataset (MIrAD-US), ingests federal irrigation statistics from the U.S. Department of Agriculture (USDA), a satellite-based 

variable describing peak vegetation vigor, and agricultural land cover from the 2001 National Land Cover Database to identify 

the location of irrigated agriculture. The model was run for 2002 (fig. 69) and 2007, corresponding to the USDA’s Census of Agriculture publication years. Consistent field data to ground reference irrigation are not readily available across the whole country. 

Two existing data sources were used to assess MIrAD-US accuracy: field-level land use surveyed by the California Department 

of Water Resources and Great Plains field points collected for irrigated and nonirrigated fields by the University of North Dakota 

in 2006. Model results for 2002 MIrAD-US identified irrigated lands with reasonable accuracy in California and Great Plains 

states with overall accuracies of 92 percent and 75 percent and kappa statistics of 0.75 and 0.51, respectively. The lower statistics for the Great Plains may be a result of the temporal mismatch of the field dataset. 

The MIrAD-US modeling approach enables consistent wall-to-wall mapping and regular updates for irrigated lands and 

should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. For further information, contact Jesslyn Brown, USGS EROS, jfbrown@usgs.gov.

U.S. Evapotranspiration Project 

The Evapotranspiration (ET) Project at USGS EROS covers diverse geographic areas around the world. The USGS EROS 

developed the Simplified Surface Energy Balance (SSEB) model to estimate landscape ET for various applications. Since ET 

is a critical component of the hydrologic cycle and the most difficult to measure, remote-sensing-based techniques such as the 

SSEB have become very important. For early warning applications, ET provides crop performance and drought monitoring information. For hydrological applications, ET is used to estimate groundwater recharge and withdrawal rates. Water management 

Figure 69. The 2002 irrigated agriculture results from the MIrAD-US model. The six inset boxes 

show MIrAD-US model results next to 2002 mid-summer Landsat scenes.
Science and Applications Activities 51

personnel use ET information for estimating irrigation water requirements and use.

 The SSEB ET model was run using a combination of MODIS datasets (thermal, NDVI, and albedo) and weather datasets 

such as radiation, air temperature, wind speed, relative humidity, and air pressure for the continental United States, the Euphrates 

and Tigris region in Iraq, and northeast Africa. The model produced 1-kilometer resolution ET on 8-day, monthly, seasonal, and 

annual time scales for the various study regions from March 2000 to December 2009. The annual ET total distribution for 2009 

at the three study sites is shown in figure 70.

The U.S. ET Project was funded by the USGS Groundwater Resources Program in collaboration with various water science 

centers such as the California, Nevada, New Mexico, Oregon, and Washington Water Science Centers. The Northeast Africa ET 

Project was funded by the Famine Early Warning System Network (FEWS NET) of the U.S. Agency for International Development. The Department of Defense funded the Iraq ET Project. For further information, contact Gabriel Senay, senay@usgs.gov. 

eMODIS Normalized Difference Vegetation Index for Food Security Monitoring

Famine Early Warning Systems Network (FEWS NET) uses a variety of remotely sensed data products and modeled 

outputs to support food aid decision making. One of the products that FEWS NET has utilized throughout its 25-year history is 

the Normalized Difference Vegetation Index (NDVI), used primarily for monitoring vegetation conditions. NDVI data from the 

Advanced Very High Resolution Radiometer (AVHRR) sensor have provided a long time series for monitoring cropland and 

pasture conditions, initially supporting FEWS NET efforts in Africa. In recent years, monitoring efforts have expanded to include Haiti, Central America, and Afghanistan and are now becoming more global. As the number of areas monitored continues 

to grow, so does the need for obtaining new and improved datasets.

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor flown on the Terra satellite provides a good source 

of NDVI data at higher spatial resolution and greater geometric accuracy than AVHRR. USGS EROS began using these data as 

an alternative NDVI data source in 2002. The data have proven to be invaluable for a number of applications, including support 

to crop and food supply assessment missions in multiple countries, maize production estimation in Zimbabwe, drought monitoring in Afghanistan, and pastoral/agro-pastoral analysis in Niger. 

The standard MODIS NDVI data, however, have limited capabilities when it comes to the type of operational monitoring that is required by FEWS NET. The 16-day composite period is lengthy for early warning applications, variable degrees of 

product latency hamper efforts for quick response, and the numerous reprocessing iterations have limited the ability to collect a 

consistently processed time series. For these reasons, USGS EROS has pursued an alternative MODIS-based NDVI resource.

The eMODIS (expedited MODIS) capabilities developed by the Land Processes Distributed Active Archive Center (LP 

DAAC) at EROS in 2007 provided a viable option. The system relies on direct access to daily swath surface reflectance data 

from MODIS for calculating NDVI. The eMODIS production system provides the ability to customize compositing and to proFigure 70. Annual evapotranspiration for three study 

regions showing spatial distribution of vegetation 

water use across different landscapes in the United 

States, northeast Africa, Iraq, and surrounding 

regions. Green indicates high water use in high 

rainfall and irrigated regions. Brown indicates low 

water use in arid and semiarid regions.
52 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

vide timely data delivery (24 hours expedited; 3–5 days nonexpedited), minimized re-sampling, user-friendly file formats, and 

improved spatial resolution (fig. 71).

In FY 2010, FEWS NET initiated the near-real time production of 250-meter eMODIS NDVI data for Central America, 

the Caribbean (including Haiti), and Africa. The Central America/Caribbean dataset is complete throughout the Terra MODIS 

history and is being used in an operational manner for monitoring these areas. The Africa eMODIS data are operational in the 

near-real time production mode (fig. 72) but were historically incomplete at the end of FY 2010. FEWS NET will begin to use 

these data operationally as soon as comparison with a historical dataset is done fiscal year 2011. For further information, contact 

James Verdin, USGS EROS, verdin@usgs.gov.

Figure 71. An example of 

the improvement in spatial 

resolution with the expedited 

MODIS (eMODIS) Normalized 

Difference Vegetation Index 

(NDVI) (upper right) compared 

to coarse resolution Advanced 

Very High Resolution Radiometer 

data (lower right). The Haiti land 

cover map (left) shows an area 

of dense agriculture along the 

west central coast that, when 

compared to the NDVI maps, 

illustrates the benefits that 

eMODIS quality and resolution 

will provide for improved 

agricultural monitoring in current 

Famine Early Warning Systems 

Network countries and other 

remote monitoring locales.

Figure 72. A 10-day eMODIS Normalized Difference 

Vegetation Index composite of Africa at 250-meter 

resolution.
Science and Applications Activities 53

The USGS FEWS NET Informing Climate Adaptation Series

Whether related to natural internal variations of the climate system or anthropogenic changes related to greenhouse gas 

emissions, low frequency climate trends can have serious impacts on food insecure nations. To support the information needs of 

food security and development specialists, the USGS and FEWS NET have created a new “Informing Climate Change Adaptation” series of reports. These brief reports have a standard format, comprised of the following elements: (1) a callout box listing 

key climate trends, impacts, and affected populations, (2) a climate “hotspots” map showing observed and projected changes in 

key rainfall and contour lines, (3) a plot of observed and potential rainfall and/or temperature changes between the 1960–1989 

and 2010–2039 time periods, (4) a qualitative evaluation of the likelihood that the observed trend may continue, and (5) a discussion of affected populations and agricultural production centers. If relevant, additional analyses may also be presented. An 

example of these reports for Kenya is available online as a USGS Fact Sheet (Funk and others, 2010). 

The first “hotspot” graphic combines long-term climate mean fields and gridded trend fields in a unique way (fig. 73). First, 

visualization of the data and knowledge of crop requirements for the region are used to identify meaningful rainfall thresholds. 

For example, a 500-millimeter-per-season rainfall threshold typically provides a reasonable delineation between productive and 

marginal cropping areas. Almost all cultivated areas in eastern Africa and the Sahel receive, on average, more than this amount 

of rainfall during the main growing season. The 30°C temperature contour line tends to play a similar role, delineating hot-dry 

regions and cool-wet seasons during the main crop growing periods. The 1960–1989 mean fields may be used to derive 1960–

1989 contour lines. By combining the mean and trend fields, observed contours for the 1980–2009 time period may be produced. 

Assuming stationarity of the trend through the 2010–2039 era allows for a third contour to be created. 

In research (2003–2010) looking into African rainfall trends (table 2), results suggest that the drying in parts of eastern 

Africa, Kenya, and Sudan is related to a ~1°C warming in the Indian Ocean. This warming is consistent and persistent through 

the 1950–present era, correlates strongly with global air temperature through the 1900–2009 era, and shows up as a pronounced 

“hockey stick” in related proxy data (coral and station air temperature data). It is also uniformly reproduced by all the IPCC 

climate models and many additional datasets (Williams and Funk, 2010). Indian Ocean sea surface temperatures and Kenyan, 

Ethiopian, and Sudanese rainfall and temperature trends exhibit considerable levels of persistence on decadal timescales. Thus, 

even in the absence of greenhouse gas forcings, momentum in the climate system seems likely to cause persistence of these 

trends for at least the next 10–15 years. 

The second figure of the FEWS NET climate adaptation report combines 1960–2009 observations with an assumption of 

trend persistence to produce a composite climate shock assessment (fig. 74): the best estimated change in rainfall or air temperature between 1975 and 2025. Note that the bulk (70 percent) of this change assessment relies upon observations (35 years 

spanning the 1975–2009 era), and the 15 years until 2025 are projected using the observed trend.

For Kenya, the food security implications of this change can be visualized in rainfall patterns by plotting the 500-millimeter rainfall contour lines for the observed 1960–1989, observed 1980–2009, and projected 2010–2039 contour lines, overlain 

on major food surplus areas for long rains maize production (fig. 73). The 500-millimeter lines are significant, as they represent 

areas which, on average, receive enough long-season rainfall to support cropping. Throughout the 1960–1989 period, mean 

rainfall extended well to the east and north of the central highlands but now is much closer, contracting by about 15 kilometers 

per decade. This recession has already impacted the densely populated areas to the south, east, north, and northeast of Nairobi 

(Funk and Verdin, 2009). Some of these districts are major food surplus areas for long rains maize production. The 1975 to 2025 

warming will generally represent more than a 1°C increase in temperature for Kenya, a substantial change in the country’s underlying climate. This 1°C warming value can be compared to the typical interannual standard deviation of March through June 

station temperatures, about 0.6°C; the long-term warming signal is therefore substantially more than half a standard deviation. 

This warming has likely exacerbated the impact of the observed drying tendencies, which coincide with densely populated, food 

insecurity, and agriculturally important areas of the central highlands.

The resulting USGS FEWS NET Climate Change reports are being used to inform climate adaptation. For example, recent 

discussions at the USAID mission in Nairobi helped differentiate areas of increasing climate vulnerability and areas of stable 

climatic resilience. This information can help guide agricultural development along sustainable and productive pathways. USGS 

Fact Sheets for Ethiopia and Sudan are under final preparation, and FY 2011 activities should produce special reports targeting 

temperature ET impacts, links between crop phenology and warming temperatures, recent drying trends in India, and the interaction between land cover and climate change in Ethiopia. For further information, contact Chris Funk, USGS EROS, cfunk@

usgs.gov.
54 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Past research and relevant reports

Funk, C., Michaelsen, J., Verdin, J., Artan, G., Husak, G., Senay, G., Gadain, H., and Magadzire, T., 2003, The Collaborative 

Historical African Rainfall Model—Description and Evaluation: International Journal of Climatology, v. 23, p. 47–66. (Also 

available online at ftp://chg.geog.ucsb.edu/pub/pubs/CHARM_IJOC_article.pdf).

Funk, C., and Michaelsen, J., 2004, A simplified diagnostic model of orographic rainfall for enhancing satellite-based rainfall 

estimates in data poor regions: Journal of Applied Meteorology, v. 43, p. 1366–1378. (Also available online at ftp://chg.geog.

ucsb.edu/pub/pubs/VDELB.pdf).

Funk, C., Asfaw, A., Steffen, P., Senay, G., Rowland, J., and Verdin, J., 2003, Estimating Meher Crop Production Using Rainfall 

in the ‘Long Cycle’ Region of Ethiopia: FEWS NET Special Report available online at http://earlywarning.usgs.gov/adds/

pubs/EthProductionOutlook.pdf.

Funk, C., Senay, G., Asfaw, A., Verdin, J., Rowland, J., Michaelsen, J., Eilerts, G., Korecha, D., and Choularton, R., 2005, 

Recent Drought Tendencies in Ethiopia and equatorial-subtropical eastern Africa: FEWS NET Special Report available online 

at http://earlywarning.usgs.gov/adds/pubs/RecentDroughtTendenciesInEthiopia.pdf.

Verdin J., Funk C., Senay, G., and Choularton, R., 2005, Climate Science and Famine Early Warning: Philosophical Transactions of the Royal Society B, v. 360, p. 2,155–2,168. (Also available online at ftp://chg.geog.ucsb.edu/pub/pubs/RoyalSociety_2005.pdf).

Figure 73. Suitable crop growing areas shrink in central Kenya. The backdrop 

image (light green) shows key crop surplus and crop deficit areas. The three 

overlain polygons show areas typically receiving enough rain to support a healthy 

crop (areas receiving, on average, more than 500 millimeters of rainfall) during 

1960–1989 (tan), 1990–2009 (brown), and 2010–2039 (orange).

Figure 74. Observed and projected change in rainfall and temperature (left), together with smoothed central Kenyan rainfall and a 

smoothed version of the Indian-Pacific-Area climate index (right).
Science and Applications Activities 55

Funk, C., and Brown, M., 2005, A maximum-to-minimum technique for making projections of NDVI in semi-arid Africa for 

food security early warning: Remote Sensing of Environment, v. 101, p. 249–256. (Also available online at http://earlywarning.usgs.gov/adds/pubs/ndvi_projections.pdf).

Funk C., Dettinger M., Michaelsen J.C., Verdin J.P., Brown M.E., Barlow M., and Hoell A., 2008, Warming of the Indian Ocean 

threatens eastern and southern African food security but could be mitigated by agricultural development: Proceedings of the 

National Academy, v. 105, p. 11,081–11,086. (Also available online at http://earlywarning.usgs.gov/adds/pubs/WarmingInTheIndianOceanThreatensEasternAndSouthernAfrica.pdf).

Brown, M.E., and Funk, C., 2008, Food Security under Climate Change: Science, v. 319, p. 580–581. (Also available online at 

http://earlywarning.usgs.gov/adds/pubs/PerspectivesPiece_and_Letter.pdf).

Funk, C., and Brown M., 2009, Declining Global Per Capita Agricultural Capacity Production and Warming Oceans Threaten 

Food Security: Food Security, v. 1, no. 3, p. 271–289, DOI: 10.1007/s12571-009-0026-y. (Also available online at ftp://chg.

geog.ucsb.edu/pub/pubs/FoodSecurity_2009.pdf).

Funk C., and Verdin, J., 2009, Real-time decision support systems—the Famine Early Warning System Network, chap. 17 in 

Gebremichael, M. and Hossain, F., eds., Satellite rainfall applications for surface hydrology: New York, Springer, p. 295–320. 

(Also available online at ftp://chg.geog.ucsb.edu/pub/pubs/RealtimeDSS_for_FEWS_NET_wfigs_v5.pdf).

Jury M., and Funk C., 2010, Climate change over Ethiopia—local signals and regional drivers: International Journal of Climatology (under review).

Crop Area Estimation for Haiti with Very High Resolution Satellite Imagery

Food security assessment in developing countries is a multidisciplinary activity that must take into account a wide range of 

socioeconomic and agro-climatic variables. The Famine Early Warning Systems Network (FEWS NET) performs this service 

for the Office of Food for Peace (FFP) of the U.S. Agency for International Development, which provides $2–3 billion in food 

aid worldwide each year. The goal of FFP is “to ensure that appropriate... emergency food aid is provided to the right people in 

the right places at the right time and in the right way.” USGS EROS has been a FEWS NET implementing partner since 1985, 

applying its expertise in remote sensing to support food aid decision making at FFP.

A key variable in food security assessment is the amount of food produced within a country, which is compared with the 

population’s food requirement. Estimation of national crop production requires, in turn, knowledge of the crop area harvested in 

the country. Unfortunately, in some countries the available data on crop area are ambiguous at best because of weak data collection methods, lack of timeliness, or inconsistent figures from more than one government agency. In the face of this uncertainty 

for a key variable needed in the design of food aid programs, FFP asked USGS EROS to develop objective and repeatable methods for estimating crop area from satellite imagery.

In partnership with the Geography Department at the University of California, Santa Barbara, an approach has been developed that combines interpretation of very high resolution commercial satellite imagery and area-frame sampling statistical methods. It has been applied in several priority countries for the last few years, including Ethiopia, Zimbabwe, Niger, Afghanistan, 

and Guatemala. In FY 2010, the method was applied in Haiti, a country whose chronic food insecurity was seriously exacerbated 

by the devastating earthquake of January 12, 2010.

With the assistance of the National Geospatial-intelligence Agency (NGA), imagery from OrbView and WorldView, with 

resolution of 1 meter or better, was acquired between August and November 2009 for Haiti. Coverage of 30 percent of the 

national territory was achieved. A 0.5-kilometer dot grid was defined to create a systematic sample of 32,225 points for interpretation of the presence or absence of a crop at each of these locations (fig. 75). These image interpretations were supplemented 

by other datasets having full national coverage: gridded mean seasonal rainfall, general land cover types, slope, erosion risk, and 

demographic variables at the commune level. Using the dot grid interpretations of the very high resolution imagery, a logistic 

regression statistical model was trained to estimate percent crop area nationwide based on the values of the nationally continuous datasets. 

Results for Haiti as a whole, as well as its 10 Departments, were calculated using the statistical estimator. They are presented in table 2. These figures were used by FEWS NET and the United Nations to design a Crop and Food Supply Assessment 

Mission for Haiti in July 2010. They cited the lack of any other up-to-date and authoritative figures. Thus, remote sensing was 

able to fill a critical information gap needed to assess the food security of Haiti and design appropriate international food aid 

programs. For further information, contact James Verdin, verdin@usgs.gov.
56 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Remote Sensing Activities

The USGS EROS Center’s remote sensing activities are framed around excellence in science, data management, infrastructure, and facilities devoted to evaluation and assessment of land changes and their impact on society. Core to the EROS mission is the continuity of remote sensing of the Earth’s land surfaces at all scales to ensure availability of historical and current 

observations. Although EROS is well known as the USGS receiving station for Landsat satellite images, data from many other 

satellites and other remote sensing platforms are also archived and distributed by EROS. Receiving, calibrating and validating, 

Figure 75. WorldView panchromatic image of Central Haiti, L’Artibonite Department 

from November 23, 2009. This image captures agricultural areas (green points) and 

nonagricultural areas (orange points) as interpreted by expert image analysts in the 

region.

Table 2. Cropped area estimates for all of Haiti and broken down by Department. Area 

estimates are in thousands of hectares.

Coverage by 

imagery

(percent)

Total area

Cropped 

area 

estimate

Standard 

error

Cropped area 

(percent)

Haiti 30% 2,688.30 549.9 27.5 21%

Department

Centre 47% 324.2 59.4 5.9 18%

Grand’Anse 3% 187.7 36.2 4 19%

L’Artibonite 47% 441.1 81.7 6.5 19%

Nippes 1% 126.7 25.7 3.3 20%

Nord 18% 197.4 60.9 6.1 31%

Nord-Est 25% 158.4 55.1 5.5 35%

Nord-Ouest 32% 248.6 60.9 6.1 24%

Ouest 33% 509.4 63.9 5.1 13%

Sud 9% 287.6 72.6 5.8 25%

Sud-Est 29% 207.2 33.4 3.7 16%
Remote Sensing Activities 57

processing, archiving, and distributing these data are primary tasks performed at EROS. In addition, EROS is defining requirements and specifications for future instruments, developing and implementing ground systems for future Earth observing missions, and developing national and international partnerships. 

Landsat Program

The Landsat Program is a joint effort of the USGS and NASA to gather Earth resource data using a series of land observing satellites. Whereas NASA’s role is the development and launch of Earth observing instruments and spacecraft, the USGS 

is responsible for flight operations, maintenance, and management of all ground data reception, processing, archiving, product 

generation, and distribution for the Landsat series of Earth observation missions. A primary objective of the Landsat Program is 

to ensure a collection of consistently calibrated Earth imagery.

Today, the Landsat Project at EROS manages two active satellites, Landsat 5 and Landsat 7, and the historical archive of 

data collected since 1972—more than 2.4 million images. In FY 2009, a change in data policy (no charge, web-enabled data) 

transformed the distribution of Landsat data for scientists and operational users worldwide; as a result, more than 3 million 

Landsat images have been delivered to customers! As of FY 2010, Landsat 5 reached 26 years in orbit, and Landsat 7 reached 11 

years in orbit. With the respective design life of 3 years and 5 years, both of these satellites continue to provide essential data to 

scientists well beyond their expected lifespan. The Landsat team is continually working to extend the longevity of the satellites 

in orbit, enhance Landsat data quality, improve systems at EROS used to archive, process, and access Landsat data, and is leading the design and development of the ground system for the Landsat Data Continuity Mission. 

Survey of Landsat Users Demonstrates Value of Landsat Data

To better understand the users, uses, and societal benefits of Landsat imagery, USGS conducted a survey of approximately 

1,400 U.S.-based professional users of this imagery in the fall of 2009. This surveying effort sought to answer the following 

questions:

How is Landsat imagery used?

• At multiple scales, from local to global, in locations around the world.

• In a variety of sectors, from academic institutions to all levels of government, as well as private businesses and nonprofit 

organizations. 

• In many applications areas including ecological monitoring, emergency/disaster relief, agricultural management, rural 

and urban planning and development, climate science, and water resource management.

How important is Landsat imagery?

• More than 80 percent of respondents find Landsat important to their current work.

• More than 80 percent will increase or maintain their use of Landsat in the next 5 years. 

• 40 percent rely exclusively on Landsat for their work.

Does the imagery meet the needs of users?

• Key features of Landsat are important to respondents when they choose which kind of imagery to use for their work. 

• Respondents are satisfied with these features of Landsat.

What are the impacts if Landsat imagery were no longer available? 

• Negative impacts to respondents include:

• More than 50 percent would discontinue some to all of their work.

• 65 percent would likely incur increased overall project costs.

• 33 percent would experience a decrease in revenues or funding.

What are the effects of Landsat imagery becoming available at no charge?

• Respondents acquired twice as many Landsat scenes from 2008 to 2009.

• Respondents spent 80 percent less on Landsat imagery from 2008 to 2009.
58 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Some of the preliminary information from the survey indicates that Landsat data are very important and valuable to a broad 

user community (fig. 76). The USGS is compiling the complete results in an upcoming report.

The survey, funded by the Land Remote Sensing Program, was conducted by USGS Biological Resources Discipline, 

USGS Policy Analysis and Science Assistance Branch, Fort Collins, Colorado. For further information, contact Kristi Kline, 

USGS EROS, kkline@usgs.gov or Thomas Loveland, USGS EROS, loveland@usgs.gov.

Landsat Users Break Records—More than 2.4 Million Images Delivered

In FY 2009, Landsat users downloaded an astounding 1.1 million images from the EROS Center. That number pales in 

comparison to the downloads in FY 2010—More than 2.4 million! 

The USGS previously charged nominal fees for Landsat data, but in FY 2008 a policy change enabled Landsat data to be 

distributed at no charge via the Internet. Before the policy change, the highest year of distribution was in FY 2001 when approximately 25,000 scenes were delivered. Today, the Landsat Project can distribute in just a few days what once took an entire 

year (fig. 77). 

Providing free data has improved capability in the Earth observation research community. For instance, in perpetually 

cloudy areas, researchers struggled to find the best images at an affordable cost resulting in less than ideal data coverage of the 

study area. The images below highlight the impact of the free archive on science results. In figure 78, in the first image, scientists purchased the best available data (104 images for $83,200). In the second image, 3 to 5 images were added per path/row 

area to reduce cloud cover. However, that was once cost prohibitive (416 images for $332,800). It is clear in the third image 

that additional Landsat scenes can improve the forest cover mapping in a cloudy region. For further information, contact Kristi 

Kline, USGS EROS, kkline@usgs.gov.

Figure 76. Preliminary survey information shown by this scatter diagram indicates that Landsat 

data are very important and valuable to a broad user community. 
Remote Sensing Activities 59

Landsat Data Revival—Multispectral Scanner Data Improvements

Landsat 1, known initially as Earth Resources Technology Satellite 1 (ERTS-1), was launched on July 23, 1972. The first 

five Landsat missions included an instrument to collect multispectral data called the Multispectral Scanner (MSS). MSS data 

were collected from 1972 through 1992. The oldest data on the early Landsat satellites have undergone many changes since 

inception. From significant technological advances in computing capability to migration of the data from many media sources, 

the ability to process and utilize these data has dramatically changed. 

In FY 2010, the Landsat Project completed an effort to migrate processing of MSS data from a legacy system to a single 

system used for other instruments from later Landsats. As part 

of this recent change, the project upgraded the MSS capability. Included in this upgrade are significant improvements 

to data calibration, faster automated processing of data, and 

increased geometrical accuracy of most products. Each MSS 

image includes a JPEG (fig. 79) of geometric accuracy. Past 

processing of MSS images was slow and cumbersome, and 

image accuracy often constrained use of the products. For further information, contact Kristi Kline, USGS EROS, kkline@

usgs.gov. 

Figure 77. Increased data delivery into fiscal year 2010.

Figure 78. Landsat scenes (left to right) illustrate improved research capabilities with increased availability and use of free data 

(Hansen and others, 2008).

Figure 79. Example Multispectral Scanner image includes a 

JPEG of geometrical accuracy.
60 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Landsat Saves the Orphans

In addition to significant processing improvements for MSS data, the Landsat Project discovered old MSS data that were 

unable to be processed (fig. 80). In the early years of operations, data were collected on Wide Band Video Tape (WBVT) media 

with the necessary spacecraft telemetry metadata stored on 9-track computer tapes. As part of a data rescue effort, older collections stored by other Federal agencies were sent to EROS. However, unreadable or misplaced 9-track computer tapes resulted in 

“orphan” data. These data were once considered to be unable to be processed. The Landsat Project is implementing an innovative method to recover these images. The recovery systems have been built and tested, and rescue will commence in FY 2011. 

For further information, contact Kristi Kline, USGS EROS, kkline@usgs.gov.

Landsat Global Archive Consolidation—The World at EROS

The Landsat Global Archive Consolidation (LGAC) effort will bring more of the world to EROS. Pre-Landsat 7 missions 

did not have onboard data recorders like the one on Landsat 7. Instead, data were downlinked to ground stations around the 

world. These stations collected, archived, and distributed these data to customers. Initial estimates show that the global stations 

have nearly 5 million Landsat images in their archives. With approximately 2.4 million images in the U.S. archive today, bringing the world to EROS would triple the Landsat data holdings in the USGS archive. 

Although in some cases these data have been in foreign archives for decades, collecting the Landsat holdings in the U.S. 

archive is increasingly critical. Many stations have unique data, unique systems, and unique data formats. Scientists have long 

desired to have Landsat data in common formats with standard processing methods applied. Additionally, data in the archives of 

many stations are already at risk with aging media and are unable to be processed by the station that originally received the data. 

Data successfully recovered from global archives will 

be archived and made available to the science community. 

Landsat is a key dataset used to perform long-term studies 

for global change research. Stations collecting data in the 

early years with Landsats 1, 2, and 3 have nearly 250,000 

unique images in their archives (fig. 81). Approximately 

3.5 million additional unique Landsat images are housed in 

the archives of other non-U.S. stations. 

The Landsat project is currently working with international stations to compile the complete picture of Landsat 

data holdings globally. Sample data are being assessed to 

determine the technical requirements of consolidating all 

Landsat data at EROS. Many international stations are eager to work with the Landsat project, and arrangements are 

in work to begin collection of data. For further information, contact Kristi Kline, USGS EROS, kkline@usgs.gov.

Figure 80. Example of a recovered image (Landsat 

2, path 40, row 35, June 27, 1978) not previously 

archived at EROS, but processed using the updated 

MSS processing software.

Figure 81. Graphic of unique Landsat 1–3 image data held at 

international ground stations (IGS).
Remote Sensing Activities 61

New Missions

The USGS and the EROS Center are continually seeking opportunities to collaborate in the development and operations of 

Earth observing remote sensing missions to satisfy the needs of the Nation’s land imaging data requirements. The New Missions 

activities facilitate the communication and definition of USGS LRS Program requirements to the EROS Center. These activities are focused on developing partnerships to collect, archive, process, and distribute remotely sensed data in response to the 

evolving needs of scientific research, operational applications, decision makers, and educators. Toward these ends, teams are 

established to develop project plans, define and document requirements, perform systems engineering analysis, and implement 

technical solutions.

LDCM Ground Network Element Critical Design Review

The Landsat Data Continuity Mission (LDCM) Ground Network Element (GNE) is responsible for communicating telemetry and commands between the mission operations center (MOC) and the spacecraft, as well as receiving mission data which 

are subsequently sent to the Data Processing and Archive System (DPAS) for processing, archive, and distribution. The GNE 

is composed of LDCM ground network (LGN) stations located at Gilmore Creek, Alaska (“GLC,” in partnership with National 

Oceanic and Atmospheric Administration) and at USGS EROS in Sioux Falls, South Dakota (“LGS,” in partnership with the 

Landsat 5/7 program), and the Data Collection and Routing Subsystem (DCRS), which is a new development for LDCM. A 

diagram of the high-level Ground Network Element architecture is shown in figure 82.

The GNE critical design review was held on February 9, 2010, covering the final details of the design implementation of 

the GNE and the analysis showing predicted performance. Two minor requests for action (RFAs) and three advisories were 

received during the review. In preparation for the review, peer reviews were held for the LGN design and the DCRS development effort, which reviewed documentation to ensure that the element was at the maturity needed for the Critical Design Review 

(CDR). For further information, contact Grant Mah, USGS EROS, mah@usgs.gov.

Figure 82. Illustration of the equipment used in the June 2010 test (image courtesy of Orbital Sciences 

Corporation).
62 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

LDCM Ground Network Element (GNE) Testing with Spacecraft Engineering Model (EM) Hardware

During the weeks of February 8 and June 14, 2010, tests were conducted using the spacecraft engineering model (EM) 

communications and command and data handling (C&DH) subsystems to send data to ground system equipment. In the February test, a demod similar to the operational unit was tested to measure bit error rate (BER) and implementation loss performance, 

and in the June test, operational Ground Network Element (GNE) equipment (demod, downconverter, Data Collection and Routing Subsystem server, and network switch) were used. Both tests were highly successful, demonstrating that the end-to-end link 

performance will easily meet the 10e‐12 BER and 3 dB implementation loss requirements. Test data were consistent between 

both sets of testing and with tests run for GNE Level 4/5 testing at the USGS/EROS ground station. Moreover, the June test also 

demonstrated the capability of the ground system to receive and process the Consultative Committee on Space Data Systems 

(CCSDS) File Data Protocol (CFDP) data files that were generated and formatted by the EM C&DH. This demonstrated, with 

ample margin, that the system works end-to-end at the levels of performance needed for LDCM to deliver 400 scenes/day to 

the ground system for processing, archive, and distribution. These results have led to the recommendation to retire the LDCM 

system level risks for BER performance and CFDP compatibility between the spacecraft and the ground system. Image of the 

equipment used in the June test is shown in figure 83 (image courtesy of Orbital Sciences Corporation).

LDCM is the first operational flight mission to use Low Density Parity Check (LDPC) forward error correction (FEC), 

which is more spectrally efficient than the current convolutional coding FEC currently used by most missions. Moreover, the 

LDCM BER requirements are orders of magnitude higher than is typically required by a space mission (LDCM requires 10e-12 

BER, most space missions are typically specified in the range of 10e-6 to 10e-9), which is further compounded by the exceptionally high data rates used for LDCM (384 Mbits/sec). The successful end-to-end testing is a major accomplishment in both 

the overall LDCM development effort and in demonstrating new technology that operates at a substantially higher level of 

performance than anything that is currently flying or in development. For further information, contact Grant Mah, USGS EROS, 

mah@usgs.gov.

LDCM Collection Activity Planning Development Element

In January 2010, the Landsat Data Continuity Mission (LDCM) Development Team released the first version of the Collection Activity Planning Development Element (CAPE) that contains the ability to generate the high level instrument imaging 

mission schedules. The bulk of the imaging is done to satisfy the requirements established in the Long Term Acquisition Plan 

8 (LTAP-8) controlled by the LDCM Science Office. The policies governing data collection scheduling are implemented in the 

CAPE and provided to the Mission Operations Center to be transmitted to the orbiting satellite. For further information, contact 

Rodney Pater, USGS EROS, pater@usgs.gov.

Landsat Science Team Activities

The Landsat Science Team comprises 18 scientists from industry, academia, and government selected by the U.S. Geological Survey through an open competition to provide technical and scientific input to the USGS and NASA in support of Landsats 

1–7 and the Landsat Data Continuity Mission (LDCM). The Landsat Science Team is completing its fourth year out of a 5-year 

contract period, and the team has sustained a regular schedule of meetings every January and June since its inception in Fiscal 

Year 2007. 

In addition to the two meetings in FY 2010, the team held an additional meeting to address Landsat processing topics. The 

special meeting was hosted by Boston University in October 2009. During the meeting, the team reviewed state-of-the-science 

algorithms used to detect and map clouds and shadows, for atmospheric correction, and to calculate surface temperature and 

reflectance. The meeting concluded with plans to further test selected approaches for generating advanced Landsat science products that might be distributed by the USGS in the future.

Figure 83. Illustration of the equipment used in the June 2010 test (image courtesy of Orbital Sciences Corporation).
Remote Sensing Activities 63

The need for higher level science products was the theme for the January 2010 meeting held in Mountain View, California, 

and hosted by NASA Ames. The team concluded that producing a Landsat surface temperature and reflectance time series from 

1972 forward is a priority and the development of derived datasets based on Essential Climate Variable concepts should also be 

pursued.

The June 2010 meeting was hosted in Boise, Idaho by the University of Idaho and Idaho Department of Water Resources. 

The meeting included reviews of the status of Landsat 5 and 7, LDCM, and the recently completed Landsat user survey. In addition, each science team member gave a detailed presentation on their research and applications involving Landsat. The presentations highlighted the rapid advances resulting from the availability of web-enabled Landsat data (fig. 84). 

In addition to these meetings, during the past year the Landsat Science Team contributed to a USGS congressional briefing 

on Landsat and provided periodic evaluations of issues facing the USGS and NASA. For example, the team provided input on 

Landsat 5 acquisition options, methods for processing Landsat thermal imagery, and priorities for improving the USGS global 

Landsat archive. For further information, contact Thomas Loveland, USGS EROS, loveland@usgs.gov.

Data Processing and Archive System Critical Design Review

The Data Processing and Archive System (DPAS) is responsible for receiving Landsat Data Continuity Mission data from 

the Ground Network Element (GNE), archiving the data for safekeeping, calibrating the performance of the science instruments, 

and generating products for the user community (fig. 85). 

The DPAS engineering team presented its Critical Design Review (CDR) to a review panel of veteran USGS and NASA 

engineers on February 23–24, 2010. This review was the culmination of a year’s worth of difficult work that started with a 

ground-up re-architecture of the entire system in early 2009. The new architecture required the team to revisit its System Requirements Review in July 2009 and present a new Preliminary Design Review in September 2009. The DPAS CDR was a very 

successful review, resulting in only two formal Requests For Action throughout two full days of very detailed design material 

review. The panel characterized the review as fully successful, and the panel chairman noted in his report that the team “provided a comprehensive presentation of the entire final design” and “is to be commended on a well thought out design.” This review 

puts the DPAS team on very solid ground as it moves forward into implementation and testing. For further information, contact 

Chris Engebretson, USGS EROS, engebret@usgs.gov.

Figure 84. No-charge Landsat time series datasets contribute to natural resources management by providing an affordable 

means to detect threats to resources. The images show areas of forest change associated with western spruce budworm (yellow 

and red) at San Pedro Peaks, New Mexico and was produced by Landsat Science Team member Jim Vogelmann (USGS). The two 

images represent a 1998 Landsat 5 image (left) and a 1998 to 2008 land change map (right).
64 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Landsat Data Continuity Mission Ground System Critical Design Review

The Landsat Data Continuity Mission (LDCM) project completed critical design of the Ground System (fig. 86) this fiscal 

year, culminating in a Critical Design Review (CDR) in March 2010. The USGS, with mission partner NASA, presented the 

Ground System design to an independent review panel, receiving approval to proceed with implementation, integration, and 

test. The panel issued only three Requests for Action, which were addressed following the conclusion of the design review. For 

further information, contact Dave Hair, USGS EROS, hair@usgs.gov.

Figure 85. Browse image of a sample Level 1 user product.

Figure 86. High-level architectural diagram of the Landsat Data Continuity Mission Ground System.
Remote Sensing Activities 65

EROS LDCM Test Infrastructure

The EROS Landsat Data Continuity Mission (LDCM) is entering the early test phases. The infrastructure to support formal 

qualification testing of the Data Processing and Archive System (DPAS) has been acquired and installed. The infrastructure 

needed to support testing includes the operational test room, four racks of computer equipment, and network improvements 

(fig. 87). When completed, the DPAS will archive satellite image data and process it to a format suitable for scientific and civilian purposes. Future plans include procuring the LDCM production string of hardware at EROS and augmenting the capabilities 

at two other remote ground stations. For further information, contact Chris Torbert, USGS EROS, ctorbert@usgs.gov.

EROS LDCM Ground Readiness Tests

The EROS Landsat Data Continuity Mission (LDCM) is taking delivery of the first of many components needed for the 

completion of the ground system. The integration of those components is currently being performed at EROS and Goddard 

Space Flight Center, where Ground Readiness Testing (fig. 88) will occur. Ground Readiness Testing is a collaborative effort 

between USGS and NASA personnel to demonstrate that the ground system meets documented requirements. The tests will be 

conducted in phases and began in July 2010 when the commanding, reception of telemetry and imagery, and ground communication systems were evaluated. Future tests in 2011 and 2012 will include a capstone of nominal operational scenarios, contingency scenarios, and the calibration and processing of the LDCM imagery. For further information, contact Chris Torbert, USGS 

EROS, ctorbert@usgs.gov.

Figure 88. This is a graphical representation of the configuration needed for Ground Readiness Test 1, 

where the Mission Operation Center will generate commands that the EROS Ground Station will transmit to a 

spacecraft simulator. Simulated telemetry will be received and verified as valid responses by the flight operation 

team.

Figure 87. LDCM Data Processing and Archive 

System housed in a secure, climate controlled 

equipment room. Computer operators will test the 

system from the operations room adjacent to the 

computer room. 
66 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Calibration and Validation Technical Interchange Meetings

The Landsat Data Continuity Mission (LDCM) continues the long heritage of consistent, high-quality data collected 

with all the previous Landsat missions. The LDCM Calibration and Validation Team (CVT) ensures LDCM data are accurate 

and consistent throughout the life of the mission. The CVT consists of groups within the U.S. Geological Survey (USGS) at 

the EROS Center and NASA Goddard Space Flight Center (GSFC), as well as remote sensing groups at South Dakota State 

University (SDSU), University of Arizona (UA), and Rochester Institute of Technology (RIT). The CVT works closely with 

organizations across the country ranging from the instrument and spacecraft providers to the scientists relying on the imagery. 

Calibration and Validation Technical Interchange Meetings (TIM), held quarterly, provide the opportunity to discuss instrument 

and spacecraft development, ground system development, algorithm development, and calibration and validation methodologies, 

with the end goal of high-quality LDCM imagery in the hands of the science community.

The first calibration and validation TIM of 2010 occurred April 6–7, 2010, at NASA GSFC. John Schott from the Rochester 

Institute of Technology (RIT) was on hand to provide an overview of the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model, which is a software package used to simulate remotely sensed imagery. The Thermal Infrared Sensor 

(TIRS) team presented the development status of the sensor along with some initial analysis of their functional performance 

model (the precursor to the TIRS flight instrument). Additional analysis of TIRS dark data was presented by CVT members 

from GSFC. A lengthy discussion of the development status of the Operational Land Imager (OLI) was led by Jeff Pedelty of 

the Landsat Project Science Office (LPSO), who is stationed at Ball Aerospace and Technologies Corporation (BATC) (fig. 89). 

BATC presented their data acquisition plans for the OLI Engineering Development Unit (EDU) and OLI flight unit. Additional 

presentations and discussions revolved around the algorithm development and ground system development occurring at the 

USGS EROS Center.

The second calibration and validation TIM was held August 10–12, 2010. Updates from the second phase of the TIRS functional performance model testing and results of the OLI EDU thermal vacuum testing were among the topics of discussion. The 

second phase of the TIRS functional performance model testing is intended to prepare the test equipment and build the software 

needed to test the TIRS flight unit. Similarly, the OLI EDU thermal vacuum testing is intended as a dry-run of the test equipment 

and analysis software needed to test the OLI flight unit. While neither the OLI EDU nor the TIRS functional performance model 

are going to be operational, they are similar enough to the flight units that algorithms needed for requirements verification and 

image product generation can be built and tested. During the TIM in August 2010, substantial time was spent on the analysis of 

the OLI EDU and TIRS functional performance model test data that was collected and allow for collaboration between elements 

of the CVT. For further information, contact John Dwyer, USGS EROS, dwyer@usgs.gov.

Figure 89. The Operational Land Imager design concept by Ball Aerospace and Technology Corporation.
Remote Sensing Activities 67

Phase 2 Algorithms for Operational Land Imager and Thermal Infrared Sensor Delivered to 

Development

The Calibration and Validation Team’s (CVT) major accomplishment in 2010 was the delivery of all the phase 2 algorithms 

to the Data Processing and Archive Segment (DPAS) in the Landsat Data Continuity Mission (LDCM) project. The last of the 

phase 2 deliveries were delivered by the CVT to DPAS developers in May 2010. The phase 1 algorithm deliveries included only 

basic information, such as inputs, outputs, dependencies, and background. The DPAS developers used this information to define 

processing flows and interfaces for their preliminary design review. The phase 2 algorithms build upon the phase 1 content, 

adding the detailed algorithm procedures needed to support the DPAS critical design review (fig. 90). Phase 2 also enables the 

developers to begin implementing the algorithms shortly after critical design review. These deliveries are less mature than the 

phase 3 algorithms; however, they provide the development team with a good platform to build schedules and identify some 

of the problems that may come up during the phase 3 work. Since the phase 3 algorithm maturity level is what the final image 

processing and image assessment system code will be built upon, including prototype code, verification methods, and test data, it 

is imperative that the phase 2 deliveries are well researched and the methodologies are clearly defined. 

The LDCM instruments will not be completed until the later portion of phase 3; therefore, the algorithm updates, and possibly new algorithms, will be delivered if found to be needed as the instrument is built. Changes are likely before the instruments’

preship reviews. After the instrument preship reviews, a final phase 3 delivery will occur, with expectations of no significant 

changes at that point. The follow-on phase 4 will contain updates determined once the instrument is in orbit as real-time data are 

collected, especially during the on-orbit check-out period. The responsibility for researching and delivering phase 2 algorithms 

were members of the CVT at the NASA Goddard Space Flight Center and at the USGS EROS. The collaboration between these 

two groups along with external researchers at South Dakota State University, Rochester Institute of Technology, and the instrument vendors at Ball Aerospace and Technology Corporation, and NASA Goddard, were essential to these phase 2 algorithm 

deliveries. For further information, contact John Dwyer, USGS EROS, dwyer@usgs.gov.

International Cooperator Meeting: 38th Landsat Ground Station Operators Working Group

The 38th Landsat Ground Station Operators Working Group (LGSOWG #38) meeting was held in Berlin, Germany, 

September 28–October 5, 2009. The meeting was jointly organized by the USGS and NASA and was hosted by the German 

Aerospace Center (DLR). Participants from 11 countries (fig. 91) represented 14 international ground stations who discussed a 

wide range of programmatic and technical topics.

Presentations included Landsat 5 and Landsat 7 mission status, the Landsat Project’s web-enabled product distribution 

statistics, Landsat 4 Thematic Mapper (TM) and Landsat 1–5 Multispectral Scanner (MSS) product development progress, the 

Global Land Survey Projects, the Landsat Global Archive Consolidation initiative, proposed data validation and exchange modiFigure 90. The algorithm maturity level is mapped from the instrument provider to the Calibration and Validation Team for algorithm 

design to Data Processing and Archive Segment development. The green box (across center of diagram) identifies the phase of 

development along with interfaces and a rough event synchronization.`
68 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

fications, and future development plans. LDCM-related presentations included project and ground system status, ground system 

and downlink overview, data processing flow, and the LDCM Ground System-to-International Cooperator interface, including 

the International Cooperator Web Portal. Additionally, the USGS Land Remote Sensing Program provided the attendees with an 

overview of the future land remote sensing satellite data downlink framework agreement, along with the National Land Imaging 

initiative’s international vision and goals. A Landsat Science Team update was also presented, providing an update on its working group activities and several key research projects.

Each International Cooperator briefed the group on the status of their systems, addressed their future satellite mission(s) 

and ground system plans, and provided an overview of their data distribution statistics and business model impacts since the 

introduction of Landsat web-enabled data. Finally, a representative from the Australian Department of Climate Change capped 

the meeting with a briefing on the Group on Earth Observation (GEO) Forest Carbon Tracking (FCT) initiative.

International Cooperators in attendance included representatives from the following countries and organizations:

• Australia (GA-NEO) 

• Brazil (INPE) 

• Canada (CCRS) 

• China (CEODE) 

• Europe (ESA) 

• Germany (DLR) 

• Indonesia (LAPAN) 

• Japan (RESTEC) 

• Mexico (CONABIO) 

• Sweden (SSC) 

• Thailand (GISTDA)

For further information, contact Steve 

Labahn, USGS EROS, labahn@usgs.gov.

International Cooperator Meeting: 19th Landsat Technical Working Group 

The 19th Landsat Technical Working Group (LTWG #19) meeting was held in Phuket, Thailand, March 22–26, 2010. The 

meeting was jointly organized by the U.S. Geological Survey (USGS) and NASA and was hosted by the Thailand Geo-Informatics and Space Technology Development Agency (GISTDA). Participants from nine countries (fig. 92), including members 

of the USGS Landsat and Landsat Data Continuity Mission (LDCM) Projects, represented 14 international ground stations who 

discussed a wide range of Landsat technical topics.

Landsat Project presentations included Landsat 5 and Landsat 7 mission statuses as well as the latest Landsat 5 Traveling 

Wave Tube Amplifier testing results, Landsat 1–5 Multispectral Scanner product development progress, Global Land Survey 

status, the Landsat Global Archive Consolidation initiative, and Data Validation and Exchange enhancements. With the LDCM 

Ground System undergoing a major re-architecture activity throughout the last year, this was also a primary area for discussion. 

LDCM presentations included Project and Ground System status including plans and timelines for LDCM Ground System processing software availability, Science Data Reception, Science Data Processing, LDCM Ground System-to-International Cooperator interface, including the International Cooperator Web Portal, and a discussion on LDCM Data Validation and Exchange. A 

Landsat Science Team update was also presented, providing information on its working group activities and several key research 

projects.

Each International Cooperator briefed the group on the status of their systems; presented their future satellite mission(s), 

ground system plans, and Landsat Metadata Initiative (LMI) implementation status; and provided an overview of their data 

distribution statistics. Finally, a representative from the European Space Agency (ESA) capped the meeting with a briefing on 

the Sentinel-2 mission.

• International Cooperators in attendance included representatives from the following countries and organizations:

Figure 91. Group photograph from the 38th Landsat Ground Station 

Operators Working Group (LGSOWG #38) meeting held in Berlin, Germany, 

September 28–October 5, 2009.
Remote Sensing Activities 69

• Australia (GA-NEO)

• Brazil (INPE)

• China (CEODE)

• Europe (ESA)

• Indonesia (LAPAN)

• Japan (RESTEC)

• Russia (ScanEx)

• Sweden (SSC)

• Thailand (GISTDA)

For further information, contact Steve 

Labahn, USGS EROS, labahn@usgs.gov.

Land Satellites Data System Consolidated Exhibit 300

In January 2010, the Office of Management and Budget approved a proposal by the U.S. Geological Survey to consolidate 

the Landsat Operations and Landsat Data Continuity Mission investments into the Land Satellites Data System (LSDS) investment. LSDS is an umbrella program, composed of several projects, that supports and ensures coordinated planning and management of these inter-related efforts. The projects and Department of the Interior’s Project Management Office have worked well 

together in implementing this new approach, developing common management plans wherever possible, and completing the 

required budget year FY 2012 capital planning exhibit 300 by the September 2010 deadline. For further information, contact 

David Hair, USGS EROS, hair@usgs.gov.

Data Management and Distribution

The USGS EROS Center manages a variety of data collections acquired from a wide array of current and historical sources, 

and distributes them to a broad range of global and niche user communities in science, applications, and operations. Data 

sources range from active satellite missions that are operated by EROS and others, historical aerial and satellite sources, as well 

as information about elevation, land cover, and other aspects of the Earth’s land surfaces and data that are maintained in EROS’ 

archives. The archives include film and digital systems developed commercially, in-house, and by and with other collaborators 

such as NASA. Access to the data is via a number of web-enabled user interfaces tailored to the collaborators’ and users’ needs, 

from simple websites to fully featured data discovery tools. In addition to managing the data as bits, EROS maintains the data 

via a data calibration and validation function, as well as science-based collection appraisals, and works with NASA and academia to ensure the integrity and value of the data. EROS uses this broad range of capabilities in collaboration with a number of 

partners to more effectively meet USGS strategic objectives. 

Image Server/ArcGIS Server Now Providing NAIP Web Mapping Service and Downloads

The National Agriculture Imagery Program (NAIP) consists of data acquired by the U.S. Department of Agriculture, with 

contributions from other Federal agencies, such as the U.S. Geological Survey. The data are utilized by the U.S. Geological 

Survey (USGS) as an Orthoimagery layer within The National Map. The data are a consistent 1-meter resolution, natural color 

or 4 band, leaf on, and cover the conterminous 48 states (fig. 93). The previous layer was distributed for web mapping services 

and online downloads via ArcIMS and using the ESRI Spatial Database Engine (SDE). With the release of the new The National 

Map interface, EROS was tasked to transition the NAIP imagery to ESRI Image Server and ArcGIS server technology. The transition consisted of loading NAIP imagery to a Storage Area Network (SAN) and creation of service overviews. The data were 

added to a single layer web mapping service and made available for downloads. The move from SDE to Image Server/ArcGIS 

Figure 92. Group photograph from the 19th Landsat Technical Working Group 

Meeting held in Phuket, Thailand, March 22–26, 2010.
70 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

technology for NAIP is the first phase of transition. The next phase will be to transition the most current high resolution Orthoimagery. For further information, contact S. Jean Paulson, Paulson@usgs.gov.

DATA.gov: Access to High Resolution Orthoimagery

DATA.gov is an official website of the U.S. Government. The website allows users to query for many kinds of data available for public consumption. The USGS was tasked to populate the DATA.gov website with metadata records representing 

observational science records. As part of the task, EROS registered 72,000+ High Resolution Orthoimagery (HRO) files, and 

1,000+ Shuttle Radar Topography Mission files with DATA.gov. 

This was accomplished by sending 

metadata records to the Environmental 

Systems Research Institute for registration in Geospatial One Stop (GOS). 

Once the metadata were registered in 

GOS, they were marked for inclusion 

in DATA.gov. Users now have the 

capability to search DATA.gov for High 

Resolution Orthoimagery and download 

the actual imagery of the search (figs. 

94 and 95). EROS will continue to 

register metadata records in FY 2011. 

For further information, contact S. Jean 

Paulson, Paulson@usgs.gov.

Figure 93. The map illustrates the coverage area in the continental 48 states of 

National Agriculture Imagery Program imagery. 

Figure 94. Search page at DATA.gov.
Remote Sensing Activities 71

Hazards Data Distribution System Graphical User Interface

A new Hazards Data Distribution System graphical user interface (fig. 96) was developed and implemented in support of 

Emergency Operations. This interface offers a significant improvement in functionality from the previous system by giving users 

the capability to enter query criteria for their area of interest. The query can be selected by event, State and county, and/or by selecting a graphical area of interest. Other features include the capability of selecting ingested data and ad hoc data, the provision 

of a Rich Site Summary (RSS) feed, ability to refine the search results, and creation of an item basket. For further information, 

contact Wayne Miller, USGS EROS, wamiller@usgs.gov.

Figure 95. Downloaded image from search results. Pierre, 

South Dakota, 0.30-meter resolution natural color, April 2005 

acquisition.

Figure 96. The new graphical user 

interface in the Hazards Data Distribution 

System.
72 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

New EarthExplorer Implementation

The steadily increasing user demands for data, especially since offering all archive data at no-charge, prompted concerns 

about the scalability, performance, and overall architecture of the current EarthExplorer system. In addition, new support 

requirements for the upcoming Landsat platform presented an opportunity for the redesign of this interface. The new EarthExplorer system (fig. 97) will replace the current system with a distributable open source architecture that is designed to fulfill the 

mission requirements of the Long Term Archive and the Landsat Data Continuity Mission projects. It offers a scalable platform 

centered on new technology and framework design which will help to effectively meet future requirements for access and distribution into the future. For further information, contact Wayne Miller, USGS EROS, wamiller@usgs.gov.

SPOT 1–3 Historical Archive L1G Processing

In 1999, the USGS EROS Center received, for archive purposes, satellite image data flown by the SPOT satellite systems. 

The USGS Satellite Pour l’Observation de la Terre (SPOT) archive contains North American coverage between 10 and 87 degrees north latitude acquired between 1986 and 1998 from SPOT 1, 2, and 3 satellites. Continuing work that began in FY 2009, 

the Long Term Archive project completed processing 615,000 additional FRED (Framed Raw Expanded Data) format images to 

a L1G (systematic) GeoTIFF format. All processing was done through the 

National Landsat Archive Processing System (NLAPS). With the help 

of the Landsat project, NLAPS successfully processed a total of 814,424 

images (fig. 98), all of which have been made available for download by 

authorized users. For further information, contact Wayne Miller, USGS 

EROS, wamiller@usgs.gov.

Figure 97. The new EarthExplorer System.

Figure 98. A sampling of one of the 814,424 images out of the SPOT 1, 2, and 

3 archive recently processed and now available for download by authorized 

users. (Copyright 2010 CNES Distribution Spot Image)
Remote Sensing Activities 73

SPOT North America Data Buy

In anticipation of a possible data gap before the Landsat Data Continuity Mission data arrival in late 2012, the USGS 

awarded a 1-year contract to Spot Image Corporation to receive moderate-resolution optical imagery (fig. 99) from the SPOT 4 

and SPOT 5 satellites. The goal of the contract is to acquire and populate the archive with SPOT satellite coverage of the conterminous United States each month. 

Starting in December 2009, USGS EROS began receiving SPOT imagery. Data acquisition relies on current antenna and 

data capture capabilities. Incoming scenes are processed to a L1A and L1Gst level in GeoTIFF format, and distributed at no 

charge via the Internet to U.S. Federal, civil, State, and local government users, per the licensing arrangements of the Data Buy 

contract. Data access is provided to registered users through USGS EarthExplorer (http://earthexplorer.usgs.gov). For further 

information, contact Wayne Miller, USGS EROS, wamiller@usgs.gov.

Phoenix V Archive Scanning

The objective of building and operating Phoenix V scanning systems was to create and web-enable a 25-micron digital 

copy of the USGS aerial film archives. Beginning with vinegar syndrome affected rolls, the Long Term Archive project is systematically generating a digital high-resolution copy of the entire USGS film collection. 

Film scanning began in October 2009 with three systems operating 24 hours a day, 5 days a week. The fourth system was 

added in the first quarter, the fifth in the second quarter, and the sixth 

and final system in the fourth quarter of FY 2010. The production team 

averages digitizing more than 10,000 images a week. By the end of the 

third quarter, there were more than 260,000 images (fig. 100) scanned, 

archived, and made available for download at no charge via the Internet. For further information, contact Wayne Miller, USGS EROS,

wamiller@usgs.gov.

Figure 99. A sampling of the moderate-resolution optical imagery being 

received from the SPOT 4 and SPOT 5 satellites. (Copyright 2010 CNES 

Distribution Spot Image)

Figure 100. A sampling of one of the 260,000+ digital high-resolution 

images that originated from the USGS film collection that was 

scanned, archived, and made available for download.
74 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

eMODIS System Enhancements Support New Users

NASA’s MODIS is used to provide a range of land process products for the land science community, including vegetation 

indices (VI) such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The terrestrial 

monitoring community has been using MODIS data extensively since its release in 2000. The enhanced MODIS (eMODIS) production system was developed as an expedited VI time series delivery capability to replace the EROS Direct Broadcast System 

in 2006. To date, VI time series products have been developed for the conterminous United States and Alaska, including historical and forward processing of precision VI products and expedited products for CONUS. Beneficiaries of the eMODIS products 

include other USGS projects, such as drought monitoring and ecosystem performance modeling, and external agencies such as 

the U.S. Department of Agriculture, the Bureau of Land Management, and various other agencies throughout the conterminous 

United States and Alaska.

In FY 2010, the eMODIS product suite was both expanded geographically in scope and ported to a new processing 

framework. The USGS component of U.S. Agency for International Development’s (USAID’s) Famine Early Warning System 

(FEWS) formalized a product stream developed for the Haiti/Caribbean region and developed a new product stream for Africa 

(fig. 101). For each of these, historical VI time series (from 2000 to the present) were produced, and forward precision and 

expedited product streams were initiated for ongoing delivery. Conterminous U.S. and Alaska production also continued during 

FY 2010.

The older eMODIS system used lower level (L1B) MODIS data to produce surface reflectance and subsequent VIs (NDVI, 

VI) to be made into composites for varying time intervals. The new system exploits swath-based (Level 2) surface reflectance 

inputs from NASA’s LAADS (Level 1 and Atmospheric Distribution System) for precision historical and forward processing, 

reducing production costs, and producing eMODIS products, which are more directly traceable back to standard MODIS surface 

parameters. As well, the new system uses Level 2 surface reflectance products from NASA’s Land and Atmosphere Near real 

time Capability for EOS (LANCE) for the expedited VI streams. The system software was streamlined and ported to a clusterbased architecture for improved scalability, upgradeability, reliability, and performance. For further information, contact David 

Meyer, USGS EROS, dmeyer@usgs.gov. 

NASA EOS Terra Mission Celebrates 10 Years at LP DAAC

The NASA’s Land Processes Distributed Active Archive Center (LP DAAC) located at the USGS EROS Center celebrated 

10 years of providing land data products from instruments aboard the Earth Observing System (EOS) Terra spacecraft. These 

products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal 

Figure 101. Famine Early Warning System implementation of LANCE-based eMODIS expedited VI time series.
Remote Sensing Activities 75

Emission and Reflection Radiometer (ASTER), were first released publicly from the LP DAAC in 2000.

December 18, 2009, marked the 10th year since the launch of Terra, one of NASA’s “flagship” Earth observing satellites. 

But the decade is more than just a mechanical milestone. With each additional day and year that the satellite monitors Earth, scientists achieve a lengthened record of Earth’s vital signs. It’s that record that helps scientists assess the health of Earth’s ocean, 

land, and atmosphere, and determine how these systems are changing.

Since the public release in 2000, more than 98 million Terra data files have been distributed from the LP DAAC to the public. The mission was celebrated at EROS during August 2010 with a lobby display of earth science applications which, through 

the past 10 years, have benefitted from these MODIS and ASTER products. For further information, contact Thomas Sohre, 

USGS EROS, tsohre@usgs.gov. 

LP DAAC Moves Entire Archive Online

As part of the NASA Earth Science Data and Information System (ESDIS) evolution and efficiency efforts, ESDIS has 

delivered a capability to store the holdings of all ASTER and MODIS datasets on spinning disk in the Land Processes Distributed Active Archive Center (LP DAAC) located at EROS. This archive today totals 1.1 petabytes (PB), with calendar year 2010 

volume of more than 1.8 PB of disk space available for online storage of ASTER and MODIS product lines. 

This online technology implementation has enabled the LP DAAC to remove 3 tape silos from our system architecture (fig. 

102). The online architecture has also allowed the EOS Project to condense the footprint of computer room floor space holding 

the ESDIS Core System by half from 2007.

This capability also allows for a large number of possibilities in how to service our customer’s remote sensing needs from 

the available archive. The EOS Project along with NASA ESDIS is working on modifications to system architecture and clients 

to leverage this new capability related to how the archive is searched, results are displayed, and the EOS data are downloaded. 

EOS Project results suggest that LPDAAC data distribution will continue to increase as the archive grows and the system architecture is modified to enable data to become more accessible under an on-demand model (fig. 103). For further information, 

contact Thomas Sohre, USGS EROS, tsohre@usgs.gov. 

LP DAAC Supports Emergency Response Activities

NASA’s Land Processes Distributed Active Archive Center (LP DAAC) located at EROS supported a number of emergency 

response activities in FY 2010 with Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data.

The California Station Fire: On August 26, 2009, the Station Fire, caused by arson, spread in the Angeles National Forest 

and San Gabriel Mountains north of Los Angeles, California (fig. 104). More than 160,000 acres had burned by the morning of 

September 9, with associated loss of life, destruction of numerous buildings, and threat to about 4,000 structures. Key commuFigure 102. Land Processes Distributed Active Archive 

Center team shown inside and alongside one of the three tape 

silos removed from the system architecture. Figure 103. Trends indicate Land Processes Distributed 

Active Archive Center data distribution will continue to 

increase as the archive grows and is available on demand.
76 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

nication equipment and facilities on Mount Wilson were threatened, including the world-renowned astronomical observatory. 

Nearly 4,500 individuals were assembled to combat the blaze, at a cost of more than $70 million for just the first two weeks of 

firefighting. NASA Earth Observing System satellites acquired data used to characterize the extent of the burned regions and the 

threat posed to adjacent areas. The ASTER and the MODIS instruments provided timely information for analysis.

Flooding Traps Travelers at Machu Picchu, Peru: Fatalities, severe flooding, landslides and extensive destruction occurred 

because of heavy wet-season rainfall in southern Peru during January 2010. Thousands of residents in Cusco were left homeless. 

Northwest of Cusco, nearly 2,000 tourists at Machu Picchu were unable 

to leave the remote and rugged location when a railroad track along the 

Urubamba River was severely damaged in many locations. Evacuations 

were conducted for several days using military helicopters. Daily losses to 

the Peruvian economy resulting from canceled tourist visits were estimated to be $1 million. Railroad repairs were forecast to take many weeks. 

Satellite images acquired by ASTER were used to portray the Machu 

Picchu region before and after flooding (fig. 105). The ASTER instrument orbits Earth on the Terra spacecraft at an altitude of 438 miles (705 

kilometers).

Figure 104. Land Processes Distributed Active Archive Center (LP DAAC) 

Advanced Spaceborne Thermal Emission and Reflection Radiometer 

(ASTER) California Station Fire poster.

Figure 105. Land Processes Distributed Active Archive Center (LP DAAC) 

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 

Machu Picchu, Peru, poster.
Remote Sensing Activities 77

Eyjafjallajökull Volcano, Iceland: A renewed eruptive period at Eyjafjallajökull Volcano commenced in March 2010. The 

plume posed significant risk to aviation and resulted in numerous flight cancellations throughout an extended period. The NASA 

Earth Observing System Terra satellite, launched in December 1999, continues to provide exceptional images of the Earth for 

scientific analysis. Land data from ASTER and MODIS on Terra revealed the status of volcanic activity on April 19, 2010. An 

ASTER thermal infrared (TIR) band was used to identify the hotter areas. In addition to providing temperatures, ASTER TIR 

data can also be used to discriminate ash, water vapor, ice and 

sulfur dioxide, among other uses. An ASTER expedited view of 

the Eyjafjallajökull Volcano was acquired at 12:51 Coordinated 

Universal Time (UTC) on April 19, 2010, from a 705-kilometer 

altitude on the Terra spacecraft (fig. 106). The image was generated 

using ASTER registered radiance at the sensor data, with visible 

and near-infrared (VNIR) bands simulating natural color. The 

ground resolution is 15 meters. A billowing white and gray plume 

emanating from Eyjafjallajökull is visible drifting to the south and 

covering a large area. Expansive snow-covered areas appear white. 

Vegetation is visible in shades of green, with water dark blue. A 

density slice overlay using the 90-meter ground resolution thermal 

infrared (TIR) band 14 at 10.95 to 11.65 micrometer (μm) wavelengths approximates relative temperatures. The hottest pixels are 

portrayed in yellow, representing the highest TIR band 14 digital 

numbers in this scene. While still hot, the TIR pixels colored orange and red are at relatively lower temperatures. Another hot area 

representing an earlier and now-cooling flow is evident northeast of 

Eyjafjallajökull at Fimmvörduháls. 

Louisiana Oil Spill: The ASTER and MODIS instruments on Terra provided a lengthy series of imagery of the U.S. Gulf 

Coast region affected by the Deepwater Horizon oil spill. From the commencement of the event through mid-July 2010, 20 ASTER expedited taskings were scheduled in support of this activity. For further information, contact Thomas Sohre, USGS EROS, 

tsohre@usgs.gov. 

LP DAAC Develops ASTER GDEM Case Study

The Land Processes Distributed Active Archive Center (LP DAAC) developed a case study of the ASTER Global DEM 

(GDEM) in support of the Group on Earth Observations (GEO) Data Sharing Task Force (DSTF). The DSTF is moving toward 

the GEO Plenary and Ministerial with an Action Plan. Supporting documents included eight case studies, of which the ASTER 

Global DEM is one.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) remote sensing instrument on the Terra 

spacecraft has been acquiring images of Earth since it was launched in 1999. Throughout this time, data products have been 

openly available to the general public through sites in the United States and Japan. However, the release of a new product, the 

ASTER Global Digital Elevation Model (GDEM), has dramatically increased usage of ASTER data worldwide (fig. 107). 

The GDEM was contributed by Japan’s Ministry of Economy Trade and Industry (METI) and NASA to the Global Earth 

Observation System of Systems (GEOSS) for distribution at no cost to users via electronic download from the Earth Remote 

Sensing Data Analysis Center (ERSDAC) of Japan and from NASA’s LP DAAC.

The release of the global tiled research-grade DEM resulted in a significant increase in demand for ASTER elevation models and increased awareness of related products. No-cost access to these data has also promoted new applications of remotely 

sensed data, increasing their use across the full range of the GEOSS societal benefit areas. The ASTER GDEM demonstrated the 

need and user demand for a global DEM product as well as the added benefit of not only “full and open” distribution but “free 

and open” distribution.

Figure 106. Land Processes Distributed Active Archive Center (LP 

DAAC) Advanced Spaceborne Thermal Emission and Reflection 

Radiometer (ASTER) Eyjafjallajökull Volcano, Iceland, poster.
78 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

During the first three months after product release, more than 4 million GDEM tiles were distributed from the LP DAAC 

and ERSDAC. The ASTER GDEM release generated nearly 20,000 new user registrations in the NASA ECHO/WIST (EOS 

ClearingHOuse/ Warehouse Inventory Search Tool) and the ERSDAC systems. By the end of 2009, more than 6.5 million 

GDEM tiles were distributed by the LP DAAC and ERSDAC. Users have requested tiles for specific areas of interest as well as 

the entire dataset for global research. 

Intense global interest in the GDEM across all the GEOSS societal benefit areas was shown. The volume of GDEM distribution can be directly attributed to the adoption of fundamental GEOSS data sharing principles, which are directed toward 

expanded access by minimizing time delay and cost, thus facilitating data use for education, research, and a range of other applications. For further information, contact Thomas Sohre, USGS EROS, tsohre@usgs.gov. 

Interagency Agreement Signed for FY 2010–14 Operation of LP DAAC at EROS

The U.S. Department of the Interior (DOI) USGS EROS Center is currently managing and operating the Land Processes 

Distributed Active Archive Center (LP DAAC) in support of NASA requirements for the Earth Observing System Data and 

Information System (EOSDIS) devoted to the collection, processing, archiving, and distribution of land processes data. 

For FY 2010, the DOI and USGS signed a follow-on agreement with NASA for the operations and maintenance of the LP 

DAAC at EROS during fiscal years 2010 through 2014. This agreement has existed since the mid-1990s and currently provides 

for robust ingest, archive, storage, and distribution capabilities. The LP DAAC is responsible for distributing more data than 

any other project within the USGS EROS and is proud to be recognized by NASA as a strong and supportive organization that 

fulfills the Earth Science Data and Information System (ESDIS) 2015 Vision Tenets. 

NASA Earth Observing System (EOS) is a long-term, interdisciplinary, and multidisciplinary research mission to study 

global-scale processes that shape and influence the Earth as a system. The EOS mission is partially accomplished through the 

provision of a comprehensive data and information system to provide the earth science research community with easy, affordable, and reliable access to the EOS and other appropriate earth science data. For further information, contact Thomas Sohre, 

USGS EROS, tsohre@usgs.gov.

Distribution of Earth Science Data

EROS distributes approximately 200–250 terabytes (TB), or 200,000–250,000 gigabytes, of earth science data monthly. Of 

this total, an average of 50 TB is distributed via individual hard drives and the remainder is transferred via a high-speed network.

On average, EROS receives and distributes about one-half of all network traffic transferred through the Department of the 

Interior’s four primary nodes serving the Department’s 70,000 employees and contractors. The nodes are located in Reston, 

Virginia; Denver, Colorado; Menlo Park, California; and Sioux Falls, South Dakota. The Reston node serves approximately 

35,000 users, whereas the Sioux Falls node serves less than 1,000. This suggests a substantial portion of the traffic at other nodes 

comprises incoming electronic mail and browser data, in contrast to the vast majority of Sioux Falls traffic being earth science 

data distributed worldwide. The pie chart (fig. 108) shows the quantity and percentage of traffic through the four nodes for a 

recent month.

The bar charts (figs. 109 and 110) depict the increasing inflow and distribution of earth science data for the last 8 years. The 

total incoming and outbound data flow is shown in figure 109; figure 110 shows outbound data only. The reduction in inbound 

Figure 107. ASTER global digital elevation model visualization.
Remote Sensing Activities 79

data is due primarily to adoption of data compression techniques for data received by the Land Processes Distributed Active 

Archive Center, which ingests data from NASA’s Earth Observing System satellites. The upturn of inbound data in 2010 reflects 

USGS Landsat data received from the Alaskan ground station. The first Landsat web-enabled datasets began to be distributed in 

2008, and growth in user demand and data availability account for the tripling of outbound data volume. For further information, 

contact John Boyd, USGS EROS, boyd@usgs.gov. 

Archive Strategic Direction Committee

The Archive Strategic Direction Committee, sponsored by the Land Remote Sensing Program and the EROS Director, 

recommended including the Large Format Camera collection to the National Satellite Land Remote Sensing Data Archive. The 

Committee also endorsed the Air Photo Scan Rate Review Team work that led to the EROS Science Branch evaluating 34 locations of multiple scanning rates and selecting 25 microns as the level that best captures the necessary land research information. 

For further information, contact John Faundeen, USGS EROS, faundeen@usgs.gov.

Scientific Records Appraisal

Significant work was accomplished this fiscal year in terms of reviewing earth observation collections housed at or offered 

to EROS. The 14 collections appraised included:

• Arc Digitized Raster Graphics

• Controlled Image Base

Figure 108. Quantity and percentage of traffic through 

DOI’s four nodes for August 2010.

Figure 109. Total inbound and outbound data flow for the past 

8 years.

Figure 110. Total outbound data only for the same time 

period.
80 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

• For Official Use Only DOQs

• GeoEye OrbView-3

• NASA Ames Aerial

• NASA Johnson Aerial

• NASA Marshall Aerial

• NASA Wallops Island Aerial

• NASA Stennis Aerial

• NASA Kennedy Aerial

• DoD Army Aerial

• DoD Air Force Aerial

• DoD Navy Aerial

DoD Corps of Engineers Aerial

A professional paper was published entitled, “Appraising U.S. Geological Survey Science Records” in Archival Issues, the 

journal of the Midwest Archives Conference. The paper detailed the USGS EROS Scientific Records Appraisal Process including our results to date. For further information, contact John Faundeen, USGS EROS, faundeen@usgs.gov.

Represent USGS Records Management

Several forums were exploited to represent USGS Records Management in FY 2010. Brief summaries of the more significant events are included: 

A USGS-National Archive and Records Administration (NARA) Memorandum of Understanding (MOU) meeting held 

at the NARA headquarters involved senior management from NARA, the USGS Geography Discipline, and the EROS Director. Discussions included the way forward for topics included in the 2008 MOU. These discussions led to subsequent strategies 

being developed at EROS that accomplish multiple points addressed in the MOU leading to the completion of the Geography 

Scientific Records Disposition Schedule, which has been under review by NARA since 2005.

Records management training was co-provided to headquarters staff and Water Science Center personnel in San Antonio, 

TX; San Diego, CA; and Austin, TX. New EROS Government and contract personnel were also provided an introduction to 

Records Management with an emphasis on record-keeping responsibilities. A presentation was given in concert with the USGS 

Records Managers from headquarters and the Western Region at the ITEM2010 Conference.

A presentation entitled “Ensuring Geospatial Records Viability Through Time” was presented at the American Society for 

Photogrammetry and Remote Sensing (ASPRS) Annual Conference. The ASPSRS Digital Preservation and Archive Committee 

focused on ways the Committee could better serve its members.

An invited paper entitled “Archiving Strategy for USGS EROS Center and Our Future Direction” was presented at the 

National Institute of Standards and Technology during the U.S. Workshop on the Road for Digital Preservation Interoperability 

Framework.

Participated in an invitation-only workshop sponsored by the Library of Congress. The focus of the workshop was digital 

preservation best practices. Attendees included the National Archives and Records Administration, the Environmental Protection 

Agency, the Census Bureau, the National Oceanographic and Atmospheric Administration, and several universities.

Completed an extensive survey, in-person follow-up, and attended a workshop for a European Space Agency initiative to 

determine best practices for archiving Earth Observation records.

Invited to participate in the Library of Congress sponsored 2010 Digital Preservation Partners Meeting. The topics addressed included the role of collaboratives in promoting digital preservation, the challenges of preserving social media content, 

and issues going beyond archiving.

Participated in the Scientific Data Management (SDM) for Government Agencies Workshop to Improve SDM. Karen Siderelis from the Department of the Interior was a speaker at the event.

For further information, contact John Faundeen, USGS EROS, faundeen@usgs.gov.
Remote Sensing Activities 81

USGS Data Rescue Initiatives

Along with the Long-Term Archive Project, staff facilitated the first shipment of acetate-base (vinegar syndrome-affected) 

film to the National Archives and Records Administration. This preservation effort began several years ago and will take multiple years to complete.

Staff briefed the Geographic Information Office National Leadership Team on the USGS Data Rescue initiative documenting the efforts to date as well as documenting the tremendous need expressed by our scientists.

Staff compiled the FY 2010 USGS Data Rescue submissions by Discipline, coordinated rankings by the individual Disciplines, and assisted in the disbursement of more than $400,000 in grants to scientists preserving and making more accessible our 

legacy science records. Through strong support provided by the Geographic Information Office, substantially more projects were 

funded this year than any other since the initiative began in FY 2007. For further information, contact John Faundeen, USGS 

EROS, faundeen@usgs.gov.

EROS History Project

A concerted effort by a small team of employees resulted in an internal EROS website dedicated to the history of the EROS 

Program and Center. Documents, still pictures, and movies have been assembled or scanned with many more planned. Several 

thousand files have been gathered to date and approximately 50,000 slides were reviewed by the team. Historical files dating to 

the early 1970s are now accessible. For further information, contact John Faundeen, USGS EROS, faundeen@usgs.gov.

Consolidated Archive and Distribution Data Report: A Monthly “Consolidated Report” for All Data 

Managed and Distributed at EROS

Working with input from projects, EROS prepared a report template to be used by the projects for inputting their respective 

data. The template has been reviewed by the projects and the USGS Land Remote Sensing Program. The report provides statistics in terabytes distributed and data managed in FY 2010. 

Data distributed and managed for all projects, showing both monthly and cumulative totals is shown in figures 111–114. 

Data distributed and managed are shown in figures 115–124 for the following groupings:

• Landsat (figs. 115–116)

• LP DAAC (figs. 117–118)

• Other Satellite (figs. 119–120)

• Non-Satellite (figs. 121–122)

• Geospatial (figs. 123–124) including Orthoimagery, Elevation, Land Cover, and Other

For further information, contact John Faundeen, USGS EROS, faundeen@usgs.gov.

Figure 111. Fiscal year 2010 

Land Processes Distributed 

Active Archive Center, Landsat, 

other satellite, non-satellite, and 

geospatial data distributed.
82 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Figure 113. Fiscal year 2010 

Land Processes Distributed 

Active Archive Center, 

Landsat, other satellite, nonsatellite, and geospatial data 

distributed.

Figure 114. Fiscal year 2010 

Land Processes Distributed 

Active Archive Center, 

Landsat, other satellite, nonsatellite, and geospatial data 

managed.

Figure 112. Fiscal year 2010 

Land Processes Distributed 

Active Archive Center, Landsat, 

other satellite, non-satellite, and 

geospatial data distributed.
Remote Sensing Activities 83

Figure 115. Fiscal 

year 2010 satellite data 

distributed.

Figure 116. Fiscal 

year 2010 satellite data 

managed.

Figure 117. Fiscal year

2010 Land Processes 

Distributed Active Archive 

Center data distributed.
84 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Figure 119. Fiscal year

2010 other satellite data 

distributed.

Figure 120. Fiscal year

2010 other satellite data 

managed.

Figure 118. Fiscal year 2010 

Land Processes Distributed 

Active Archive Center data 

managed.
Remote Sensing Activities 85

Figure 122. Fiscal year

2010 non-satellite data 

managed.

Figure 123. Fiscal year

2010 geospatial data 

distributed.

Figure 121. Fiscal year

2010 non-satellite data 

distributed.
86 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Calibration and Validation

Remotely sensed data are a valuable tool in the management, study, and monitoring of the Earth’s surface. The usability 

and reliability of these data for users and decision makers depends on the accuracy with which these data represent the surface 

of the Earth and the processes underway on it. The USGS, as a critical provider and user of remotely sensed data, products, and 

services, places a critical reliance on the accuracy, understanding, and limitations of the data because of the technologies used 

to generate them. Other agencies, as well as the broad user community in the United States and around the world, rely on the 

USGS to provide assessment of these data. The value of remote sensing observations is assessed according to its accuracy and 

ability to assess change required to address societal needs. 

Satellite Data Characterization and Joint Agency Civil Imagery Evaluation (JACIE) Team

The USGS Remote Sensing Technologies (RST) Project continued research into the quality and usability of remotely 

sensed data from satellite and airborne platforms, public or private, U.S. or foreign. During FY 2010, system evaluations performed by Project staff included satellite system analysis of numerous systems and assessment of multiple aerial imaging and 

new technology systems. The major satellite assessment efforts included WorldView-1 and -2 (United States of America), the 

5-satellite RapidEye constellation (Germany), DMC constellation satellites (United Kingdom), ResourceSat-1 (India), CBERS2B (Brazil), SPOT 4 and SPOT 5 (France), THEOS (Thailand), and COSMO-SkyMed (Italy). The Project also assessed remote 

sensing technologies via system owners, manufacturers, and partners in supporting recommendations for both new missions and 

the Landsat Data Gap. NASA understands the value that detailed calibrations of these and other system instruments provide, 

and funded the Project to support instrument calibration and validation processes in FY 2010 under their Land Cover Land Use 

Change (LCLUC) Program. 

The Joint Agency Civil Imagery Evaluation (JACIE) Workshop is led by the USGS RST Project in partnership with the 

USGS, NASA, the National Geospatial-Intelligence Agency (NGA), and the United States Department of Agriculture (USDA). 

The USGS and the JACIE team partners co-sponsored the ninth annual Civil Commercial Imagery Evaluation Workshop 

March 16–18, 2010, in Fairfax, Virginia, to allow collaboration with other international, Federal, State, and local government 

agencies, academia, and industry. The Keynote speakers were the Department of Interior’s Deputy Assistant Secretary for Water 

and Science, Deanna Archuleta, and Dr. Franz Leberl, founder of Microsoft’s Vexel Corporation and current chaired professor of Computer Science at Graz University of Technology Graz, Austria. Attendees at the workshop numbered approximately 

140 from various government and commercial organizations exchanging information regarding the characterization and application of civil commercial imagery used by Government and commercial groups to support independent system and product 

validation (fig. 125). The tenth annual JACIE workshop is planned for March 29–31, 2011, in Boulder, Colorado.

The following list highlights the international Earth observation calibration and validation working groups, meetings, and 

accomplishments the Project supported in FY 2010:

Figure 124. Fiscal year 2010 

geospatial data managed.
Remote Sensing Activities 87

• The Quality Assurance Framework for Earth Observation (QA4EO) Workshop on Facilitating Implementation in the 

Group on Earth Observations (GEO) community sought to harmonize and standardize satellite data quality throughout 

the international community. A short QA4EO “user” guide was made available from the QA4EO website at http://qa4eo.

org/documentation.html. 

• Attendance at the first-ever GEO Work Plan Symposium meeting in South Africa.

• Continued support to the Committee on Earth Observation Satellites (CEOS) through QA4EO and four major international Infrared and Visible Optical Sensors (IVOS) campaigns: CEOS Land Surface Imaging (LSI) Dome C Campaign, 

CEOS Infrared Spectral Emitted Radiance Comparison, and the CEOS Comparison of Land Surface Reflectance I and II. 

• Development of a catalog of worldwide test sites for sensor characterization including the release on EarthExplorer 

(http://edcsns17.cr.usgs.gov/EarthExplorer/) of the CEOS-endorsed globally distributed reference standard test sites. 

• Ongoing activities with the CEOS Working Group on Calibration and Validation (WGCV), the Infrared and Visible Optical Systems (IVOS) Subgroup, the Strategic Implementation Team, the WGCV chairmanship, the 31st WGCV Plenary, 

and joint 32nd WGCV Plenary/Working Group on Information Systems and Services (WGISS) Meeting. 

• Expertise to the International Society of Photogrammetry and Remote Sensing (ISPRS) Commission I (Data Acquisition 

- Sensors and Platforms) in camera and sensor calibrations from around the world, including coordinated research and 

standards development; and support to the International Standards Organization (ISO) 19159–Calibration and Validation 

of Remote Sensing Imagery Sensors and Data work. 

• Remote sensing leadership and representation to the ASPRS and Management Association for Private Photogrammetric 

Surveyors (MAPPS) focused on (a) digital imagery, (b) the evolving technology options and innovative techniques for 

data analysis and fusion, and (c) lidar standards and best practices. 

The Project plays a key role in assessment and coordination of civil government remote sensing user data requirements, in 

support of the Commercial Remote Sensing Space Policy (CRSSP) and its data requirements, as the USGS maintains its leadership and support to the Office of Science and Technology Policy, the National Geospatial-Intelligence Agency, and the U.S. 

Space Policy. The Project operates the CRSSP Imagery Derived Requirements (CIDR) tool and actively works with users to define data requirements. During the first 10 months of FY 2010, a total of 550 new imagery requirements were received, of which 

356 have been validated and coordinated with other Federal users previously submitting requirements. For further information, 

contact Greg Stensaas, USGS EROS, stensaas@usgs.gov, or visit http://calval.cr.usgs.gov/.

Figure 125. The ninth Joint Agency Civil Imagery 

Evaluation Workshop, Fairfax, Virginia, March 2010.
88 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

USGS Quality Assurance Plan for Digital Aerial Imagery

The USGS led the effort in 2010 to establish a Quality Assurance (QA) framework for digital aerial imaging and mapping 

for the nation. Responding to requests and recommendations from the American Society of Photogrammetry and Remote Sensing and the digital imaging and mapping community, the USGS developed a Digital Imagery Quality Assurance Plan (DIQAP) 

that addressed the complete process of obtaining digital aerial data, beginning with the initial specification of data requirements 

through the capture and production of the image products to the final receipt and inspection of the data. 

USGS Sensor Type Certifications in 2010 closely followed part of the traditional role that the USGS has had in the U.S. 

Government of giving procurers of aerial imagery an assurance that the camera/sensor system used in their project is capable 

of producing consistent quality metric aerial data products. The USGS accomplished this through a reimbursable process called 

Sensor Type Certification. In this process, the USGS certification team asks the manufacturer of a sensor type to answer questions describing the design and quality regime under which it is manufactured, tested, calibrated, sold, and supported. The USGS 

team then visits the manufacturer’s facilities to observe and verify those processes. Once the USGS is satisfied the sensors are 

designed, manufactured, calibrated, and supported such that consistent metric imagery will be produced with the specified capabilities and performance measures, a certification of that sensor type is issued. 

The USGS Manufacturer Sensor Type Certification team certified four sensor types from three manufacturers in 2010 and 

continues to work the certification reports for the GeoVantage, Pictometry, and Microsoft Vexcel sensors. The team also established a new reimbursable cost model in 2010 for the manufacturer sensor certification efforts and is including this model in 

new Technical Assistance Agreements (TAA) for four new camera certification agreements in FY 2011. Those companies and 

cameras are Zeiss Intergraph DMC II, Microsoft Vexcel UltraCam L and Lp, DiMAC Camera, and IGI Digital. 

The Data Provider Evaluations using USGS National Ranges in 2010 consisted of requiring data provider’s digital aerial 

products flown over one of five USGS-approved test ranges, a process defined as part of the QA plan. The ortho-mosaic products are then delivered to the USGS for assessment of accuracy. This accuracy and basic details about the company and staff are 

available in a public report. 

Figure 126. An illustration of the web-based “Spec & Check Tool” developed as the basis of 

standard digital aerial imagery specifications and imagery product verification.
Remote Sensing Activities 89

This effort progressed very well in 2010 with the completion of Calibration and Validation Range Specifications, a USGS 

Data Provider Evaluation Plan, a Range Development Plan, three completed ranges in Sioux Falls, South Dakota; Rolla, Missouri; and Pueblo, Colorado. 

Another part of the QA Plan completed in FY 2010 was the development of a web-based digital imagery QA tool to assist 

with the specification and assessment portions of the plan. This application is known as the “Spec & Check Tool” (fig. 126) and 

is being developed at EROS with strong support from National Geospatial Program staff in Rolla and Denver and advice from 

industry and USGS State Liaisons. When completed and utilized by the digital aerial community, this tool will form the basis of 

standard digital aerial imagery specification and imagery product verification. The Project completed “Phase I” development in 

FY 2010 of the digital aerial image specification and verification tool and provided the web framework and design so internal 

stakeholders are able to review and provide input. With funding support, the tool could become operational toward the end of FY 

2011. For further information, contact Greg Stensaas, USGS EROS, stensaas@usgs.gov, or visit http://calval.cr.usgs.gov/.

Aerial Mapping Camera Calibration and Characterization

The USGS Optical Science Laboratory (OSL) has been responsible for providing calibration services for the airborne film 

mapping industry since 1973 and is the only certified analog film camera calibration capability in the United States. An FY 2010 

review of customer requirements suggested that this work is considered critical to the national survey and must be continued by 

the USGS into the near future. The USGS OSL continues to calibrate between 60 and 80 analog cameras a year on a reimbursable basis. The number of film mapping cameras calibrated at the OSL for the last four years is shown in figure 127.

The photographic multicollimator calibration process used in the OSL for determining lens and camera coefficients relies 

on film emulsion coated glass plates. The OSL completed its annual 2-week National Institute of Standards and Technology 

traceable recalibration of the multicollimator assembly that is used to calibrate aerial film cameras from across the country and 

around the world. This annual process is performed to ensure that the OSL is able to continue providing the highest accuracy 

calibrations for the aerial mapping community. Also in FY 2010, a substantially higher number of OSL camera calibration 

services were requested from international public and private sector entities primarily because of the closing of the last foreignbased analog calibration laboratory in Canada as well as locations in Europe operated by Zeiss and Wild camera manufacturers.

As part of aerial mapping camera calibration and characterization in FY 2010, the Project also added three partnerships 

with various universities and government agencies to research digital aerial camera calibration processes using the Calibration 

Laboratory at EROS software and assessment tools. 

Figure 127. The graphic shows the number of film mapping cameras calibrated at the Optical Science Laboratory for 

the last four years.
90 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

The Project also experimented with and evaluated various laboratory and field calibration techniques and software for 

commercial digital cameras using short to relatively long focal lengths (6 to 150 millimeters). With the ever-increasing use of 

commercial digital cameras for aerial applications, one of the accomplishments of FY 2010 was determining the solution for a 

simple calibration technique for use of shorter focal length cameras, for example, those being used on Unmanned Aerial Vehicles (UAVs) and smaller aerial platforms. The solution was a small portable calibration box designed and built for field calibration that uses coded targets and the Australis software application that derives the calibration parameters. The method has been 

called “calibration in a box.” Research on calibrating cameras with a long focal lens more than 200 millimeters (NASA’s DC-8 

research aircraft cameras used for Antarctica mapping mission) was completed with numerous partners, such as the Department 

of Energy’s Lawrence Livermore National Labs (LLNL), the National Geospatial-Intelligence Agency (NGA), and the Army 

Corp of Engineers (COE) on the long focal length lens for the Buckeye system. For further information, contact Greg Stensaas, 

USGS EROS, stensaas@usgs.gov, or visit http://calval.cr.usgs.gov/.

Coordination and Collaboration

As the USGS endeavors to provide overall leadership for land imaging, nationally and internationally, the USGS continues 

to enhance leadership visibility, improve communications between and among the Federal and non-Federal sectors regarding 

remote sensing observations of the Earth, and promote excellence in remote sensing for understanding the Earth’s land environment through education and training. A large part of the efforts to achieve these objectives will be accomplished through continued activities with Committee on Earth Observation Satellites (CEOS) plenary support and CEOS’ standing working groups 

on calibration and validation, on information systems and services, and on education and training. The USGS also has the lead 

role in development of a prototype for the “Land Surface Imaging (LSI) Virtual Constellation”—a CEOS Global Earth Observation System of Systems (GEOSS) initiative (see web portal at http://wgiss.ceos.org/lsip/). The USGS continues to serve as the 

lead U.S. agency to the International Charter “Space and Major Disasters.” Finally, EROS will continue to develop and offer a 

variety of ongoing education and training that together provide remotely sensed data users, and especially potential users, with 

opportunities to become more informed and educated about all aspects of the science and technology of land remote sensing. 

Haiti Earthquake Response

On January 12, 2010, a 7.0 magnitude earthquake struck Haiti. The 

capital of Port-au-Prince suffered major 

damage, and there were several aftershocks greater than magnitude 5.0. 

The International Charter Space 

and Major Disasters (fig. 128) was 

activated on January 13, 2010, by the 

French Civil Protection, the United Nations, Canada Civil Protection, and the 

USGS Earthquake Hazards program. 

USGS provided support to the Charter 

activations and other response activities by coordinating commercial and 

civilian satellite acquisitions and by 

hosting the satellite imagery along with 

aerial photography collected by many 

different sources on the Hazards Data 

Distribution System. 

There are approximately 4.0 terabytes of imagery available, and more 

than 54 terabytes of imagery have been 

downloaded by the response community. For further information, contact 

Brenda Jones, USGS EROS, bkjones@

usgs.gov.

Figure 128. The illustration depicts the 10 International Charter members and satellite 

imagery showing the Presidential Palace at Port-au-Prince, Haiti, before (IKONOS data) and 

immediately after (GEOEYE-1 data) the January 12, 2010, earthquake.
Remote Sensing Activities 91

Chile Earthquake Response

An earthquake and tsunami struck Chile on February 27, 2010. The International Charter Space and Major Disasters was 

activated on behalf of ONEMI, the Chilean Civil Protection Agency, through the Argentine Space Agency, CONAE. There was 

much interest in providing support to the response efforts, and many agencies from around the world made their satellite assets 

available to capture imagery of the destruction. 

The USGS provided support to CONAE and ONEMI by hosting a Remote Sensing Working Group call to discuss requirements and acquisition plans and by requesting collections from the U.S. high-resolution commercial satellites that were hosted 

along with imagery (fig. 129) from other agencies on the Hazards Data Distribution System. Because of the lack of high-speed 

Internet connections following the disaster, the USGS sent hard drives with copies of the imagery to ONEMI for their use in the 

response. The USGS is currently hosting about 500 gigabytes of imagery for the event and continues to post new collections as 

they are acquired. For further information, contact Brenda Jones, USGS EROS, bkjones@usgs.gov.

Figure 129. This map illustrates an overview damage assessment for the area of Concepcion and 

Talcahuano, Chile. 
92 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Deepwater Horizon Oil Spill Response

The Deepwater Horizon explosion occurred on April 20, 2010, and the drilling rig collapsed and sank on April 22, 2010. 

On April 22, 2010, the U.S. Coast Guard sent a request to the USGS for activation of the International Charter Space and Major 

Disasters. The Charter provided radar imagery from the Radarsat, Envisat, and ALOS satellites, which were used to map the 

extent of the spill (fig. 130). 

The USGS supported the National Oceanic and Atmospheric Administration oil spill mapping operations by leading the 

Remote Sensing Working Group telecon, hosting imagery and products on the Hazards Data Distribution System, and helping 

Figure 131. Oil swirls in the Gulf of 

Mexico off the Mississippi Delta in this 

natural-color image from Landsat 5, 

May 25, 2010.

Figure 130. Experimental Marine Pollution 

Surveillance Report provided by National Oceanic 

and Atmospheric Administration on May 8, 2010, 

used in analysis of the Deepwater Horizon Oil 

Spill. Data source: RADARSAT2.
Remote Sensing Activities 93

to acquire additional imagery from Charter members. As part of the Interagency Remote Sensing Coordination Cell, USGS is 

assisting in the collection of remote sensing requirements from State and Federal agencies and providing staffing support as 

required for the Unified Area Command. USGS is also working closely with National Geospatial Intelligence Agency and U.S. 

Air Force Eagle Vision on collection requirements and hosting of satellite imagery. 

As of September 30, 2010, about 16.77 terabytes of imagery representing 466,292 files (fig. 131) have been downloaded 

from the Hazards Data Distribution System. A secure site has also been created for hosting USGS products for USGS only use 

while going through the approval process. For further information, contact Brenda Jones, USGS EROS, bkjones@usgs.gov.

Facilitating Access to Landsat Data for Developing Countries

A USGS policy change has enabled Landsat satellite data to be distributed via the Internet to users all over the world at no 

cost. The USGS is allowing all people to discover, use, and learn from these observations by creating “archives without walls.” 

Developing countries are taking advantage of the data made available through the opening of the Landsat archive and are doing 

so with the support of the International Panel for Global Observation of Forest Cover/Global Observation of Landscape Dynamics (GOFC/GOLD). As a result, a second regional network data workshop was held at the USGS EROS Center May 17–27, 

2010. The workshop was attended by six regional representatives from Asia (Mongolia, Kazakhstan, Turkmenistan, Indonesia, 

Vietnam, and Malaysia). The workshop was geared toward providing developing nation experts with training on how to access, 

manage, and apply data from USGS EROS archives. The six attendees are involved in various aspects of remote sensing applications, particularly land cover and fire activities, but are restricted in their use of Landsat and other data because of Internet 

limitations. With free Landsat data, there is a new opportunity for expanding applications. Specific goals achieved included: (1) 

disseminate Landsat data to the international science community in regions where currently available distribution methods are 

not effective, (2) compile regional and in-country datasets relevant to land cover and fire observations and make them freely 

available to the international community, and (3) engage regional science expertise in the global dataset development, evaluation, and validation. For further information, contact Thomas Holm, USGS EROS, holm@usgs.gov.

USGS Supports CEOS Working Group on Information Systems and Services

The 30th meeting of the Working Group on Information Systems and Services (WGISS) was hosted by the Canadian Space 

Agency (CSA) in Montreal, Quebec, Canada on September 13–17, 2010. The CEOS Working Group on Calibration and Validation (WGCV) was also meeting in Montreal during the same week and approximately 2 days of the meetings were held jointly 

with WGCV and focused on a number of areas of mutual interest and action. The following are key topics stemming from both 

the WGISS Subgroup and Plenary sessions as well as the joint sessions with the WGCV: (1) CEOS/WGISS Integrated Catalog 

(CWIC), (2) Land Surface Imaging (LSI) Constellation Portal, (3) Data Stewardship Interest Group, and (4) USGS Hosting of 

WGISS No.33 in the spring of 2012.

A major portion of the WGISS meeting agenda was allocated to the CWIC initiative. CWIC is intended to be a major contribution from CEOS to the GEOSS and demonstrates how common standards such as the Open Geospatial Consortium (OGC) 

Catalog Service for the Web (CSW), Web Coverage Service (WCS), and the Web Mapping Service (WMS) along with the 

International Standards Organization (ISO) 19115 metadata standard can be used to facilitate cross-agency inventory searches 

and data access through a single client interface. The LSI Portal is planned as the featured client for demonstrating to CEOS 

Plenary and GEO the initial CWIC prototype. The LSI Constellation Study Team has indicated that adding the capability of a 

map-based, granule-level search and access capability to the LSI Constellation Portal is the highest priority. Of all of the efforts 

through the years of achieving interoperability among the various agency satellite data inventory and access systems, CWIC has 

the most potential of succeeding given the evolution of international OGC and ISO standards, and the services oriented architecture thrusts of the day.

 For several years, WGISS has discussed whether an interest group should be formed to address data management (data 

stewardship) needs experienced by WGISS members. USGS accepted an action from the previous WGISS meeting to determine 

if enough support is available to form such an interest group. An online survey was conducted for 6 weeks resulting in 13 responses. The results of the survey were presented in Montreal; and after open discussions, the Data Stewardship Interest Group 

was endorsed. The USGS will lead this interest group, which is expected to heavily leverage existing activities. For further 

information, contact Thomas Holm, USGS EROS, holm@usgs.gov.
94 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Coordinating a Successful CEOS WGCV Plenary Meeting

The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) 31st 

plenary meeting was held jointly with the Quality Assurance Framework for Earth Observation (QA4EO) implementation board 

meeting at the Bolger Center in Potomac, Maryland, March 2–5, 2010. The meeting was hosted under the auspices of National 

Institute of Standards and Technology (NIST). The WGCV 32nd plenary meeting was held jointly with the CEOS Working 

Group on Information Systems and Services (WGISS) at the Canadian Space Agency facility in Saint-Hubert September 13–17, 

2010 (fig. 132). The WGCV and WGISS meetings were combined in this instance to provide an integrated CEOS technical 

forum to support Global Earth Observation (GEO) objectives in data quality and availability and to contribute to the CEOS 

Implementation Plan for the GEO space segment. The WGCV agenda, meeting details, seed documents, and minutes from the 

meeting are posted on the WGCV website at http://www.ceos.org/wgcv/. For further information, contact Greg Stensaas, USGS 

EROS, stensaas@usgs.gov.

Coordinating a Successful QA4EO Workshop

A Quality Assurance Framework for Earth Observation (QA4EO) Workshop on Facilitating Implementation to the Group 

on Earth Observations (GEO) community was hosted by the TUBITAK-UZAY (Space Technologies Research Institute) in Antalya, Turkey, September 29–October 1, 2009. The workshop was chaired by the GEO and organized by the Committee on Earth 

Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and Global Space-based Inter-calibration 

System (GSICS). Approximately 35 people attended the workshop, and the program included presentations, general and technical sessions, and a group discussion. The ultimate goal of the workshop was to facilitate implementation of the QA4EO guidelines. These guidelines will become the guiding principles that will be adopted and endorsed by the international community. If 

guidelines such as these are adopted, many difficult issues of traceability and inter-operability will be effectively addressed. The 

QA4EO agenda, meeting details, documents, and minutes from the meeting are posted on the website at http://qa4eo.org/

(fig. 133). A short QA4EO “user” guide has been produced to provide background into QA4EO and how one would start 

implementing it. This user guide is also available from the QA4EO website at http://qa4eo.org/documentation.html. For further 

information, contact Greg Stensaas, USGS EROS, stensaas@usgs.gov.

First Ever GEO Work Plan Symposium

The Department of Science and Technology in South Africa hosted the first-ever Group on Earth Observations (GEO) Work 

Plan Symposium. The Symposium took place May 17–19, 2010, in Pretoria, South Africa, bringing together the Task Leads 

and contributors to the Tasks of the GEO 2009–2011 Work Plan. The main objectives of the Symposium were to (1) foster the 

Work Plan implementation across and within Global Earth Observation System of Systems (GEOSS) areas, (2) develop practical 

recommendations for the 2011 Work Plan update, (3) identify achievements that could be presented at Beijing Ministerial Summit Exhibition, and (4) initiate reflections and discussions in preparation of the GEO 2012–2015 Work Plan. The 3-day symposium was designed around parallel and plenary sessions in order to deliver concrete actions and proposals. These built upon the 

cross-fertilization of tasks and directly contribute to GEOSS implementation on a number of fronts including data sharing and 

registration of data, tools, and services in the GEOSS Common Infrastructure. For further information, contact Greg Stensaas, 

USGS EROS, stensaas@usgs.gov.

Figure 133. Screenshot of QA4EO website 

banner.

Figure 132. The Working Group on Calibration 

and the Validation and Working Group on 

Information Systems and Services participants at 

the Canadian Space Agency, Montreal, Canada.
Remote Sensing Activities 95

USGS Supports CEOS Working Group on Education: Fourth Jay Feuquay Memorial Workshop

The USGS helped organize and participated in the CEOS Working Group on Education (WGEdu), training, and capacity 

building remote sensing workshop “Geotechnologies For Natural Disaster Monitoring in Latin America,” hosted by the Instituto 

Nacional de Pesquisas Espaciais (INPE) of Brazil and held March 2010 in Santa Maria (fig. 134). The 3-day workshop was attended by more than 25 remote sensing practitioners and educators from 10 Latin American countries (fig. 135), who were welcomed on the opening day by Dr. Sergio Camacho Lara, Secretary General of INPE’s CRECTEALC Program and by WGEdu 

Co-Chair, Dr. Tania Maria Sausen (INPE). The workshop was the fourth WGEdu remote sensing workshop held in memory of 

former USGS Land Remote Sensing Program Coordinator, Jay Feuquay, and was enabled by funding support from the USGS. 

For further information, contact Eric Wood, USGS EROS, woodec@usgs.gov.

CEOS Land Surface Imaging Constellation Portal for GEOSS

The Committee on Earth Observation Satellites (CEOS, http://www.ceos.org) is an international group that coordinates 

civil spaceborne observations of the Earth and provides the space component of the Global Earth Observing System of Systems 

(GEOSS, http://www.earthobservations.org/geoss.shtml). The CEOS Virtual Constellations concept was implemented in an 

effort to engage and coordinate disparate Earth observing programs of CEOS member agencies and ultimately facilitate their 

contribution in supplying the space-based observations required to satisfy the requirements of the GEOSS. The CEOS initially 

established study teams for four prototype constellations that included precipitation, land surface imaging, ocean surface topography, and atmospheric composition. The basic mission of the Land Surface Imaging (LSI) Constellation [1] is to promote the 

efficient, effective, and comprehensive collection, distribution, and application of space-acquired image data of the global land 

surface, especially to meet societal needs of the global population, such as those addressed by the nine Group on Earth Observations (GEO) Societal Benefit Areas (SBAs) of agriculture, biodiversity, climate, disasters, ecosystems, energy, health, water, and 

weather. The LSI Constellation Portal is the result of an effort to address important goals within the LSI Constellation mission 

and provide resources to assist in planning for future space missions that might further contribute to meeting those goals. 

The CEOS LSI Constellation Portal for GEOSS was designed and built by the LSI Constellation study team in response 

to input from the community of users of mid-resolution optical remotely sensed land satellite data and with strong support and 

assistance from the CEOS Working Group on Information Systems and Services (WGISS). CEOS agencies participating in 

development of this Portal include Centre National d’Etudes Spatiales (CNES), Comisión Nacional de Actividades Espaciales (CONAE), Instituto Nacional de Pesquisas Espaciais (INPE), Indian Space Research Organisation (ISRO), NASA, Japan 

Aerospace Exploration Agency (JAXA), Geo-Informatics and Space Technology Development Agency (GISTDA), and the U.S. 

Geological Survey (USGS). Currently, the website provides information and links to mid-resolution optical data (fig. 136) that 

are being collected by the aforementioned agencies or have been collected by them for the past 35 years.

Figure 134. Training session during the Fourth 

Jay Feuquay Memorial Workshop, Santa 

Maria, Brazil, 2010.

Figure 135. Participants of the Fourth 

Jay Feuquay Memorial Workshop.
96 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Figure 137. Committee on Earth Observation Satellites Land Surface Imaging Constellation 

Portal web page for additional information about mid-resolution, optical satellites and sensors.

Figure 136. Example browse image that includes the Vancouver, Canada, region, acquired by Landsat 7 

on September 22, 2002.
Remote Sensing Activities 97

The LSI Portal (http://wgiss.ceos.org/lsip/) serves as a single web location for information about current and previous 

mid-resolution optical satellite systems and data. Mid-resolution optical systems are those that acquire reflected and/or emitted 

electromagnetic radiation in the visible, shortwave infrared, and thermal infrared (VNIR, SWIR, and TIR) wavelengths with 

spatial resolutions nominally between 10 meters and 100 meters. The Portal provides users with (1) basic information about the 

mid-resolution, optical LSI satellites and sensors (fig. 137), (2) information helpful for applications of the data, and 3) active 

links to data search and order tools for CEOS agencies that offer open user access to mid-resolution, optical satellite data (fig. 

138). For further information, contact Thomas Holm, USGS EROS, holm@usgs.gov.

Coordination of Space Data Acquisition in Support of GEO Forest Carbon Tracking

The Group on Earth Observation (GEO) established the Forest Carton Tracking (FCT) task in 2008 to provide operational 

support to countries wishing to establish a national system for forest monitoring and carbon reporting (http://www.geo-fct.org). 

The task follows the guidelines set out by the United Nations Framework Convention on Climate Change (UNFCCC) and it 

seeks to provide the technical capability 

and continuity to support the monitoring, 

reporting, and verification information 

required by future regulatory frameworks 

for the inclusion of forests in post-Kyoto 

climate agreements through global, annual, medium resolution wall-to-wall 

national-scale coverage of the world’s 

forests. 

The GEO FCT task dependence on 

Earth Observation (EO) data makes the 

Committee on Earth Observation SatelFigure 138. National Institute for Space Research (INPE) web page linked from Committee on Earth Observation 

Satellites Land Surface Imaging Constellation Portal web page for additional information about mid-resolution, 

optical satellites and sensors.

Figure 139. Group on Earth Observation 

established the Forest Carton Tracking 

national demonstrators.
98 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

lites (CEOS) and member agencies’ support vital. CEOS coordinates civil spaceborne observations of the Earth to enhance 

international coordination and data exchange to optimize societal benefits (http://www.ceos.org/). CEOS space agencies agreed 

to implement a coordinated satellite data acquisition strategy from 2009 onward including both optical and SAR sensors within 

key areas of interest in support of the GEO FCT task. 

In 2009, the GEO FCT task required an initial CEOS coordination effort for a number of “National Demonstrator” (ND) 

activities. The ND represents countries or large areas in the Americas, Africa, Asia, and Oceania with tropical forests. The ND 

included were Brazil (several regions), Guyana and Mexico (the forest main region), Cameroon and Tanzania, Borneo Island, 

and Tasmania Island (blue outlined countries/regions, fig. 139). In mid-2010, the areas were expanded with Peru, Columbia, 

Democratic Republic of Congo, and Sumatra Island (red outline countries/regions, fig. 139). For further information, contact 

Thomas Holm, USGS EROS, holm@usgs.gov.

GEO Forest Carbon Tracking Science and Data Summit and Space Data Coordination Meeting

The Woods Hole Research Center (WHRC) and the USGS hosted a Science and Data Summit and a Space Data Coordination Meeting of the Group on Earth Observations Forest Carbon Tracking Task (GEO FCT) on May 11–14, 2010, at WHRC 

in Falmouth, Massachusetts (fig. 140). The purpose of the meeting was to (1) report on the progress of the GEO FCT Product 

Development Teams on their prototype product development activities for the National Demonstrator countries (Mexico, Guyana, Brazil, Cameroon, Tanzania, Borneo, and Tasmania); (2) produce a clear statement of what data and results will be provided 

ahead of the GEO Beijing Ministerial Summit scheduled for November 5, 2010; (3) further the development of methodological 

processing standards; and (4) develop recommendations to the Committee on Earth Observation Satellites (CEOS) Space Agencies for 2010 satellite data (optical and synthetic aperture radar (SAR)) acquisition requirements for the forthcoming coordinated 

FCT acquisition campaigns. For further information, contact Thomas Holm, USGS EROS, holm@usgs.gov.

UNEP 3D Tours and Videos

The Team at UNEP GRID located at EROS in Sioux Falls produced videos with the intent of communicating examples 

of environmental changes from around the world to the public. They have been made available to view at http://www.youtube.

com, reaching around 2 million people. Short tours using Google Maps were also produced by the team with the same intention. These 3-D tours are available at Google Earth under the UNEP Layer in Global Awareness to more than 700 million users 

of Google Earth, and these videos have been widely used in education institutions to raise awareness of environmental changes. 

Statistics show that these videos have become popular among YouTube viewers in this short span of time (table 3). For further 

information, contact Charles Trautwein, USGS EROS, trautwein@usgs.gov.

Table 3. UNEP 3-D environmental change videos and YouTube viewer statistics.

[UNEP, United Nations Environment Programme]

UNEP 3-D environmental change video Number of views

Aral Sea: UNEP & Google Earth highlights environmental change 1,799,659 views

UNEP - Amazon Deforestation in Google Earth 913,112 views

Lake Chad: UNEP & Google Earth highlights environmental change 349,349 views

Shenzhen, China: UNEP & Google Earth highlights environmental change 241,798 views

UNEP - Mt. Kilimanjaro in Google Earth 130,947 views

Figure 140. Participants at Group on Earth 

Observation established the Forest Carton 

Tracking meetings in Woods Hole Research 

Center.
Remote Sensing Activities 99

Center Support Activities

Center support at the USGS EROS provides a wide range of services for numerous and highly complex science, engineering, and operational projects, diverse contracts, intricate partner and customer relationships, and national and international activities. Center support functions are located within the internal organizational units of the Center Director’s Office, Administrative Services Branch, Data Management Branch, and the Project Management Team. The FY 2010 accomplishments highlighted 

include achievements related to communication and outreach, implementing the Financial Business Management System, 

partnering, student and volunteer programs, facility updates, and contract management.

Communications and Outreach Project

The Communications and Outreach (C&O) Project at the USGS EROS Center successfully developed and launched two 

new websites, a search tool for publications, and a third collection of the Earth As Art imagery in FY 2010. These are among 

the numerous accomplishments of C&O as they worked diligently to present, promote, and highlight USGS science and remote 

sensing research locally and nationwide. 

The beginning of the fiscal year brought an addition to the walls of EROS as a 12’ x 7.9’ display of the United States and 

an 8’ x 7.9’ display of Alaska were hung outside of the training rooms. EROS C&O designed the displays for the National Land 

Cover Dataset (NLCD) project (fig. 141). Each display features several 2.1’ X 1.7’ pop-outs highlighting the data within the 

displays. A large display measuring 15.5’ x 4’ was created for the Sioux Falls, SD, airport. The display entitled “Fell Asleep on 

the Flight?” highlighted satellite and high-resolution orthoimagery of landscape as they could be seen through the windows of an 

airplane (fig. 142).

A major achievement was the addition of a third collection to the Earth As Art series. C&O brought out the intricate features displayed in the 40 Landsat images showing fresh and inspiring glimpses of different parts of our planet’s complex surface. 

The collection includes an eye-catching booklet, two traveling displays of 26’ x 28’ canvas images, and user access to download 

the imagery at no cost from the EROS Image Gallery located on the EROS external website (fig. 143).

FY 2010 also saw the growth of information sharing through the release of the new internal Bulletin Board System, the 

new EROS internal website, and the EROS Publication Search Tool. The new Bulletin Board System added numerous features, 

including easier usability and reliable email notifications in response to updates on forums, discussions, and other information. 

Figure 141. Communications and 

Outreach designed the National Land 

Cover Dataset 2001 display, which 

now hangs outside the training rooms 

at EROS.

Figure 142. The new display at Sioux Falls Regional Airport shows satellite and high-resolution orthoimagery.
100 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Figure 144. Screenshot of new internal home page.

Figure 143. Example from the Earth As Art 3 image gallery.
Remote Sensing Activities 101

The new EROS internal web (fig. 144) provides a consistent, professional look throughout the entire website while allowing 

shareholders access to adding, updating, and linking information to their specific areas. The website consists of three main access points: information shared throughout the Center; information for Government use only; and information for Contractor use 

only. Although it is not necessary to login to view any shared information, an advanced login system is available when needed 

that recognizes each staff members’ affiliation and permits access to the appropriate Government or Contractor pages. The development and release of the new Publication Search tool answered a need to have access to the publications of EROS authors. 

The archive supporting the search tool took approximately two years to build and includes publications dating from 1973 to the 

present.

C&O coordinated EROS staff participation in seven Bureau-sponsored conferences around the Nation: the Geological 

Society of America (GSA) Annual Meeting, the American Geophysical Union (AGU) Fall Meeting, the Association of American 

Geographers (AAG) Annual Meeting, the American Society for Photogrammetry and Remote Sensing (ASPRS) Annual Conference, the ESRI International User Conference, the International Geoscience and Remote Sensing Symposium (IGARSS), and 

the National Science Teacher Association (NSTA) National Conference. EROS support included designing exhibit backdrops, 

staffing, supplying handouts that highlight EROS science and activities; and individual demonstrations to participants on how to 

search for and download web-enabled imagery through EarthExplorer and GloVis.

Figure 145. Left to right – South Dakota State University 

President, David Chicoine; Acting EROS Director, Leslie 

Armstrong; SD Senator, Tim Johnson; and USGS Director, 

Marcia McNutt. Photo taken during visit to EROS on 

September 1st.

Figure 146. Image of the Week poster 

depicting the shrinking of the Aral Sea 

as revealed by Landsat imagery.
102 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Closer to home, C&O provided logistic support for a September 1st visit to EROS by USGS Director Marcia McNutt and 

South Dakota Senator Tim Johnson. In conjunction with the visit, Director McNutt and Senator Johnson visited South Dakota 

State University (SDSU) to review collaborative activities between the USGS and SDSU. Following the visit to SDSU, Director McNutt, Senator Johnson, and SDSU President, David Chicoine, toured EROS and reviewed numerous EROS science and 

operations activities (fig. 145).

In addition, C&O coordinated staff participation in nine local or regional conferences and expos: the South Dakota Space 

Grant Consortium’s (SDSGC) Annual Space Days, the American Society for Photogrammetry and Remote Sensing (ASPRS) 

Fall and Annual Conferences, the International Geoscience and Remote Sensing Symposium (IGARSS), the Sioux Falls Women 

In Science Conference, the South Dakota State University Annual Geography Convention, the Western South Dakota Hydrology 

Conference, the Visitor Expo at Ellsworth Air Force Base in South Dakota, and the Annual Neutrino Science Days Expo.

C&O also developed graphics in support of USGS Headquarters’ work involving the Gulf Oil Spill crisis (fig. 147). Additional support was provided in the development of Image of the Week posters (fig. 146), current event posters, conference 

posters and backdrops, and publications.

For further information contact, Jan Nelson, USGS EROS, jsnelson@usgs.gov.

Preparing for the Financial Business Management System Implementation

Fiscal year 2010 was a year of change preparation for the EROS Administrative Service Branch (ASB). ASB, in conjunction with the USGS Financial Business Management System (FBMS) Team, will implement FBMS to provide standardization 

and integration of business processes across DOI. The ASB Financial Management Team will be the primary users of FBMS 

and will strive to provide a fully integrated business management system in support of projects and common service activities at 

EROS. For further information, contact Jane Strand, USGS EROS, strand@usgs.gov.

Partnering

In today’s global world, partnerships are key to achieving long-term, high-quality customer service and innovation. One 

avenue for pursuing partnerships is through formal agreements. EROS typically establishes and updates 60 to 100 agreements 

each fiscal year. These agreements establish cooperative partnerships with other countries; domestic and international corporations; internal DOI programs and activities; other Federal, State, county, city organizations; universities, and tribal governments. 

Examples include:

Figure 147. C&O developed posters of the Gulf Oil Spill to show the public how satellite imagery was helping responders 

assess the crisis.
Remote Sensing Activities 103

• International entities: Landsat agreements with China, Australia, Brazil, Mexico, and Russia; (Department of Natural 

Resources, Canada), Chinese Academy of Science 

• Other Federal Agencies: NASA, DOD (NGB, USAF), USDA, EPA, USFWS, USAID, NIH

• Native America Tribes: Montana-Wyoming Tribal Leaders Council, United Sioux Tribes of South Dakota

For further information, contact Doug Spelhaug, USGS EROS, spelhaug@usgs.gov.

Student and Volunteer Programs

In support of Secretary Salazar’s Youth Initiative, EROS has been proactive and committed in hiring students to temporarily support all areas of the organization. These positions, which included administrative, computer, scientific, and engineering 

oriented students, have increased creativity and innovation in the workplace. Students bring fresh perspectives and ideas to 

EROS. Additionally, the Youth Initiative has provided EROS the opportunity to form more collaborative, long-term relationships with the universities the students attend. Along with the increase in student hires this fiscal year (2010), we have also seen 

a significant interest and increase in the Volunteers for Science Program by high school students, college students, and retired 

individuals. For more information, contact Krislyn Constant, USGS EROS, kconstant@usgs.gov.

Facility Updates

Award of ARRA Projects. EROS benefited from approximately $836,000 in American Recovery and Reinvestment Act 

(ARRA) funding this year and is currently pursuing another $887,000 in projects. The Facility Manager coordinated with USGS 

headquarters to fund a number of items from the USGS Deferred Maintenance List using ARRA monies. Projects included replacing a boiler, recoating the water tower, replacing the roof, designing an HVAC system, upgrading the security access booth, 

and repairing numerous roads. 

Award of Operations and Maintenance (O&M) Contract. As a large USGS-owned facility, EROS requires approximately 12,000 Preventative Maintenance actions and an additional 3,600 work orders to be performed each year to keep the Center in 

working order. In support of these requirements, an O&M contract is awarded every five years. The contract was recompeted in 

FY10, with the award going to DKC Enterprises of Houston, TX, starting on June 1, 2010. 

USGS Facilities Cost Modeling. The USGS Facilities uses cost models to estimate budgets for utilities, facilities staff, and 

maintenance costs based on the square footage of like buildings. For example, the goal of a cost model is to predict how much it 

costs to run similar types of buildings, such as office buildings, laboratories, warehouses. Local staff reviewed the Headquarters’ 

cost model and identified areas of concern and suggested factors and data to make the model more accurately project real operating costs. This process is ongoing and further refinements are planned to better align costs for the EROS Mundt Federal Building 

Model.

EROS National Environmental Policy Act (NEPA) Simplified Contract. Under the NEPA, EROS must ensure no sites 

of historical significance (for example, churches or tribal grounds) are disturbed as a result of any construction activities. This 

requires that an archaeological review be completed. These reviews can include comprehensive files research and intensive 

pedestrian surveys. Frequently, issuing contracts for these services can be time consuming and expensive. Facilities identified a 

method to more quickly and cost effectively contract for these services. This information was shared with other USGS Regions. 

For additional information, contact Bruce Potter, USGS EROS, bpotter@usgs.gov.

Support Service Contracts at the USGS EROS

In 2008, the Technical Support Services Contract (TSSC) and the Landsat Data Continuity Contract (LDCC) were awarded 

under separate contracts. A decision was made to recompete these two contracts as one TSSC contract, based on two significant 

factors. First, the launch date for Landsat 8 slipped to December 2012. The LDCC was scheduled to end March 2012, which 

would have occurred at a critical point before launch, and the TSSC was scheduled to end March 2013, which would have occurred at a critical postlaunch system checkout phase. The second factor pertained to the modified programmatic direction of the 

LDCM ground system. The new approach, involving augmentation to the existing Landsat ground system, could be performed 

more efficiently and for less cost under the new acquisition strategy aligned with the revised launch schedule. The new TSSC 

was awarded to SGT, Inc. on June 1, 2010, with a contract start date of August 1, 2010. It is an Indefinite Delivery Indefinite 

Quantity (IDIQ) Task Order contract.

SGT successfully completed Option Year 1 of the Technical Support Services Contract on March 31, 2010. Because of 

delays in awarding the new TSSC, the contract was extended through July 31, 2010. The TSSC’s approximately 350 employees 
104 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

provided extensive and varied support critical to USGS EROS missions and responsibilities in science, research, remote sensing, 

and geographic data and information operations projects. Since this is a performance-based, cost-reimbursement contract, USGS 

EROS provided quarterly performance evaluations to SGT. The evaluations were based on six performance criteria used to measure TSSC’s performance throughout the quarter.

On March 31, 2008, USGS awarded a new Scientific Support Services Contract to Arctic Slope Regional Corporation 

(ASRC) Research and Technology Solutions (ARTS). ARTS successfully completed the first year of the contract, and Option 

Year 2 was exercised on March 31, 2010. ARTS’ 26 employees provided comprehensive support and expertise in advanced and 

specialized scientific research critical to assisting the USGS EROS in fulfilling its science mission nationally and internationally. 

For further information, contact Joy Hood, USGS EROS, jhood@usgs.gov.

Selected Research and Technical Publications

The work cited was published in FY 2010. Names in bold type are affiliated with EROS. Online addresses are provided 

where available. If a problem or an error is experienced while attempting to access an address, you may need to copy and paste 

that address into your web browser for access.

Journal Articles

Albright, T.P., Anderson, D.P., Keuler, N.S., Pearson, S.M., and Turner, M.G., 2009, The spatial legacy of introduction—Celastrus orbiculatus in the southern Appalachians, USA: Journal of Applied Ecology, v. 46, no. 6, p. 1,229–1,238. (Also available 

online at http://dx.doi.org/10.1111/j.1365-2664.2009.01707.x).

Albright, T.P., Chen, H., Chen, L., and Guo, Q., 2010, The ecological niche and reciprocal prediction of the disjunct distribution of an invasive species—the example of Ailanthus altissima: Biological Invasions, v. 12, no. 8, p. 2,413–2,427. (Also 

available online at http://dx.doi.org/10.1007/s10530-009-9652-8).

Angal, A., Xiong, X., Choi, T. Y., Chander, G., and Wu, A., 2010, Using the Sonoran and Libyan Desert test sites to monitor 

the temporal stability of reflective solar bands for Landsat 7 Enhanced Thematic Mapper Plus and Terra moderate resolution 

imaging spectroradiometer sensors: Journal of Applied Remote Sensing, v. 4, no. 1, citation identifier 043525, available only 

online at http://dx.doi.org/10.1117/1.3424910.

Balogun, A., Adegoke, J., Vezhapparambu, S., Mauder, M., McFadden, J., and Gallo, K.P., 2009, Surface energy balance measurements above an exurban residential neighbourhood of Kansas City, Missouri: Boundary-Layer Meteorology, v. 133, no. 3, 

p. 299–321. (Also available online at http://dx.doi.org/10.1007/s10546-009-9421-3).

Barlow, J., Silveira, J.M., and Cochrane, M.A., 2010, Fire scars on amazonian trees—exploring the cryptic fire history 

of the Ilha de Maracá: Biotropica, v. 42, no. 4, p. 405–409. (Also available online at http://dx.doi.org/10.1111/j.1744-

7429.2010.00646.x.

Bergen, K.M., Goetz, S.J., Dubayah, R.O., Henebry, G.M., Hunsaker, C.T., Imhoff, M.L., Nelson, R.F., Parker, G.G., and Radeloff, V.C., 2009, Remote sensing of vegetation 3-D structure for biodiversity and habitat—review and implications for lidar 

and radar spaceborne missions: Journal of Geophysical Research–Biogeosciences, v. 114, citation number G00E06. (Also 

available online at http://dx.doi.org/10.1029/2008JG000883).

Bliss, N.B., and Maursetter, J., 2010, Soil organic carbon stocks in Alaska estimated with spatial and pedon data: Soil Science 

Society of America Journal, v. 74, no. 2, p. 565–579. (Also available online at http://dx.doi.org/10.2136/sssaj2008.0404).

Boschetti, L., Roy, D.P., Justice, C.O., and Giglio, L., 2010, Global assessment of the temporal reporting accuracy and precision 

of the MODIS burned area product: International Journal of Wildland Fire, v. 19, no. 6, p. 705–709. (Also available online at 

http://dx.doi.org/10.1071/WF09138).

Broich, M., Stehman, S.V., Hansen, M.C., Potapov, P., and Shimabukuro, Y.E., 2009, A comparison of sampling designs for 

estimating deforestation from Landsat imagery—a case study of the Brazilian Legal Amazon: Remote Sensing of Environment, v. 113, no. 11, p. 2,448–2,454. (Also available online at http://dx.doi.org/10.1016/j.rse.2009.07.011).
Selected Research and Technical Publications 105

Bruins, R.J.F., Muins Jr., W.R., Botti, S.J., Brink, S., Cleland, D., Kapustka, L., Lee, D., Luzadis, V., McCarthy, L.F., Rana, N., 

Rideout, D.B., Rollins, M.G., Woodbury, P., and Zupko, M., 2010, A new process for organizing assessments of social, economic, and environmental outcomes—case study of wildland fire management in the USA: Integrated Environmental Assessment and Management, v. 6, no. 3, p. 469–483. (Also available online at http://dx.doi.org/10.1897/IEAM_2009-075.1).

Budde, M.E., Rowland, J.D., and Funk, C.C., 2010, Agriculture and food availability—remote sensing of agriculture for food 

security monitoring in the developing world: EarthZine, v. 2, no. 2, available only online at http://www.earthzine.org/.

Bwangoy, J.R.B., Hansen, M.C., Roy, D.P., Grandi, G.D., and Justice, C.O., 2010, Wetland mapping in the Congo Basin using 

optical and radar remotely sensed data and derived topographical indices: Remote Sensing of Environment, v. 114, no. 1, 

p. 73–86. (Also available online at http://dx.doi.org/10.1016/j.rse.2009.08.004).

Chander, G., Huang, C., Yang, L., Homer, C.G., and Larson, C., 2009, Developing consistent Landsat data sets for large area 

applications–the MRLC 2001 Protocol: IEEE Geoscience and Remote Sensing Letters, v. 6, no. 4, p. 777–81. (Also available 

online at http://dx.doi.org/10.1109/LGRS.2009.2025244).

Chander, G., Xiong, X., Choi, T., and Angal, A., 2010, Monitoring on-orbit calibration stability of the Terra MODIS and 

Landsat 7 ETM+ sensors using pseudo-invariant test sites: Remote Sensing of Environment, v. 114, no. 4, p. 925–939. (Also 

available online at http://dx.doi.org/10.1016/j.rse.2009.12.003).

Chen, W., and Henebry, G.M., 2009, Change of spatial information under rescaling—a case study using multi-resolution image 

series: ISPRS Journal of Photogrammetry and Remote Sensing, v. 64, no. 6, p. 592–597. (Also available online at http://

dx.doi.org/10.1016/j.isprsjprs.2009.05.002).

Chen, W., and Henebry, G.M., 2010, Spatio-spectral heterogeneity analysis using EO-1 Hyperion imagery: Computers and 

Geosciences, v. 36, no. 2, p. 167–170. (Also available online at http://dx.doi.org/10.1016/j.cageo.2009.05.005).

de Beurs, K.M., and Henebry, G.M., 2010, A land surface phenology assessment of the northern polar regions using MODIS 

reflectance time series: Canadian Journal of Remote Sensing, v. 36, no. Suppl. S1, p. S87–S110. (Also available online at 

http://pubservices.nrc-cnrc.ca/rp-ps/inDetail.jsp?jcode=cjrs&lang=eng&vol=36&is=S1).

de Beurs, K.M., Wright, C.K., and Henebry, G.M., 2009, Dual scale trend analysis for evaluating climatic and anthropogenic 

effects on the vegetated land surface in Russia and Kazakhstan: Environmental Research Letters, v. 4, no. 4, article number 

045012, available only online at http://dx.doi.org/10.1088/1748-9326/4/4/045012.

DeFries, R.S., Rudel, T., Uriarte, M., and Hansen, M., 2010, Deforestation driven by urban population growth and agricultural 

trade in the twenty-first century: Nature Geoscience, v. 3, no. 3, p. 178–181, available only online at http://dx.doi.org/10.1038/

ngeo756.

Drummond, M.A., and Loveland, T.R., 2010, Land-use pressure and a transition to forest-cover loss in the Eastern United 

States: BioScience, v. 60, no. 4, p. 286-298. (Also available online at http://www.bioone.org/doi/abs/10.1525/bio.2010.60.4.7).

Faundeen, J.L., 2010, Appraising U.S. Geological Survey science records: Archival Issues, v. 32, no. 1, p. 7–22.

Fosnight, E.A., 2009, Earth imagery for the masses–TerraLook delivers free satellite imagery for monitoring change: Earth 

Imaging Journal, v. 4, no. 5, p. 32–36. (Also available online at http://www.eijournal.com/Featured_Articles_directory.

asp?cattypeid=7).

Franks, S., Masek, J.G., Headley, R.M., Gasch, J., and Arvidson, T., 2009, Large area scene selection interface (Lassi)–methodology of selecting Landsat imagery for the Global Land Survey 2005: Photogrammetric Engineering and Remote Sensing, v. 

75, no. 11, p. 1,287–1,296. (Also available online at http://www.asprs.org/publications/pers/).

Gesch, D.B., 2009, Analysis of lidar elevation data for improved identification and delineation of lands vulnerable to sea level 

rise: Journal of Coastal Research, v. 53, no. SI, p. 49–58. (Also available online at http://dx.doi.org/10.2112/SI53-006.1).

Grovenburg, T.W., Jacques, C.N., Klaver, R.W., and Jenks, J.A., 2010, Bed site selection by neonate deer in grassland habitats 

on the Northern Great Plains: Journal of Wildlife Management, v. 74, no. 6, p. 1,250–1,256. (Also available online at http://

dx.doi.org/10.2193/2009-399).
106 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Grovenburg, T.W., Jenks, J.A., Jacques, C.H., Klaver, R.W., and Swanson, C.C., 2009, Aggressive defensive behavior by 

free-ranging white-tailed deer: Journal of Mammalogy, v. 90, no. 5, p. 1,218–1,223. (Also available online at http://dx.doi.

org/10.1644/08-MAMM-A-360.1).

Grovenburg, T.W., Jenks, J.A., Klaver, R.W., Swanson, C.C., Jacques, C.N., and Todey, D., 2009, Seasonal movements and 

home ranges of white-tailed deer in north-central South Dakota: Canadian Journal of Zoology, v. 87, no. 10, p. 876–885. 

(Also available online at http://dx.doi.org/10.1139/Z09-076).

Gu, Y., Brown, J.F., Miura, T., van Leeuwen, W.J., and Reed, B., 2010, Phenological classification of the United States—a geographic framework for extending multi-sensor time-series data: Remote Sensing, v. 2, no. 2, p. 526–544, available only online 

at http://dx.doi.org/10.3390/rs2020526.

Gu, Y., and Wylie, B.K., 2010, Detecting ecosystem performance anomalies for land management in the Upper Colorado River 

Basin using satellite observations, climate data, and ecosystem models: Remote Sensing, v. 2, no. 8, p. 1,880–1,891, available 

only online at http://dx.doi.org/10.3390/rs2081880.

Hansen, M.C., Stehman, S.V., and Potapov, P.V., 2010, Quantification of global gross forest cover loss: Proceedings of 

the National Academy of Sciences, v. 107, no. 19, p. 8,650–8,655. (Also available online at http://dx.doi.org/10.1073/

pnas.0912668107).

Henebry, G.M., and Betancourt, J.L., 2010, Toward a U.S. national phenological assessment: Eos, Transactions, American Geophysical Union, v. 91, no. 1, p. 3. (Also available online at http://dx.doi.org/10.1029/2010EO010003).

Holm, T.M., Gallo, K.P., and Bailey, G.B., 2010, The CEOS-Land Surface Imaging Constellation Portal for GEOSS—a 

resource for land surface imaging system information and data access: Earthzine, available only online at http://www.earthzine.org/.

Houet, T., Loveland, T.R., Hubert-Moy, L., Gaucherel, C., Napton, D.E., Barnes, C.A., and Sayler, K.L., 2010, Exploring subtle land use and land cover changes—a framework for future landscape studies: Landscape Ecology, v. 25, no. 2, p. 249–266. 

(Also available online at http://dx.doi.org/10.1007/s10980-009-9362-8).

Houet, T., Verburg, P.H., and Loveland, T.R., 2010, Preface -- Monitoring and modelling landscape dynamics: Landscape Ecology, v. 25, no. 2, p. 163–167. (Also available online at http://dx.doi.org/10.1007/s10980-009-9417-x).

Huang, C., Goward, S.N., Masek, J.G., Thomas, N., Zhu, Z., and Vogelmann, J.E., 2010, An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks: Remote Sensing of Environment, v. 114, 

no. 1, p. 183–198. (Also available online at http://dx.doi.org/10.1016/j.rse.2009.08.017).

Ji, L., Wylie, B.K., Ramachandran, B., and Jenkerson, C.B., 2010, A comparative analysis of three different MODIS NDVI 

data sets for Alaska and adjacent Canada: Canadian Journal of Remote Sensing, v. 36, no. Suppl. 1, p. S149–S167. (Also 

available online at http://pubs.nrc-cnrc.gc.ca/cjrs/cjrs.html).

Ji, L., Zhang, L., and Wylie, B.K., 2009, Analysis of dynamic thresholds for the normalized difference water index: Photogrammetric Engineering & Remote Sensing, v. 75, no. 11, p. 1,307–1,317. (Also available online at http://www.asprs.org/publications/pers/).

Ju, J., Roy, D.P., Shuai, Y., and Schaaf, C., 2010, Development of an approach for generation of temporally complete daily 

nadir MODIS reflectance time series: Remote Sensing of Environment, v. 114, no. 1, p. 1–20. (Also available online at http://

dx.doi.org/10.1016/j.rse.2009.05.022).

Kovalskyy, V., and Henebry, G.M., 2009, Change and persistence in land surface phenologies of the Don and Dnieper 

river basins: Environmental Research Letters, v. 4, no. 4, article number 045018, available only online at http://dx.doi.

org/10.1088/1748-9326/4/4/045018.

Lannoo, M., Kinney, V., Heemeyer, J., Engbrecht, N., Gallant, A.L., and Klaver, R.W., 2009, Mine spoil prairies expand critical habitat for endangered and threatened amphibian and reptile species: Diversity, v. 1, no. 2, p. 118–132, available only 

online at http://dx.doi.org/10.3390/d1020118.

Lin, W., Wang, B., Li, J., Wang, X., Zeng, L., Yang, L., and Lin, H., 2010, The impact of urbanization on the monthly averaged 

diurnal cycle in October 2004 in the Pearl River Delta region: Atmosfera, v. 23, no. 1, p. 37–51. (Also available online at 

http://www.scielo.org.mx/scielo.php?script=sci_issuetoc&pid=0187-623620100001&lng=en&nrm=iso).
Selected Research and Technical Publications 107

Lioubimtseva, E., and Henebry, G.M., 2009, Climate and environmental change in arid Central Asia—impacts, vulnerability, 

and adaptations: Journal of Arid Environments, v. 73, no. 11, p. 963–977. (Also available online at http://dx.doi.org/10.1016/j.

jaridenv.2009.04.022).

Lu, Z., and Dzurisin, D., 2010, Ground surface deformation patterns, magma supply, and magma storage at Okmok volcano, 

Alaska, from InSAR analysis—2. Coeruptive deflation, July-August 2008: Journal of Geophysical Research B—Solid Earth, 

v. 115, citation number B00B03. (Also available online at http://dx.doi.org/10.1029/2009jb006970).

Lu, Z., Dzurisin, D., Biggs, J., Wicks Jr., C., and McNutt, S., 2010, Ground surface deformation patterns, magma supply, 

and magma storage at Okmok volcano, Alaska, from InSAR analysis—1. Intereruption deformation, 1997–2008: Journal of Geophysical Research B—Solid Earth, v. 115, citation number B00B02. (Also available online at http://dx.doi.

org/10.1029/2009jb006969).

Lu, Z., Dzurisin, D., Jung, H.-S., Zhang, J., and Zhang, Y., 2010, Radar image and data fusion for natural hazards characterisation: International Journal of Image and Data Fusion, v. 1, no. 3, p. 217–242. (Also available online at http://www.informaworld.com/10.1080/19479832.2010.499219).

Lu, Z., and Wicks, C., 2010, Characterizing 6 August 2007 Crandall Canyon mine collapse from ALOS PALSAR 

InSAR: Geomatics, Natural Hazards and Risk, v. 1, no. 1, p. 85–93. (Also available online at http://www.informaworld.

com/10.1080/19475701003648077).

Lu, Z., Zhang, J., Zhang, Y., and Dzurisin, D., 2010, Monitoring and characterizing natural hazards with satellite InSAR imagery: Annals of GIS, v. 16, no. 1, p. 55–66. (Also available online at http://prod.informaworld.

com/10.1080/19475681003700914).

Maxwell, S.K., Meliker, J.R., and Goovaerts, P., 2010, Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research: Journal of Exposure Science and Environmental Epidemiology, v. 20, 

no. 2, p. 176–185. (Also available online at http://dx.doi.org/10.1038/jes.2009.7).

Melesse, A.M., Loukas, A.G., Senay, G.B., and Yitayew, M., 2009, Preface–Climate change, land-cover dynamics and ecohydrology of the Nile River Basin: Hydrological Processes, v. 23, no. 26, p. 3,651–3,652. (Also available online at http://dx.doi.

org/10.1002/hyp.7522).

Michimi, A., and Wimberly, M.C., 2010, Spatial patterns of obesity and associated risk factors in the conterminous U.S.: 

American Journal of Preventive Medicine, v. 39, no. 2, p. e1–e12. (Also available online at http://dx.doi.org/10.1016/j.

amepre.2010.04.008).

Napton, D.E., Auch, R.F., Headley, R.M., and Taylor, J.L., 2010, Land changes and their driving forces in the southeastern 

United States: Regional Environmental Change, v. 10, no. 1, p. 37–53. (Also available online at http://dx.doi.org/10.1007/

s10113-009-0084-x).

Numata, I., Cochrane, M.A., Roberts, D.A., Soares, J.V., Souza, C.M., Jr., and Sales, M.H., 2010, Biomass collapse and carbon 

emissions from forest fragmentation in the Brazilian Amazon: Journal of Geophysical Research—Biogeosciences, v. 115, 

no. G3, citation number G03027. (Also available online at http://dx.doi.org/10.1029/2009JG001198).

Pierce Jr., K.B., Ohmann, J.L., Wimberly, M.C., Gregory, M.J., and Fried, J.S., 2009, Mapping wildland fuels and forest 

structure for land management—a comparison of nearest neighbor imputation and other methods: Canadian Journal of Forest 

Research, v. 39, no. 10, p. 1,901–1,916. (Also available online at http://dx.doi.org/10.1139/X09-102).

Pijanowski, B.C., Iverson, L.R., Drew, C.A., Bulley, H.N.N., Rhemtulla, J.M., Wimberly, M.C., Bartsch, A., and Peng, J., 2010, 

Addressing the interplay of poverty and the ecology of landscapes: A Grand Challenge Topic for landscape ecologists?: Landscape Ecology, v. 25, no. 1, p. 5–16. (Also available online at http://dx.doi.org/10.1007/s10980-009-9415-z).

Rover, J.A., Wylie, B.K., and Ji, L., 2010, A self-trained classification technique for producing 30-m percent-water maps from 

Landsat data: International Journal of Remote Sensing, v. 31, no. 8, p. 2,197–2,203. (Also available online at http://www.

informaworld.com/10.1080/01431161003667455).

Roy, D.P., Boschetti, L., Maier, S.W., and Smith, A.M.S., 2010, Field estimation of ash and char colour-lightness using a 

standard grey scale: International Journal of Wildland Fire, v. 19, no. 6, p. 698–704. (Also available online at http://dx.doi.

org/10.1071/WF09133).
108 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Roy, D.P., Ju, J., Kline, K.L., Scaramuzza, P.L., Kovalskyy, V., Hansen, M., Loveland, T.R., Vermote, E., and Zhang, C.,

2010, Web-enabled Landsat Data (WELD)–Landsat ETM+ composited mosaics of the conterminous United States: Remote 

Sensing of Environment, v. 114, no. 1, p. 35–49. (Also available online at http://dx.doi.org/10.1016/j.rse.2009.08.011).

Roy, D.P., Ju, J., Mbow, C., Frost, P., and Loveland, T.R., 2010, Accessing free Landsat data via the Internet—Africa’s challenge: Remote Sensing Letters, v. 1, no. 2, p. 111–117. (Also available online at http://www.informaworld.

com/10.1080/01431160903486693).

Senay, G.B., Asante, K., and Artan, G., 2009, Water balance dynamics in the Nile Basin: Hydrological Processes, v. 23, no. 26, 

p. 3,675–3,681. (Also available online at http://dx.doi.org/10.1002/hyp.7364).

Sohl, T.L., Loveland, T.R., Sleeter, B.M., Sayler, K.L., and Barnes, C.A., 2010, Addressing foundational elements of regional 

land-use change forecasting: Landscape Ecology, v. 25, no. 2, p. 233–247. (Also available online at http://dx.doi.org/10.1007/

s10980-009-9391-3).

Spindler, B.D., Chipps, S.R., Klumb, R.A., and Wimberly, M.C., 2009, Spatial analysis of pallid sturgeon Scaphirhynchus albus 

distribution in the Missouri River, South Dakota: Journal of Applied Ichthyology, v. 25, no. Suppl. 2, p. 8–13. (Also available 

online at http://dx.doi.org/10.1111/j.1439-0426.2009.01283.x).

Stohlgren, T.J., Jarnevich, C.S., and Giri, C.P., 2010, Modeling the human invader in the United States: Journal of Applied 

Remote Sensing, v. 4, no. 1, citation number 043509, available only online at http://dx.doi.org/10.1117/1.3357386.

Stoker, J.M., 2010, Making Lidar more photogenic—creating band combinations from Lidar information: Photogrammetric 

Engineering and Remote Sensing, v. 76, no. 3, p. 216–220. (Also available online at http://www.asprs.org/publications/

pers/2010jour.html).

Stoker, J.M., Tyler, D.J., Turnipseed, D.P., Van Wilson, K., and Oimoen, M.J., 2009, Integrating disparate Lidar datasets for a 

regional storm tide inundation analysis of Hurricane Katrina: Journal of Coastal Research, v. 53, no. SI, p. 66–72. (Also available online at http://dx.doi.org/10.2112/SI53-008.1).

Stryker, T. and Jones, B.K., 2009, Disaster response and the International Charter Program: Photogrammetric Engineering and 

Remote Sensing, v. 75, no. 12, p. 1,342–1,344. (Also available online at http://www.asprs.org/publications/pers/).

Tadesse, T., Wardlow, B., Hayes, M., Svoboda, M., and Brown, J.F., 2010, The Vegetation Outlook (VegOut)—a new method 

for predicting vegetation seasonal greenness: GIScience and Remote Sensing, v. 47, no. 1, p. 25–52. (Also available online at 

http://dx.doi.org/10.2747/1548-1603.47.1.25).

Tan, Z., Tieszen, L.L., Liu, S., and Tachie-Obeng, E., 2010, Modeling to evaluate the response of savanna-derived cropland to 

warming—drying stress and nitrogen fertilizers: Climatic Change, v. 100, no. 3-4, p. 703–715. (Also available online at http://

dx.doi.org/10.1007/s10584-009-9688-x).

Tang, X., Liu, S., Liu, J., and Zhou, G., 2010, Effects of vegetation restoration and slope positions on soil aggregation and soil 

carbon accumulation on heavily eroded tropical land of Southern China: Journal of Soils and Sediments, v. 10, no. 3, 

p. 505–513. (Also available online at http://dx.doi.org/10.1007/s11368-009-0122-9).

Tang, X., Liu, S., and Zhou, G., 2010, Erosion and vegetation restoration impacts on ecosystem carbon dynamics in South 

China: Soil Science Society of America Journal, v. 74, no. 1, p. 272–281. (Also available online at http://dx.doi.org/10.2136/

sssaj2009.0007).

Weng, Y.-L., Gong, P., and Zhu, Z., 2010, A spectral index for estimating soil salinity in the Yellow River Delta region of China 

using EO-1 Hyperion data: Pedosphere, v. 20, no. 3, p. 378–388. (Also available online at http://dx.doi.org/10.1016/s1002-

0160(10)60027-6).

Wey, C.L., Griesse, J., Kightlinger, L., and Wimberly, M.C., 2009, Geographic variability in geocoding success for West 

Nile virus cases in South Dakota: Health and Place, v. 15, no. 4, p. 1,108–1,114. (Also available online at http://dx.doi.

org/10.1016/j.healthplace.2009.06.00).
Selected Research and Technical Publications 109

White, M.A., de Beurs, K.M., Didan, K., Iinouye, D.W., Richardson, A.D., Jensen, O.P., O’Keefe, J., Zhang, G., Nemani, 

R.R., van Leeuwen, W.J.D., Brown, J.F., de Wit, A., Schaepman, M., Lin, X.A., Dettinger, M.l., Bailey, A.S., Kimball, J., 

Schwartz, M.D., Baldocchi, D.D., and Lee, J.T., 2009, Intercomparison, interpretation, and assessment of spring phenology 

in North America estimated from remote sensing for 19822006: Global Change Biology, v. 15, no. 10, p. 2,335–2,359. (Also 

available online at http://dx.doi.org/10.1111/j.1365-2486.2009.01910.x).

Wickham, J.D., Stehman, S.V., Fry, J.A., Smith, J.H., and Homer, C.G., 2010, Thematic accuracy of the NLCD 2001 land 

cover for the conterminous United States: Remote Sensing of Environment, v. 114, no. 6, p. 1,286–1,296. (Also available 

online at http://dx.doi.org/10.1016/j.rse.2010.01.018).

Wright, C.K., De Beurs, K.M., Akhmadieva, Z.K., Groisman, P.Y., and Henebry, G.M., 2009, Reanalysis data underestimate 

significant changes in growing season weather in Kazakhstan: Environmental Research Letters, v. 4, no. 4, article 

number 045020, available only online at http://dx.doi.org/10.1088/1748-9326/4/4/045020.

Xian, G., and Homer, C.G., 2010, Updating the 2001 National Land Cover Database impervious surface products to 2006 using 

Landsat imagery change detection methods: Remote Sensing of Environment, v. 114, no. 8, p. 1,676–1,686. (Also available 

online at http://dx.doi.org/10.1016/j.rse.2010.02.018).

Xiong, X., Cao, C., and Chander, G., 2010, An overview of sensor calibration inter-comparison and applications: Frontiers of 

Earth Science in China, v. 4, no. 2, p. 237–252. (Also available online at http://dx.doi.org/10.1007/s11707-010-0002-z).

Xue, Y.-J., Liu, S., Hu, Y.-M., and Yang, J.-F., 2010, Soil quality assessment using weighted fuzzy association rules: Pedosphere, 

v. 20, no. 3, p. 334–341. (Also available online at http://dx.doi.org/10.1016/s1002-0160(10)60022-7).

Yuan, W., Liu, S., Liu, H., Randerson, J.T., Yu, G.-R., and Tieszen, L.L., 2010, Impacts of precipitation seasonality and ecosystem types on evapotranspiration in the Yukon River Basin, Alaska: Water Resources Research, v. 46, citation number 

W02514. (Also available online at http://dx.doi.org/10.1029/2009WR008119).

Yuan, W., Liu, S., Yu, G., Bonnefond, J.-M., Chen, J., Davis, K., Desai, A.R., Goldstein, A.H., Gianelle, D., Rossi, F., Suyker, 

A.E., and Verma, S.B., 2010, Global estimates of evapotranspiration and gross primary production based on MODIS and 

global meteorology data: Remote Sensing of Environment, v. 14, no. 7, p. 1,416–1,431. (Also available online at http://dx.doi.

org/10.1016/j.rse.2010.01.022).

Zhang, J., Xu, Y., Yao, F., Wang, P., Guo, W., Li, L., and Yang, L., 2010, Advances in estimation methods of vegetation water 

content based on optical remote sensing techniques: Science China Technological Sciences, v. 53, no. 5, p. 1,159–1,167. (Also 

available online at http://www.springerlink.com/content/r777367u5565612h/).

Zhang, L., Wylie, B.K., Ji, L., Gilmanov, T.G., and Tieszen, L.L., 2010, Climate-driven interannual variability in net ecosystem 

exchange in the northern Great Plains grasslands: Rangeland Ecology & Management, v. 63, no. 1, p. 40–50. (Also available 

online at http://dx.doi.org/10.2111/08-232.1).

Zhang, Y., Zhang, J., Lu, Z., and Gong, W., 2009, A new numerical method for calculating extrema of received power for polarimetric SAR: IEEE Geoscience and Remote Sensing Letters, v. 6, no. 4, p. 666–670. (Also available online at http://dx.doi.

org/10.1109/LGRS.2009.2022958).

Zhao, S., Liu, S., Li, Z., and Sohl, T.L., 2010, Federal land management, carbon sequestration, and climate change in the Southeastern U.S.—a case study with Fort Benning: Environmental Science & Technology, v. 44, no. 3, p. 992–997. (Also available 

online at http://dx.doi.org/10.1021/es9009019).

Zhao, S., Liu, S., Li, Z., and Sohl, T.L., 2010, A spatial resolution threshold of land cover in estimating terrestrial carbon 

sequestration in four counties in Georgia and Alabama, USA: Biogeosciences, v. 7, no. 1, p. 71–80. (Also available online at 

http://www.biogeosciences.net/7/71/2010/).

Zhao, S., Liu, S., Yin, R., Li, Z., Deng, Y., Tan, K., Deng, X., Rothstein, D., and Qi, J., 2010, Quantifying terrestrial ecosystem 

carbon dynamics in the Jinsha Watershed, Upper Yangtze, China from 1975 to 2000: Environmental Management, v. 45, 

no. 3, p. 466–475. (Also available online at http://dx.doi.org/10.1007/s00267-009-9285-9).

Zhu, Q., Jiang, H., Liu, J., Wei, X., Peng, C., Fang, X., Liu, S., Zhou, G., Yu, S., and Ju, W., 2010, Evaluating the spatiotemporal variations of water budget across China over 1951-2006 using IBIS model: Hydrological Processes, v. 24, no. 4, 

p. 429–445. (Also available online at http://dx.doi.org/10.1002/hyp.7496).
110 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Book Chapters

de Beurs, K.M., and Henebry, G.M., 2010, Spatio-temporal statistical methods for modelling land surface phenology, chap. 9 

in Hudson, I.L., and Keatley, M.R., eds., Phenological research—methods for environmental and climate change analysis: 

London, Springer, p. 177–208. (Also available online at http://dx.doi.org/10.1007/978-90-481-3335-2_9).

Duda, K.A., Ramsey, M., Wessels, R., and Dehn, J., 2009, Optical satellite volcano monitoring—a multi-sensor rapid response 

system, chap. 22 in Ho, P-G.P., ed., Geoscience and remote sensing: Vukovar, Croatia, IN-TECH Press, p. 473–496. (Also 

available online at http://sciyo.com/articles/show/title/optical-satellite-volcano-monitoring-a-multi-sensor-rapid-responsesystem).

Funk, C.C., and Verdin, J.P., 2010, Real-time decision support systems—the Famine Early Warning System Network, chap. 17 

in Gebremichael, M., and Hossain, F., eds., Satellite rainfall applications for surface hydrology: New York, Springer, 

p. 295–320.

Liu, S., 2009, Quantifying the spatial details of carbon sequestration potential and performance, chap. 7 in McPherson, B. and 

Sundquist, E., eds., Carbon sequestration and its role in the global carbon cycle: Washington, D.C., American Geophysical 

Union, p. 117–128. 

Lu, Z., and Kwoun, O., 2009, Interferometric synthetic aperture radar (InSAR) study of coastal wetlands over southeastern 

Louisiana, chap. 2 in Wang, Y.Q., ed., Remote sensing of coastal environments: Washington, D.C., CRC Press, p. 25–60. 

Reij, C., Tappan, G.G., and Smale, M., 2009, Re-Greening the Sahel—farmer-led innovation in Burkina Faso and Niger, chap. 

7 in Spielman, D.J., and Pandya-Lorch, R., eds., Millions fed—proven successes in agricultural development: Washington, 

D.C., International Food Policy Research Institute, p. 53–58. (Also available online at http://www.ifpri.org/book-5826/millionsfed/pubs).

Yang, L., Lin, W., Zhang, L., Lin, H., and Du, D., 2009, Contemporary land use and land cover change in coastal Pearl River 

Delta and its impact on regional climate, chap. 19 in Wang, Y.Q., ed., Remote sensing of coastal environments: Washington, 

D.C., CRC Press, p. 369–394.

Yang, L., Sang, H., Lin, H., and Chen, J., 2009, Quantifying biophysical conditions of herbaceous wetland vegetation in Poyang 

Lake of coastal China via multi-temporal SAR imagery and in-situ measurements, chap. 14 in Wang, Y.Q., ed., Remote sensing of coastal environments: Washington, D.C., CRC Press, p. 281–296.

Reports

USGS Fact Sheets

Funk, C.C., 2010, A climate trend analysis of Kenya—August 2010: U.S. Geological Survey Fact Sheet, 2010–3074, 4 p. (Also 

available online at http://pubs.usgs.gov/fs/2010/3074/).

Headley, R.M., 2010, Landsat—A global land-imaging project: U.S. Geological Survey Fact Sheet, 2010–3026, 4 p. (Also 

available online at http://pubs.usgs.gov/fs/2010/3026/).

Jones, B.K., and Bewley, R.D., 2010, The Hazards Data Distribution System is updated: U.S. Geological Survey Fact Sheet, 

2010–3053, 1 p. (Also available online at http://pubs.usgs.gov/fs/2010/3053/).

Jucht, C., 2010, Joint Agency Commercial Imagery Evaluation (JACIE): U.S. Geological Survey Fact Sheet, 2010–3080, 2 p. 

(Also available online at http://pubs.usgs.gov/fs/2010/3080/).

Poppenga, S.K., Evans, G.A., Gesch, D.B., Stoker, J.M., Queija, V., Worstell, B.B., Tyler, D., Danielson, J.J., Bliss, N.B.,

and Greenlee, S.M., 2010, Topographic Science: U.S. Geological Survey Fact Sheet, 2010–3049, 4 p. (Also available online 

at http://pubs.usgs.gov/fs/2010/3049/).
Selected Research and Technical Publications 111

USGS Open-File Reports

Balser, A.W., and Wylie, B.K., 2010, Multitemporal L- and C-band synthetic aperture radar to highlight differences in water 

status among boreal forest and wetland systems in the Yukon Flats, interior Alaska: U.S. Geological Survey Open-File Report 

2010–1027, 18 p. (Also available online at http://pubs.usgs.gov/of/2010/1027/).

Jenkerson, C.B., Maiersperger, T.K., and Schmidt, G.L., 2010, eMODIS—a user-friendly data source: U.S. Geological Survey Open-File Report 2010–1055, 10 p. (Also available online at http://pubs.er.usgs.gov/usgspubs/ofr/ofr20101055).

Karstensen, K.A. and Sayler, K.L., 2009, Land-cover change in the Lower Mississippi Valley, 1973–2000: U.S. Geological Survey Open-File Report, 2009–1280, 12 p. (Also available online at http://pubs.er.usgs.gov/usgspubs/ofr/

ofr20091280?from=home).

Sundquist, E.T., Ackerman, K.V., Bliss, N.B., Kellndorfer, J.M., Reeves, M.C., and Rollins, M.B., 2009, Rapid assessment of 

U.S. forest and soil organic carbon storage and forest biomass carbon sequestration capacity: U.S. Geological Survey OpenFile Report, 2009–1283, 15 p., available only online at http://pubs.er.usgs.gov/usgspubs/ofr/ofr20091283.

Williams, A.P., and Funk, C.C., 2010, A westward extension of the tropical Pacific warm pool leads to March through June drying in Kenya and Ethiopia: U.S. Geological Survey Open-File Report, 2010–1199, 7 p. (Also available online at http://pubs.

usgs.gov/of/2010/1199/).

Zhu, Z., ed., Bergamaschi, B., Bernknopf, R., Clow, D., Dye, D., Faulkner, S., Forney, W., Gleason, R., Hawbaker, T., Liu, J., 

Liu, S., Prisley, S., Reed, B., Reeves, M., Rollins, M.G., Sleeter, B., Sohl, T.L., Stackpoole, S., Stehman, S.V., Striegl, R., 

Wein, A., and Zhu, Z., 2010, Public review draft—a method for assessing carbon stocks, carbon sequestration, and greenhouse-gas fluxes in ecosystems of the United States under present conditions and future scenarios: U.S. Geological Survey 

Open-File Report, 2010–1144, 196 p. plus nine appendixes, available only online at http://pubs.er.usgs.gov/usgspubs/ofr/

ofr20101144.

USGS Scientific Investigations Reports

Gesch, D.B., 2009, Mapping and visualization of storm-surge dynamics for Hurricane Katrina and Hurricane Rita: U.S. Geological Survey Scientific Investigations Report, 2009–5230, 26 p. (Also available online at http://pubs.er.usgs.gov/usgspubs/

sir/sir20095230).

Johnston, C.M., Dewald, T.G., Bondelid, T.R., Worstell, B.B., McKay, L.D., Rea, A.M., R.B., and Goodall, J.L., 2009, Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset: U.S. Geological Survey Scientific Investigations Report, 2009–5233, 88 p. (Also available online at http://pubs.er.usgs.gov/usgspubs/sir/sir20095233).

Mack, T.J., Akbari, M.A., Ashoor, M.H., Chornack, M.P., Coplen, T.B., Emerson, D.G., Hubbard, B.E., Litke, D.W., Michel, 

R.L., Plummer, L.N., Rezai, M.T., Senay, G.B., Verdin, J.P., and Verstraeten, I.M., 2010, Conceptual model of water 

resources in the Kabul Basin, Afghanistan: U.S. Geological Survey Scientific Investigations Report, 2009–5262, 240 p. (Also 

available online at http://pubs.er.usgs.gov/usgspubs/sir/sir20095262).

Poppenga, S.K., Worstell, B.B., Stoker, J.M., and Greenlee, S.M., 2010, Using selective drainage methods to extract continuous surface flow from 1-meter Lidar-derived digital elevation data: U.S. Geological Survey Scientific Investigations Report, 

2010–5059, 12 p. (Also available online at http://pubs.er.usgs.gov/usgspubs/sir/sir20105059).

Non-USGS Discussion Paper

Reij, C., Tappan, G.G., and Smale, M., 2009, Agroenvironmental transformation in the Sahel—another kind of “Green Revolution”: International Food Policy Research Institute Discussion Paper, 914, 52 p. (Also available online at http://www.ifpri.org/

book-5826/millionsfed/pubs).
112 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Conference Papers

Irons, J.R., and Dwyer, J.L., 2010, An overview of the Landsat Data Continuity Mission, in Shen, S.S., and Lewis, P.E., eds., 

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, Orlando, Fla., April 2010, 

Proceedings of SPIE Vol. 7695: Bellingham, Wash., Society of Photo-Optical Instrumentation Engineers, paper number 

769508. (Also available online at http://dx.doi.org/10.1117/12.850416).

Seifert, F.M., Costa, H., Rosenqvist, A., Holm, T.M., and Crevier, Y., 2010, Coordination of space data acquisition in support of 

geo forest carbon tracking, in European Space Agency Living Planet Symposium, Bergen, Norway, 28 June–2 July 2010.

Conference Presentations

Allen, J.E., Johnson, A., and Headley, R.M., 2009, Integrated Geospatial Education and Technology Training (iGETT) for 

workforce development [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, 

no. 52: Washington, D.C., American Geophysical Union, abstract number ED41D-0545. (Also available online at http://www.

agu.org/meetings/fm09/waisfm09adv.html).

Auch, R.F., 2010, Contemporary U.S. industrial forestry—a geographical exploration of America’s wood baskets [abs.], in

Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 28708. (Also available online at http://meridian.aag.org/callforpapers/program/AbstractDetail.

cfm?AbstractID=28708). 

Behnke, J., Hall, A., Meyer, D.J., Sohre, T., and Doescher, C., 2009, Recent release of the ASTER global DEM product [abs.], 

in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., 

American Geophysical Union, abstract number IN12A-07. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Bennett, B., Wood, E.C., Meyer, D.J., Maynard, N., and Pandya, R.E., 2009, NASA NDATC global climate change education initiative [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: 

Washington, D.C., American Geophysical Union, abstract number ED33A-0555. (Also available online at http://www.agu.

org/meetings/fm09/waisfm09adv.html).

Bliss, N.B., 2010, Detailed soil properties from SSURGO for USGS modeling [abs.], in Understanding and predicting for a 

changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Bliss, N.B., Waltman, S.W., and West, L., 2009, Detailed mapping of soil organic carbon stocks in the United States using 

SSURGO [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: 

Washington, D.C., American Geophysical Union, abstract number B51F-0367. (Also available online at http://www.agu.org/

meetings/fm09/waisfm09adv.html).

Bouchard, M.A., Dwyer, J.L., and Granneman, B.J., 2009, A Yukon River Basin Landsat mosaic for assessing environmental 

change [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number GC51A-0708. (Also available online at http://www.agu.org/

meetings/fm09/waisfm09adv.html).

Boyte, S.P., Wylie, B.K., Gu, Y., and Major, D.J., 2010, Ecosystem performance models for multiple land types and climate 

change effects on Big Sagebrush in the Owyhee Uplands [abs.], in Understanding and predicting for a changing world, USGS 

Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Boyte, S.P., Wylie, B.K., Gu, Y., and Major, D.J., 2010, Modeling future climate change effects on Big Sagebrush (Artemisia 

tridentata) and the ecosystem performance of five rangeland types in the Owyhee Uplands, USA [poster], in Understanding the past, informing decisions for the future, Climate Change Science Conference, Denver, Colo., 9–11 March 2010, U.S. 

Geological Survey.

Boyte, S.P., Wylie, B.K., Gu, Y., and Major, D.J., 2010, Modeling rangeland performance and climate change effects on Big 

Sagebrush in the Owyhee Uplands [poster], in Workshop on natural resource needs related to climate change in the Great 

Basin and Mojave Desert—research, adaptation, mitigation, Las Vegas, Nev., 20–22 April 2010, USGS/EPA/USFWS/NPS.
Selected Research and Technical Publications 113

Brown, J.F., Anderson, M.C., Wardlow, B.D., and Svoboda, M.D., 2009, Remote sensing techniques for monitoring drought 

hazards—an intercomparison (Invited) [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number NH41D-01. (Also available 

online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Brown, J.F., Wardlow, B.D., and Tadesse, T., 2010, Advantages of real-time satellite data for operational drought monitoring—

the utility of MODIS and AVHRR [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, 

D.C., American Association of Geographers, abstract ID 28284. (Also available online at http://communicate.aag.org/eseries/

aag_org/program/index.cfm?mtgID=55).

Budde, M.E., Ward, D.H., Ely, C.R., Handel, C.M., and Hupp, J.W., 2009, Altering their ecological niche—investigating the 

response of avian migrants to changes in vegetation phenology at northern latitudes [abs.], in Fall Meeting, San Francisco, 

Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, 

abstract number B43C-0384. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Chen, M., Liu, S., Yuan, W., Liu, H., and Randerson, J.T., 2009, Sequential parameter estimation of a terrestrial ecosystem 

model against eddy covariance measurements by smoothed Ensemble Kalman Filter [abs.], in Fall Meeting, San Francisco, 

Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, 

abstract number B33B-0392. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Danielson, J.J., 2010, A new enhanced global digital elevation model (DEM)—final accuracy assessment and hydrological 

comparisons [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American 

Association of Geographers, abstract ID 29570. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Dinardo, T., and Dwyer, J.L., 2010, Developing essential climate variables for terrestrial modeling and monitoring [abs.], in

Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. 

Geological Survey.

Foster, J.H., Cherubini, T., Manjunath, D.V., Murphy, M., Brooks, B.A., Businger, S., Albers, S.C., Lu, Z., Poland, M.P., Chen, 

S., and Mass, C., 2009, Numerical weather models and mitigating atmospheric artifacts in InSAR [abs.], in Fall Meeting, San 

Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical 

Union, abstract number G23A-0664. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Gesch, D.B., 2010, Elevation uncertainty in sea-level rise assessment—how much land is really at risk? [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 

28054. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Gu, Y., Brown, J.F., and Hawbaker, T.J., 2009, The relationship between climate and satellite-derived vegetation phenology 

[abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, 

D.C., American Geophysical Union, abstract number B43C-0385. (Also available online at http://www.agu.org/meetings/

fm09/waisfm09adv.html).

Gu, Y., and Wylie, B.K., 2010, Detecting ecosystem performance anomalies in the upper Colorado River Basin—implication 

for land management [poster], in Conference on the environment, Portland, Oreg., 26–30 May 2010, U.S. Department of the 

Interior.

Hato, M., Tsu, H., Tachikawa, T., Abrams, M., and Bailey, G.B., 2009, The ASTER Global Digital Elevation Model (GDEM)—

for societal benefit [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, 

no. 52: Washington, D.C., American Geophysical Union, abstract number U33B-0065. (Also available online at http://www.

agu.org/meetings/fm09/waisfm09adv.html).

Hawbaker, T.J., Rollins, M.G., Vogelmann, J.E., Shi, H., and Sohl, T.L., 2009, A national disturbance modeling system to 

support ecological carbon sequestration assessments [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos 

Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B52C-03. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Hawbaker, T.J., Rollins, M.G., Vogelmann, J.E., Shi, H., and Zhu, Z., 2010, Disturbances on ecological carbon sequestration 

and greenhouse gas emissions [abs.], in Understanding and predicting for a changing world, USGS Modeling Conference, 

3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.
114 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Headley, R.M., 2009, Enabling new research with free Landsat data [abs.], in Fall Meeting, San Francisco, Calif., 14–18 

December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number 

IN43C-1162. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Headley, R.M., and Allen, J., 2010, Enabling educators with free Landsat data [abs.], in Annual Meeting, Washington, D.C., 

14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 28193. (Also available 

online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Heidemann, H.K., 2010, The role of common standards, practices, and specifications in national Lidar [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 

33495. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Homer, C.G., 2010, The National Land Cover Database, current status and future plans [abs.], in Annual Meeting, Washington, 

D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 28209. (Also 

available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Huang, C., Li, A., Shi, H., Sun, G., Zhu, Z., Goward, S.N., and Masek, J., 2009, Developing a fine resolution forest height map 

for Mississippi using Landsat time series observations and GLAS lidar data [abs.], in Fall Meeting, San Francisco, Calif., 

14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract 

number B23F-03. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Huang, S., Liu, S., Young, C., Rover, J.A., Heidemann, H.K., Mushet, D., Euliss, N., and Feng, M., 2010, Combining 

National Wetland Inventory, Landsat, and LIDAR to model the wetland water storage in the prairie pothole region of the 

United States [abs.], in Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 

7–11 June 2010, U.S. Geological Survey.

Jenkerson, C.B., Meyer, D.J., and Didian, K., 2009, Case study for EOSDIS support to MEaSUREs—the vegetation index and 

vegetation phenology ESDRs [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., 

v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number IN43C-1165. (Also available online at http://

www.agu.org/meetings/fm09/waisfm09adv.html).

Ji, L., Wylie, B.K., Ramachandran, B., and Jenkerson, C.B., 2009, Comparison of eMODIS and standard MODIS NDVI 

products for Alaska and adjacent Canada [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number IN33D-1069. (Also available 

online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Ji, L., Wylie, B.K., Ramachandran, B., and Jenkerson, C.B., 2010, Comparison of eMODIS and standard MODIS NDVI 

products for Alaska and adjacent Canada [poster], in Understanding the past, informing decisions for the future, Climate 

Change Science Conference, Denver, Colo., 9–11 March 2010, U.S. Geological Survey.

Ji, L., Zhang, L., and Wylie, B.K., 2010, Evaluation of normalized difference water index for mapping surface water bodies 

[abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Washington, D.C., American Association of Geographers, 

abstract ID 31688. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Jones, B.K., 2009, USGS emergency response and the International Charter Space and Major Disasters [abs.], in Fall Meeting, 

San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number NH42A-08. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Killough, B.D., Chander, G., and Gowda, S., 2009, A Web-based Google-Earth coincident imaging tool for satellite calibration 

and validation [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: 

Washington, D.C., American Geophysical Union, abstract number U51B-0016. (Also available online at http://www.agu.org/

meetings/fm09/waisfm09adv.html).

Li, Z., Liu, S., and Tan, Z., 2009, Simulating regional CO2 fluxes in the mid-continent region using GEMS [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B51E-0336. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Liu, J., Liu, S., Oeding, J., Sohl, T.L., and Bliss, N.B., 2010, Estimating soil erosion and deposition under future climate and 

land cover change scenario—USPED model application in the Mississippi plains [abs.], in Understanding and predicting for a 

changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.
Selected Research and Technical Publications 115

Liu, J., Sleeter, B.M., Key, C., Zhu, Z., Liu, S., Sohl, T.L., Vogelmann, J.E., Price, D., Chen, J., Cochrane, M., Eidenshink, 

J.C., Howard, S.M., Bliss, N.B., and Jiang, H., 2010, Estimating vegetation carbon changes in the western United States 

because of land use change, climate change, and natural disturbance—1951–2006 [abs.], in Understanding and predicting for 

a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Liu, S., and Land Carbon Team, 2010, Ecological carbon sequestration under projected land cover and climate change in Mississippi plains—model intercomparison and analysis [abs.], in Understanding and predicting for a changing world, USGS 

Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Liu, S., Li, Z., and Chen, M., 2010, Integrating remote sensing data with GEMS to improve simulation of carbon dynamics 

[abs.], in Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 

2010, U.S. Geological Survey.

Long, J., and Giri, C.P., 2010, Mapping mangrove forest distribution in Australia using Landsat imagery [abs.], in Annual 

Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, 

abstract ID 30992. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Meyer, D.J., and Gallo, K.P., 2009, Enabling data access and interoperability at the EOS Land Processes Distributed Active 

Archive Center [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: 

Washington, D.C., American Geophysical Union, abstract number IN12A-03. (Also available online at http://www.agu.org/

meetings/fm09/waisfm09adv.html).

Miura, T., Brown, J.F., and Gu, Y., 2009, Cross-calibration of AVHRR and MODIS NDVI conterminous United States datasets 

[abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, 

D.C., American Geophysical Union, abstract number B43C-0387. (Also available online at http://www.agu.org/meetings/

fm09/waisfm09adv.html).

Morisette, J.T., Brown, J.F., and Henebry, G.M., 2009, The USA National Phenology Network Land Surface Phenology/

Remote Sensing Phenology Program [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, 

Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B43B-0370. (Also available online at 

http://www.agu.org/meetings/fm09/waisfm09adv.html).

Napton, D.E., 2010, Developed land conversion in the eastern United States—1980 to 2000 [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 28128. 

(Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55)

Pervez, M.S., and Brown, J.F., 2009, Accuracy assessment of the Moderate Resolution Imaging Spectroradiometer (MODIS) 

irrigated agriculture dataset for the conterminous United States (MIrAD-US) [abs.], in Fall Meeting, San Francisco, Calif., 

14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract 

number H21A-0829. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Queija, V., 2010, Lidar analysis of vegetation changes for post-fire chaparral [abs.], in Annual Meeting, Washington, D.C., 

14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 31236. (Also available 

online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Ramsey, M.S., Dehn, J., Duda, K.A., Hughes, C.G., Lee, R., Rose, S., Scheidt, S.P., and Wessels, R.L., 2009, Ten years of 

ASTER thermal infrared data from Terra—discoveries, lessons learned, and insights into future missions [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number U32A-06. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Rover, J.A., Wylie, B.K., and Dahal, D., 2010, Analysis of surface water dynamics in the Yukon Flats of Alaska [abs.], 

in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of 

Geographers, abstract ID 30002. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.

cfm?mtgID=55).

Rover, J.A., Wylie, B.K., and Ji, L., 2009, A new self-trained classification model for producing 30-m percent-water maps from 

Landsat imagery [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 

52: Washington, D.C., American Geophysical Union, abstract number H53L-05. (Also available online at http://www.agu.org/

meetings/fm09/waisfm09adv.html).
116 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Rover, J.A., Wylie, B.K., Wickland, K., and Griffith, B., 2010, Quantifying surface water in the Yukon River Basin [poster], in

Understanding the past, informing decisions for the future, Climate Change Science Conference, Denver, Colo., 9–11 March 

2010, U.S. Geological Survey.

Roy, D., Ju, J., Vermote, E.F., Zhang, C., Egorov, A., Kovalskyy, V., Loveland, T.R., Hansen, M.C., Scaramuzza, P.L., Kline, 

K., Yeom, J., and Kommadreddy, I., 2009, Web-enabled Landsat Data (WELD)—demonstration of MODIS-Landsat data 

fusion to provide a consistent, long-term, large-area data record for the terrestrial user community [abs.], in Fall Meeting, San 

Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical 

Union, abstract number IN43C-1166. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Sayler, K.L., 2010, Detecting land cover change in the United States northern Great Plains, 1973–2006 [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 

32037. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Senay, G.B., Bohms, S., Morgan, D.S., Moreo, M.T., Qi, S., and Christenson, S.C., 2010, Characterizing landscape evapotranspiration dynamics using remote sensing and global weather datasets [abs.], in Understanding and predicting for a changing 

world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Senay, G.B., Bohms, S., and Verdin, J.P., 2010, Using remote sensing for estimating regional evapotranspiration and basin 

water balance components [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., 

American Association of Geographers, abstract ID 33110. (Also available online at http://communicate.aag.org/eseries/aag_

org/program/index.cfm?mtgID=55).

Shi, H., Hawbaker, T.J., Rollins, M.G., Vogelmann, J.E., and Yang, L., 2009, Predicting burn severity and patterns of biomass 

consumption in support of national-scale carbon assessment [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 

2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B53D-0425. 

(Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Singh, R., Liu, S., and Tieszen, L.L., 2010, Satellite-based evapotranspiration and gross primary productivity for the midcontinent intensive campaign [abs.], in Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, 

Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Sleeter, B.M., and Liu, J., 2009, Land-use and land-cover change in California—implications for regional carbon flux [abs.], 

in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., 

American Geophysical Union, abstract number B11D-0502. (Also available online at http://www.agu.org/meetings/fm09/

waisfm09adv.html).

Sohl, T.L., Sleeter, B.M., Sayler, K.L., Acevedo, W., Bouchard, M., and Bennett, S., 2010, Developing a land-use modeling 

framework to support analyses of carbon sequestration and flux [abs.], in Understanding and predicting for a changing world, 

USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Stoker, J.M., 2010, A national Lidar dataset—implications for science [abs.], in Annual Meeting, Washington, D.C., 14–18 

April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 33454. (Also available online 

at http://communicate.aag.org/eseries/aag_org/program/index.cfm?mtgID=55).

Tolk, B.L., 2010, Advanced Wide Field Sensor (AWiFS) imagery—a viable data substitute for LANDFIRE update mapping? 

[abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association 

of Geographers, abstract ID 32845. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.

cfm?mtgID=55).

Verdin, J.P., Funk, C.C., Budde, M.E., Lietzow, R.W., Senay, G.B., Smith, R., Pedreros, D.H., Rowland, J.D., Artan, 

G.A., Husak, G.J., Michaelsen, J., Adoum, A., Galu, G., Magadzire, T., and Rodriguez, M., 2009, Monitoring and modeling 

agricultural drought for famine early warning (Invited) [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, 

Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number H13F-02. (Also 

available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Verdin, J.P., Funk, C.C., and Peters-Lidard, C., 2010, A land data assimilation system for famine early warning [abs.], in

Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. 

Geological Survey.
Selected Research and Technical Publications 117

Vermote, E.F., Justice, C.O., Csiszar, I.A., Eidenshink, J.C., Myneni, R.B., Baret, F., Masuoka, E., and Wolfe, R.E., 2009, A 

terrestrial surface climate data record for global change studies [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 

2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number IN42A-08. 

(Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Wood, E.C., Bennett, B.T., Meyer, D.J., Pandya, R.E., and Maynard, N.G., 2010, Tribal college climate change education in the 

Dakotas [abs.], in Annual Meeting, Washington, D.C., 14–18 April 2010, Proceedings: Washington, D.C., American Association of Geographers, abstract ID 33918. (Also available online at http://communicate.aag.org/eseries/aag_org/program/index.

cfm?mtgID=55).

Wu, Y., and Liu, S., 2010, Impacts of climate change on hydrological components in the upper Mississippi River Basin [poster], 

in Understanding and predicting for a changing world, USGS Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. 

Geological Survey.

Wylie, B.K., Boyte, S.P., and Gu, Y., 2010, Normalized Difference Vegetation Index for restoration monitoring [abs.], in NRDA 

Restoration Program National Workshop, Phoenix, Ariz., 19–23 April 2010, U.S. Department of Interior.

Wylie, B.K., Ji, L., Waldrop, M.P., Rover, J.A., Nossov, D., McFarland, J.W., and Hollingsworth, T., 2010, Quantifying 

changes in terrestrial and aquatic ecology in the Yukon River Basin [poster], in Understanding the past, informing decisions 

for the future, Climate Change Science Conference, Denver, Colo., 9–11 March 2010, U.S. Geological Survey.

Wylie, B.K., Murnaghan, K., Rover, J.A., Tieszen, L.L., and Brisco, B., 2009, Modeling boreal forest performance with 

MODIS, site characteristics, and weather to monitor climate, management, and disturbance impacts [abs.], in Fall Meeting, 

San Francisco, Calif., 14–18 December 2009, Eos Transactions, Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B43C-0388. (Also available online at http://www.agu.org/meetings/fm09/waisfm09adv.html).

Xian, G., and Homer, C.G., 2009, Evaluation of urban land cover and land use—large scale quantification and characterization 

from satellite-based remote sensing [abs.], in Fall Meeting, San Francisco, Calif., 14–18 December 2009, Eos Transactions, 

Suppl., v. 90, no. 52: Washington, D.C., American Geophysical Union, abstract number B33D-0426. (Also available online at 

http://www.agu.org/meetings/fm09/waisfm09adv.html).

Young, C., Liu, S., Mushet, D., Euliss, N., Feng, M., and Huang, S., 2010, Modeling wetland floristic quality change in space 

and time in the prairie pothole region of the United States [abs.], in Understanding and predicting for a changing world, USGS 

Modeling Conference, 3rd, Denver, Colo., 7–11 June 2010, U.S. Geological Survey.

Zhang, L., Wylie, B.K., Ji, L., Gilmanov, T.G., and Howard, D., 2010, Interannual variability in net ecosystem exchange in 

United States Great Plains grasslands [abs.], in General Assembly, European Union of Geosciences, Vienna, Austria, 2–7 May 

2010, Geophysical Research Abstracts, v. 12: Katlenburg-Lindau, Germany, European Geophysical Society, abstract number 

EGU2010-7424. (Also available online at http://meetingorganizer.copernicus.org/EGU2010/poster_programme/1859).

Zhang, L., Wylie, B.K., Ji, L., Gilmanov, T.G., Howard, D., and Tieszen, L.L., 2010, Upscaling carbon fluxes over Great 

Plains grassland—sinks and sources [abs.], in Conference on the environment, Portland, Oreg., 26–30 May 2010, Proceedings: Washington, D.C., U.S. Department of Interior. (Also available online at http://www.regonline.com/builder/site/Default.

aspx?eventid=782504).
118 U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center—Fiscal Year 2010 Annual Report

Conclusion

In FY 2010, EROS Management rolled out the Center’s new strategic plan: “Moving Forward: A 2010–2015 Strategic Plan 

for USGS EROS.” In FY 2011, the Center is intent on achieving results against this plan through its mission goals: 

• Understand the Nation’s remote sensing requirements;

• Expand our multimission capabilities so that those requirements can be addressed;

• Develop a terrestrial monitoring system that provides the data, services, and assessments needed to understand and manage environmental change; and

• Maintain a strong remote sensing science, applications, and development program that addresses the Nation’s most pressing needs.

EROS will be working with USGS Leadership and the network of USGS Science Centers to achieve these goals.

Communication with our expanding constituent and customer base is vital to the success of our programs and projects, and 

we encourage your feedback. Please let us know how well we are meeting your needs and share your suggestions for improvement with us directly.

To communicate with us, or for more information about EROS, contact:

Communications and Outreach

USGS EROS Center

47914 252nd Street

Sioux Falls, South Dakota 57198

jsnelson@usgs.gov

http://eros.usgs.gov/

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Janice S. Nelson, Compiler—U.S. Geological Survey (USGS) Earth Resources Observation 

and Science (EROS) Center—Fiscal Year 2010 Annual Report—Open-File Report 2011–1057