![](media/image1.wmf){width="1.625in" height="0.5986111111111111in"}

Land Use Change and Effects on Water Quality and Ecosystem Health in the
Lake Tahoe Basin, Nevada and California: Year-1 Progress

By William Forney^1^, Christian Raumann^1^, Timothy B. Minor ^2^, J.
LaRue Smith ^3^, John Vogel ^1^, and Robert Vitales^1^

# Open-File Report 02-014

## 2002

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

## U.S. Department of the Interior

U.S. Geological Survey

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

^1^U.S. Geological Survey, Menlo Park, California

^2^Desert Research Institute, University and Community College System of
Nevada, Reno, Nevada

^3^U.S. Geological Survey, Carson City, Nevada

# ABSTRACT

As part of the requirements for the Geographic Research and Applications
Prospectus grants, this Open-File Report is the second of two that
resulted from the first year of the project. The first Open-File Report
(OFR 01--418) introduced the project, reviewed the existing body of
literature, and outlined the research approach. This document will
present an update of the research approach and offer some preliminary
results from multiple efforts, specifically, the production of
historical digital orthophoto quadrangles, the development of the land
use/land cover (LULC) classification system, the development of a
temporal transportation layer, the classification of anthropogenic cover
types from the IKONOS imagery, a preliminary evaluation of landscape
ecology metrics (quantification of spatial and temporal patterns of
ecosystem structure and function with appropriate indices) and their
utility in comparing two LULC systems, and a new initiative in
community-based science and facilitation.

# INTRODUCTION

This paper updates the previous Open-File Report (OFR 01--418) by
focusing on specific results and accomplishments that have occurred over
fiscal year (FY) 2001. The only item that is repeated from OFR 01--418
is Chart 1. This is meant to refresh the memory of any reader that has
read the other OFR, and---for those that have not---to put the body of
the text in context. For further discussion of the elements and
particulars of Chart 1, please refer to OFR 01--418.

**Chart 1**. Schematic of research approach.

+--------------------+-------------------------+----------------------+
| **IKONOS** (25     | **HDOQs** (pilot        | **Fieldwork**        |
| km^2^ scene)       | watersheds)             |                      |
+--------------------+-------------------------+----------------------+
| \- Obtain imagery. | \- Produce HDOQs.       | \- Define LULC       |
|                    |                         | classes.             |
| \- Classify        | \- Produce temporal     |                      |
| impervious cover.  | LULC datasets.          | \- Do accuracy       |
|                    |                         | assessments.         |
| \- Classify        | \- Create temporal      |                      |
| natural cover.     | transp. layer           | \- Clarify mixed     |
|                    |                         | pixel problems.      |
+--------------------+-------------------------+----------------------+

+-----------------------------------+-----------------------------------+
| ######### ANALYSIS                |                                   |
+-----------------------------------+-----------------------------------+
| ######### Landscape Structure     |                                   |
+-----------------------------------+-----------------------------------+
| Investigate and define metrics.   |                                   |
|                                   |                                   |
| Assess the integrity of           |                                   |
| landscape.                        |                                   |
+-----------------------------------+-----------------------------------+
| ######### Water Quality           | ######### Ecosystem Health        |
+-----------------------------------+-----------------------------------+
| \- Assess the change in two       | \- Change in class and landscape  |
| hydrographs.                      | metrics, fractal dimension.       |
|                                   |                                   |
| \- Perform SCS Curve Number       | \- Change in SEZs and riparian    |
| analysis.                         | patches.                          |
|                                   |                                   |
| \- Do export coefficient model.   | \- Metapopulation dynamics and    |
|                                   | corridors.                        |
| \- Regress class metrics to water |                                   |
| quality parameters.               | \- Human and naturally induced    |
|                                   | disturbance regimes.              |
+-----------------------------------+-----------------------------------+

The progress to be discussed in this OFR is the production of historical
digital orthophoto quadrangles (HDOQ), the development of the land
use/land cover (LULC) classification system, the development of the
temporal transportation layer, the classification of anthropogenic cover
types from the IKONOS imagery, a preliminary evaluation of landscape
ecology metrics (quantification of spatial and temporal patterns of
ecosystem structure and function with appropriate indices), and the
utility of landscape ecology metrics in comparing two LULC systems: the
California Gap Analysis and the Multi-Resolution Land Characteristics
(MRLC), and a new initiative in community-based science and
facilitation.

# PROGRESS AND RESULTS

## Historical Digital Orthophoto Quadrangle Production

The production of HDOQs was the second project of its kind undertaken by
the U.S. Geological Survey's (USGS) Western Geographic Science Center
Data Applications & Integration Section (DAIS). The first part of the
project required image rectification of 22 natural color 3.75-minute
DOQs. The 3.75-minute HDOQs are within the Emerald Bay, South Lake
Tahoe, Echo Lake, Freel Peak, Caples Lake, and Carson Pass, Calif.,
7.5-minute quadrangles, which encompass the pilot watersheds. Only 14 of
the 22 HDOQs were ingested into the DOQ database, as 8 HDOQs did not
have complete image coverage within the 3.75-minute cell.

Challenges facing this particular project that are inherent
characteristics of many HDOQ projects included the use of non-National
Aerial Photography Program (NAPP) source imagery (nonstandard flight
heights/scale), the use of image photography not quarter-quad centered,
and the absence of traditional ground control and aerotriangulation.

Materials for the project that were researched and acquired included
existing first-generation DOQs (produced from 1992 NAPP photographs),
digital elevation models (DEM), published quadrangle maps, flight line
diagrams, camera calibration reports, and the natural color 1987 U.S.
Forest Service (USFS) aerial photographs. Forty-four image diapositives
were required to make the twenty-two 3.75-minute HDOQs in the project;
four to six image "chips" per HDOQ. The photograph centers and extents
were plotted on 7.5-minute topographic quadrangle maps to determine
optimum image coverage for the 3.75-minute DOQ cells.

The image diapositives were digitally captured with a scanning aperture
of 30 microns. During the scanning phase, two representative images with
clear fiducial marks were selected for measurement. The coordinates of
the fiducial marks were measured on the scanner as input to
transformation software that generated a camera calibration file, with
additional processing that calculated an approximate photographic scale.

In lieu of control or aerotriangulation, the existing 1992 DOQs were
used to control each scanned image. Control points that were selected
had to be visible on both the existing DOQ and on the scanned image of
the 1987 photograph. Using a split screen, we selected at least nine
distributed points of common, well-defined, photoidentifiable image
features and measured them to control each image. At least two points
were selected on each image edge, for commonality with two or more
adjoining overlap and side images. The relative closeness of the
photograph acquisition dates between the historical image photographs,
and the source image photographs of the existing DOQs facilitated
selection and accurate reading of the control points.

With the camera and derived control files, DEMs, and source images as
input, the Digital Orthophoto Processing System (DOPS) was used to
perform image rectification and HDOQ creation. A parameter file (.par)
was generated, with relevant information about the project. Each aerial
photograph or image chip was entered into the .par file to ensure the
proper interaction between inputs and to be used for subsequent program
execution. Image chips falling within Universal Transverse Mercator
(UTM) Zone 11 were initially rectified in UTM Zone 10, as requested by
the project staff. Using the requisite control, DEMs, and raw image
files, the DOPS software rectified the image chips.

Once the individual image chips were rectified, they required mosaicking
to construct the final HDOQ. Many of the image chips were used
repeatedly where chip coverage extended into multiple HDOQs.
Re-rectification of image chips occurred when chips did not extend to
areas of estimated coverage. This was remedied by adjusting the corner
coordinate determining domain size in the .par file and then
reprocessing. The mosaic program locally adjusted the brightness values
at join lines to minimize tonal variations between image chip join
areas. After the mosaic of the chips was completed, the HDOQ overedge
was calculated and trimmed, and the HDOQ datum quadrangle corner crosses
were embedded. Finally, the standard USGS keyword header for the HDOQ
was edited, which included recording the photographic source information
of the image chips contained within.

Final quality assurance/quality control (QA/QC) measures consisted of
HDOQ header verification, thorough image inspection of each individual
HDOQ, and a comprehensive check of all HDOQs within the project,
checking image adjacency geometry and general image radiometry. Tone
matching was not performed on the HDOQs. After the chips that resided in
UTM Zone 11 were re-rectified, the 14 HDOQs with complete image coverage
met DOQ acceptance criteria and were ingested into the DOQ database.

## Temporal Land Use/Land Cover Mapping

The two primary considerations in defining a classification system for
the Lake Tahoe Basin are (1) the techniques of LULC mapping and (2) the
intended use of the resulting temporal LULC coverages.

To maintain consistency with other LULC mapping activities of the USGS
National Mapping Program, we developed a modified-Anderson hierarchical
classification system with definitions (Appendix B) for the Tahoe Basin;
this is a subset of the system developed for the MRLC 2000 National Land
Cover Data (NLCD) mapping effort (Anderson, 1976). Additional models for
defining classes were provided by classification systems developed by a
group at the USGS Rocky Mountain Mapping Center for use in large-scale
regional temporal LULC mapping projects in the Middle Rio Grande Basin,
Colorado Front Range, and Brazos, Texas (Stier, 1999). This approach
allows the capture of high-resolution features from the HDOQs in a
system that can be aggregated and compared on a regional basis. The
system developed for the Tahoe Basin allows classification of major land
use types (2000-series Developed) and land cover types (1000 Water, 2000
Bare, 4000 Vegetated), as well as estimation of impervious surface cover
for developed lands (fig. 1).

For this project, Aerial Information Systems, Inc. (AIS) in Redlands,
Calif., was chosen to compile the temporal LULC coverages under the
direction of the USGS. AIS uses traditional aerial photography
interpretation techniques to create vector LULC coverages by onscreen
(or "heads up") digitizing of LULC polygons over a DOQ/HDOQ base layer.
Also, stereopairs of the original aerial photographs from which the DOQs
were produced are viewed through a stereoscope to assist in the LULC
mapping. Areas of similar LULC are detected and grouped on the basis of
color, tone, texture, size, shape, and context of features shown on the
imagery, as well as information gained from ancillary data sources, such
as parcel, vegetation, elevation, and NLCD data layers. The minimum
mapping unit (MMU) used will be 1 acre. These techniques yield a spatial
resolution that allows a classification system up to Level IV.

The intended use and analysis of the temporal LULC coverages were
considered in determining classes and defining their extent. Since the
impact of anthropogenic impervious surfaces on water quality is the
basis for much of the future analysis, the LULC coverages must include
an estimation of impervious cover. LULC classification systems used in
previous water quality studies have assigned a single percentage of
impervious surface coverage for each land use class. However, a more
accurate assessment of impervious cover is possible with more precise
and rigorous photographic interpretation and use of ancillary data. With
this in mind, AIS will estimate anthropogenic impervious surface cover
from 0-100 percent in 5-percent increments for each developed parcel
(2000-series) and will include this value as a separate attribute in
each coverage.

## Temporal Transportation Layer Development

The HDOQs produced for this project, as well as existing Tahoe Basin
DOQs for 1992 and 1998, will serve as the primary source for developing
temporal transportation layers. These geographic information system
(GIS) layers will be used to provide quantitative information on
landscape structure, to estimate impervious surface coverage, and to
assist in the interpretation of land cover classes.

A 1998 transportation layer for the pilot watersheds was developed for
this project on the basis of the best available vector-based
transportation dataset, which was obtained from the USFS, and then
modified using 1998 DOQs and data obtained from the field (fig.2). The
original USFS transportation layer incorporated USGS DLG data with USFS
global positioning system (GPS) corrections obtained in 1998. However,
even with the GPS corrections, this layer contained many horizontal
inaccuracies of up to 20 meters that had to be reduced to make the data
useful in later analysis and derivation of temporal layers.

The USFS layer was modified by displaying the data onscreen at a scale
of 1:4,000, with the 1998 DOQs as a reference for editing. All road
segments that did not lie within the width of a road as shown on the DOQ
were moved to fall within the width of the road. However, the modified
road segments do not necessarily represent the centerlines of the roads.
Also, if a line existed in the layer but a coinciding road was not
visible on the 1998 DOQ, the line was deleted. This process removed many
trails that the USFS has identified but that are not visible on the 1998
DOQs. Trails cannot be accurately identified in compiling

###  {#section-1 .Style1}

  ----------- -------------------- ------------------------- ------------------------
  **Level I** **Level II**         **Level III**             **Level IV**

                                                             

  1000 Water  1100 Open Water      1110 Stream/River         

                                   1120 Canal/Ditch          

                                   1130 Lake/Pond            

                                   1140 Reservoir            

                                   1150 Bay/Estuary          

              1200 Perennial                                 
              Ice/Snow                                       

  2000        2100 Residential     2110 Single-family        
  Developed                        Residential               

                                   2120 Multi-family         
                                   Residential               

              2200 Nonresidential  2210 Commercial           2211 Major Retail
              Developed                                      

                                                             2212 Mixed/Minor Retail

                                                             2213 Office

                                                             2214 Light Industry

                                   2220                      
                                   Communication/Utilities   

                                   2230 Institutional        2231 Schools

                                                             2232 Cemeteries

                                   2240                      
                                   Agriculture/Livestock     

                                   2250 Transportation       2251 Primary Road

                                                             2252 Railroad

                                                             2253 Airport

                                   2260 Recreation/Open      2261 Golf Course
                                   Space                     

                                                             2262 Urban Park

                                                             2263 Ski Runs

                                                             2264 Campground/Picnic
                                                             Area

                                                             2265 Marina/Boat Launch

                                                             2266 Swimming Beaches

              2300 Mixed Urban                               

  3000 Bare   3100 Transitional                              

              3200 Quarries/Strip                            
              Mines/Gravel Pits                              

              3300 Rock Faces,                               
              Rock Slides, Cliffs                            

              3400 Exposed Rock                              

              3500 Disposal                                  

              3600 Mixed Bare                                

  4000        4100 Forest          4110 Coniferous           4111 Coniferous (10-50%
  Vegetated                                                  Crown Closure)

                                                             4112 Coniferous (\>50%
                                                             Crown Closure)

                                   4120 Deciduous            4121 Deciduous (10-50%
                                                             Crown Closure)

                                                             4122 Deciduous (\>50%
                                                             Crown Closure)

                                   4130 Coniferous/Decid.    4131 Con./Decid. Mixed
                                   Mixed                     (10-50% Crown Closure)

  **Level I** **Level II**         **Level III**             **Level IV**

                                                             4132 Con./Decid. Mixed
                                                             (\>50% Crown Closure)

                                   4140 Brush/Shrubland      

                                   4150 Mixed Forest/Shrub   

                                   4160 Planted/Cultivated   

              4200 Herbaceous      4210 Natural Herbaceous   

                                   4220 Planted/Cultivated   
                                   Herb.                     

              4300 Wetlands        4310 Wooded Wetlands      

                                   4320 Brush/Shrub Wetlands 

                                   4330 Herbaceous Wetlands  

              4400 Severely Burned                           
              Upland Vegetation                              
  ----------- -------------------- ------------------------- ------------------------

**Figure 1.** Land Use/Land Cover Classification System for the Lake
Tahoe Basin.

the temporal transportation layers if trails are not visible in the
HDOQs. In other cases, if a road was visible in the 1998 DOQs but not
present in the USFS layer, the road was added to the layer.

Once line editing was completed, the attributes of the layer were
modified. Road width and accessibility attributes were added, both of
which required field measurements in addition to DOQ interpretation. The
three transportation attributes and their descriptors are as follows:

1.  Surface: paved, unpaved, railroad, trail

2.  Width: actual width of the road in feet

3.  Access: unlimited, limited, controlled

The accuracy of this initial transportation layer is crucial for
preserving vertical integration, because this layer will be used as a
base to derive the older transportation layers. As the HDOQs from 1987,
1969, and 1940 become available, lines will then be edited or deleted
from this completed 1998 transportation layer, and new temporal layers
will be created.

![](media/image2.jpeg){width="5.375694444444444in"
height="7.080555555555556in"}

**Figure 2.** Extent and detail of the edited 1998 transportation layer
for the pilot

watersheds.

## Anthropogenic Cover: Impervious Surfaces

Remotely sensed data offer the advantage of synoptic, large-area
analyses but have limitations in an environment such as the Lake Tahoe
Basin. Analysis of airborne and/or spaceborne data for impervious cover
is complicated by high variability in extended forest canopy density
throughout the Basin. Some commercial areas near the "Y," as shown in
figure 3 for example, have very little or no canopy cover. Rural
residential areas such as those shown in figure 4, on the other hand,
have canopy densities approaching 90 percent or higher, essentially
obscuring the surface features underneath the canopy. With high canopy
closure, conventional manual interpretation of aerial photographs and/or
satellite imagery will not provide accurate estimates of impervious
cover, because understory features, such as driveways or roofs, cannot
be detected below the canopy.

![](media/image3.wmf){width="5.594444444444444in"
height="4.307638888888889in"}

**Figure 3.** Portion of IKONOS imagery showing commercial development

with little or no canopy cover at the South Lake Tahoe "Y."

Despite this difficulty, remotely sensed imagery has been used to derive
accurate impervious cover estimates by using methods that integrate
ancillary data sources. Image classification methods have been tailored
to combine both imagery and ancillary spatial data, such as parcel
descriptions, transportation, and other demographic and physical data.
It is critical in these applications that the ancillary spatial data
(especially parcel data, if being used) have a high level of accuracy.
These methods produce a raster-based surface of impervious cover
density. The raster-based surfaces represent local probabilities of
impervious cover density ranging from high to low (Harris and Ventura,
1995; Mesev, 1998). These probability data can then be converted to
percentage of impervious cover estimates by unit. Ji and Jensen (1999)
used Landsat thematic mapper (TM) data with a layered classification
approach, along with a subpixel classifier, to derive eight levels of
urban imperviousness in parts of Charleston, S.C. Although, these
methods result in some measure of impervious cover, they do not measure
it directly. That is, the result is not a discrete number but rather a
categorical range or associated value, such as low, medium, or high.

New satellite data collected by the IKONOS instrument may allow direct
estimates of impervious cover, where canopy closure does not obscure the
direct sensing of features. IKONOS also provides a means of

![](media/image4.wmf){width="5.577083333333333in"
height="4.175694444444445in"}

**Figure 4.** Portion of IKONOS imagery showing residential development
obscured

by canopy cover in the Black Bart neighborhood of South Lake Tahoe.

discriminating different urban land cover types and their relationship
to impervious cover classes. The results from Cablk and Minor (in press)
indicate that impervious cover can be accurately and directly mapped
with IKONOS imagery. The method for impervious cover mapping involved
multiple image processing steps, ranging from masking to image
transformation with thresholding, to applying morphological filters. A
modeling approach was proposed because the IKONOS data were expected to
have the same difficulties that other air- and space-borne sensors have
with dense canopies. The results were contrary to this assumption; it
was found that sub-canopy and subshadow surfaces were not only
detectable, but also discernible with respect to the underlying surface
cover, when image processing methods were combined with spatial modeling
tools (fig. 5). An image processing/spatial modeling method based on
principal components analysis and spatial morphological operators was
developed using image processing software and a GIS. On the basis of an
accuracy assessment using 170 ground verification points selected
throughout the study area, an overall classification accuracy of 92.94
percent was obtained, with an even higher user or "reliability" accuracy
of 95.83 percent. Impervious cover estimates for the entire
9.65-square-mile (25-square-kilometer) area were calculated at 1.6
square miles (4.15 square kilometers), or 16 percent of the total
surface area.

The investigation described in this report expands on the work presented
by Cablk and Minor (in press) to determine if contemporary urban land
use classes can be generated using the impervious cover results. These
use types include commercial, residential, infrastructure, and
industrial. These distinctions depend primarily upon the availability of
a good GIS parcel layer, which the El Dorado County Assessor's office is
in the process of producing. Natural land cover types will be identified
as well, particularly those associated with relevant ecosystem
processes. Investigators will determine if IKONOS data can allow finer
distinctions between classes than other types of multispectral imagery
(such as Landsat TM or SPOT) and the HDOQs. An accuracy assessment of
the IKONOS classification results will be conducted using ground
truthing to validate the accuracy of the results and examine
heterogeneous pixel issues.

![](media/image5.wmf){width="5.988888888888889in"
height="3.0729166666666665in"}

**Figure 5.** Results of principal component analysis with morphological
operators to detect

impervious cover under tree canopy shadow; Black Bart neighborhood of
South Lake Tahoe.

## Assessment of LULC Systems and Landscape Ecology Metrics

One of the goals of this research is to assess alternative LULC data
sources for their ability to provide useful classification systems and
landscape metrics. As such, the California Gap Analysis and the MRLC
systems were examined, and their GIS coverages were analyzed.

The Gap Analysis is an ecoregional assessment with a scale of 1:100,000
and a 100-hectare MMU. Gap Analysis data are intended for identifying
landscapes that contain large numbers of potentially unprotected
vegetation types and vertebrate species (California Gap Analysis
Program, 2001). It applies the California Wildlife-Habitat Relation
(WHR) System as its dominant LULC classification system to determine
preferred and likely habitat of 455 native terrestrial vertebrate
species. Figure 6 presents the GIS coverage and LULC of the Gap Analysis
for the four-quadrangle area of South Lake Tahoe (Freel Peak, South Lake
Tahoe, Echo Lake, and Emerald Bay).

The MRLC is a consortium of the USGS (National Mapping, Biological
Resources, Geologic, and Water Resources Disciplines), U.S.
Environmental Protection Agency, USFS, and National Oceanic and
Atmospheric Administration, and its goal is to produce a consistent land
cover data layer for the conterminous United States based on 30-meter
(0.09 ha) Landsat TM data (Lake Tahoe Data Clearinghouse, 2001). Figure
6 presents the NLCD GIS coverage that is a result of the consortium's
efforts for the same four-quadrangle area that was represented in Figure
7.

After obtaining the two coverages and clipping them to the same spatial
extent, we used the software package FRAGSTATS\*ARC to produce a suite
of patch, class, and landscape metrics. Although the software produces a
total of 59 metrics, certain simple ones were selected to elucidate the
consistency between systems and assess the utility of the data. Tables 1
and 2 present select class and landscape metrics from the two coverages.

In table 1, the two metrics presented provide valuable information about
a class or a particular land cover type in a landscape. According to the
MRLC, over 32,000 ha or almost 60 percent of the four-quadrangle area in
South Lake Tahoe is considered to be evergreen forest. These metrics are
useful for getting a sense of the composition of a landscape. As for the
two LULC classification systems, table 1 gives a good indication of the
problems associated with using multiple systems. When comparing the two
systems, the nomenclature assigned to the same or similar cover types
can confound analyses or applications of the data. For example, the
distinction between barren versus rock/sand/clay can be significant. If
one were trying to establish hydrologic infiltration rates or
ground-water recharge sites, neither of these land cover types would
offer much guidance in parameterizing a water balance model or
determining locations in which to prohibit certain land uses.
Consequently, as this research moves

![](media/image6.jpeg){width="6.495833333333334in"
height="5.392361111111111in"}

**Figure 6.** California Gap Analysis Program land cover data for the
pilot watersheds.

**Table 1**. Class metrics of two LULC classification systems (regular
text signifies the Gap Analysis metrics, and italicized text signifies
the MRLC/NLCD metrics)

+-----------------------------+-------------------+-------------------+
| ## Gap an                   | **Area (ha)**     | **% Landscape**   |
| d MRLC/NLCD Classifications |                   |                   |
+-----------------------------+-------------------+-------------------+
| Barren                      | 2,907             | 5.2               |
+-----------------------------+-------------------+-------------------+
| #### Rock/Sand/Clay         | *539*             | *1.0*             |
+-----------------------------+-------------------+-------------------+
| Wet meadow                  | 767               | 1.4               |
+-----------------------------+-------------------+-------------------+
| ####                        | *100*             | *0.2*             |
| Emergent herbaceous wetland |                   |                   |
+-----------------------------+-------------------+-------------------+
| Subalpine conifer           | 8,440             | 15.4              |
+-----------------------------+-------------------+-------------------+
| #### Evergreen forest       | *32,715*          | *59.5*            |
+-----------------------------+-------------------+-------------------+
| Urban                       | 4,512             | 8.2               |
+-----------------------------+-------------------+-------------------+
| ###                         | *1,877*           | *3.4*             |
| # Low-intensity residential |                   |                   |
+-----------------------------+-------------------+-------------------+

![](media/image7.jpeg){width="6.745138888888889in"
height="5.398611111111111in"}

**Figure 7.** The National Land Cover Dataset for the pilot watersheds.

forward, it is essential that a consistent and hierarchical LULC system
be adopted and used for all data sources and locations. This will
provide for analyses and applications at multiple scales and regions.

Table 2 shows that the landscape metrics that aggregate across all land
cover types within the specified region are very useful in quantifying
the visually apparent differences in the LULC datasets. As suggested in
figure 5, the Gap Analysis data have large patches compared with the
NLCD, as a result of their relatively coarse resolution. Table 2
supports this assertion as the mean patch size of the Gap Analysis is
337 ha, whereas for the NLCD it is 1.3 ha. Furthermore, the NLCD is
derived from raster Landsat data, which will tend to make the class
designations more intermittent and interspersed. This assertion is
supported by the fact that although the NLCD has a lower patch richness
(or diversity of land cover types), it has a higher number of patches
(table 2). Overall, the NLCD data appear to be more useful than the Gap
Analysis data for this study, so future comparisons will be made using
the NLCD. As this research moves forward, the consistency of scale,
resolution, and source of data needs to be maintained. This will become
a challenge when comparing LULC datasets derived from the HDOQs with
ones derived from IKONOS imagery.

## Community-Based Science

At the May 2001 meeting of the Upper Truckee Watershed Focus Group, the
USGS and Desert Research Institute project scientists presented an
overview of this USGS research effort in the Tahoe Basin

**Table 2.** Landscape metrics of two LULC classification systems

  ------------------ ----------------- ----------------- -----------------
  **Classification   **Patch           **\# of Patches** **Mean Patch Size
  System**           Richness**                          (ha)**

  Gap analysis       17                163               337

  MRLC/NLCD          14                41,901            1.3
  ------------------ ----------------- ----------------- -----------------

to other scientists, regional administrators, and local landowners.
Following that meeting, project researchers approached the landowners
and asked for their input on the project; specifically, the project team
wanted to know if the research being conducted addressed the landowners'
questions and concerns. As a result of those discussions, the authors
are now exploring the impact of beaver populations in the watershed
(Busher and Dzieciolowski, 1999), and they were asked to facilitate
future meetings that focus on issues important to the landowners. In
August 2001, Christian Raumann and John Vogel presented project
information and facilitated a meeting of landowners, Tahoe Regional
Planning Agency officials, El Dorado County government personnel, and
USGS researchers.

# Summary and Work Plan

As the tasks described in this report are completed, work in 2002 will
build upon these accomplishments. Production of HDOQs for the pilot area
will be completed, and then temporal LULC coverages with impervious
cover estimates will be derived from the HDOQs. The temporal
transportation datasets in the pilot area will also be completed using
the HDOQs. Once IKONOS imagery is obtained for the entire Tahoe Basin
(summer 2002) all impervious cover in the pilot watersheds will be
classified. When these datasets have been created, the hypotheses stated
in OFR 01--418 can be tested. An ArcIMS-based Web site will also be
created to allow improved data dissemination and analysis by all
potential data users.

# Acknowledgments

Thank you to those who also contributed to the progress of this project
and the writing of this report, including Timothy Rowe, Ken Adams, Mike
Campagna, and Leila Gass.

# REFERENCES

Anderson, James, Hardy, Ernest, Roach, John, and Witmer, Richard, 1976,.
A land use and land cover classification system for use with remote
sensor data: U.S. Geological Survey Professional Paper 964.

Busher, P.E., and Dzieciolowski, R.M., 1999, Beaver protection,
management, and utilization in Europe and North America: New York,
Kluwer Academic/Plenum Publishers, p. 182.

Cablk, M.E., and Minor T.B., in press, Detecting and discriminating
impervious cover with high resolution IKONOS data using principal
components analysis and morphological operators: International Journal
of Remote Sensing.

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http://www.biogeog.ucsb.edu/projects/gap/gap_proj.html.

Harris, P.M., and Ventura, S.J., 1995, The integration of geographic
data with remotely sensed imagery to improve classification in urban
areas: Photogrammetric Engineering and Remote Sensing, v. 61, no. 8, p.
993--998.

Ji, M., and Jensen, J.R., 1999, Effectiveness of subpixel analysis in
detecting and quantifying urban imperviousness from Landsat thematic
mapper Imagery: Geocarto International, v. 14, no. 4, p. 31--39.

Lake Tahoe Data Clearinghouse, September 2001,
http://tahoe.usgs.gov/files/nlcd_meta_ca.txt.

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Photogrammetric Engineering and Remote Sensing, v. 64, no. 5, p.
431--438.

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Bartolino, J.R., ed., U.S. Geological Survey Middle Rio Grande Basin
Study---Proceedings of the Third Annual Workshop, February 24--25, 1999,
Albuquerque, N. Mex.: U.S. Geological Survey Open File Report 99--203.

# APPENDIX A

## Lake Tahoe Basin Land Use/Land Cover Classification System Definitions

**1000 WATER**---Area covered by water, snow, or ice with less than
25-percent vegetated or developed cover, unless specifically included in
another category.

> **1100 Open Water**---All areas of open water with less than
> 25-percent vegetative or developed cover.
>
> **1110 Stream/River**---A natural body of flowing water. Includes
> streams and rivers that have been channelized to control flooding or
> erosion or to maintain flow for navigation.
>
> **1120 Canal/Ditch**---A manmade open waterway constructed to
> transport water, to irrigate or drain land, to connect two or more
> bodies of water, or to serve as a waterway for watercraft. Collection
> should include the rights-of-way and associated dikes and levees.
>
> **1130 Lake/Pond**---A nonflowing, naturally existing body of water.
> Includes water impounded by natural occurrences and artificially
> regulated natural lakes. The delineation of a lake is based on the
> areal extent of water at the time the imagery was acquired.
>
> **1140 Reservoir**---Any artificial body of water, unless specifically
> included in another category. It can lie in a natural basin or a
> manmade basin. The delineation of a reservoir is based on the areal
> extent of water at the time the imagery was acquired. (The water
> control structures are classified as Communications/Utilities)
>
> **1150 Bay/Estuary**---The inlets or arms of the sea that extend
> inland.
>
> **1200 Perennial Ice/Snow**---Areas covered year-round with snow and
> ice.
>
> **2000 DEVELOPED**---Areas that have been improved by human activity.
> Includes all built-up and urban areas of the landscape. Does not
> include mining lands, croplands, or waste-disposal areas. This land
> use category takes precedence over a land cover category when the
> criteria for more than one category are met.
>
> **2100 Residential**---Lands containing structures used for human
> habitation.
>
> **2110 Single-Family Residential**---Lands used for housing residents
> in single-family dwelling units. Includes trailer parks, mobile home
> parks, and entire farmsteads when there is a home in the complex.
> Single-family residential buildings located within another category
> should be identified in this category.
>
> **2120 Multi-Family Residential**---All lands devoted to housing more
> than one family on a permanent or semipermanent basis, group living
> situations, and their associated grounds. Includes apartments,
> apartment complexes, duplexes, triplexes, attached row houses,
> condominiums, retirement homes, nursing homes, and residential hotels.
> Residential buildings located within another category, such as
> barracks and dormitories, should be identified in this category when
> possible.
>
> **2200 Nonresidential Developed**---Any developed area or feature that
> is used for a purpose other than habitation.
>
> **2210 Commercial**---Structures and associated grounds used for the
> sale of products and services, for business, or for light industrial
> activities. Includes all retail and wholesale operations. Includes
> "industrial parks" and other features that cannot be clearly
> classified as either a retail service or light industry, such as heavy
> equipment yards, machinery repair, and junkyards.
>
> **2211 Major Retail**---Includes shopping malls, retail "outlet
> centers," and "superstores" that draw clientele from a regional area.
> Major retail centers consist of extremely large single buildings or a
> complex of large buildings and their parking lots. Malls usually house
> one or two major department stores and numerous small retail stores.
> Includes outlet centers, "superstores," multiplex movie theaters,
> warehouse-type stores, hotels, and casinos. The structures themselves
> are often several acres in size and have extensive parking lots.
>
> **2212 Mixed/Minor Retail and Services**---Includes individual stores
> and services of various sizes and associated grounds and parking.
> Includes neighborhood strip malls and shopping centers, veterinarian
> services, small movie theaters, gas stations and auto repair shops,
> garden centers, motels, small auto dealerships, public parking lots,
> lumber yards, art galleries, farm supply stores, flea markets, bars
> and restaurants, grocery stores, and commercial truck stops. Many
> small office buildings will have no features to distinguish them from
> retail stores and will fall in this category.
>
> **2213 Office**---Structures (and their associated grounds and
> parking) that provide financial, professional, administrative, and
> informational services. Includes administrative government offices
> (for example, IRS and State Motor Vehicles offices), trade schools,
> professional medical office complexes, research facilities/centers,
> and banks. Usually only office buildings in office complexes or in
> downtown areas will be distinguishable as offices. Small, single-story
> office buildings may blend in with minor retail.
>
> **2214 Light Industry**---Structures and their associated grounds and
> facilities that are used primarily to produce or process some finished
> product, or that are used as a wholesale distribution center.
> Activities include the design, assembly, finishing, packaging,
> warehousing, or shipping of products rather than the processing of raw
> materials. The materials used in light industry have generally been
> processed at least once. They are generally "clean" industries that do
> not produce large amounts of waste materials. Use this category as a
> default for those facilities with semi-truck and trailer activity
> around loading docks, but that cannot be classified as either retail
> services or heavy industry. Includes electronic firms, clothing and
> furniture manufacture, grain elevators, printing plants, commercial
> bakeries, shipping and distribution centers, sand/gravel sorting
> facilities, secondary buildings associated with a mining or quarrying
> site, and generic warehouses.
>
> **2220 Communications/Utilities**---Structures or facilities and
> associated grounds used for the generation of power and
> communications, the treatment or storage of drinking water, waste
> management, flood control, or the distribution and storage of gas and
> oil not associated with a unique feature. Includes pumping stations
> (oil, gas, or water), tank farms, power plants, electric substations,
> sewage treatment facilities and ponds, garbage collection facilities
> (not the final dumping ground; these are included in Bare), dams,
> levees, and spillways of appropriate dimensions, filtration plants,
> and heavy concentrations of antennas or satellite dishes, along with
> the related operational buildings.
>
> **2230 Institutional**---Specialized government or private features
> that meet the educational, religious, medical, governmental,
> protective, and correctional needs of the public. Parking lots and
> associated grounds are included with these features. Includes public
> and private schools, city halls, courthouses, libraries, churches,
> convents, monasteries, hospitals and training hospitals, post offices,
> police and fire departments, prisons, and military bases.
>
> **2231 Schools**---Public and private schools, seminaries, university
> campuses, and associated lands, including the entire "core campus"
> area, along with athletic fields and vegetated areas. This category
> does not include daycare centers or commercial trade schools, both of
> which are commercial uses.
>
> **2232 Cemeteries**---Structures and lands devoted to burial of the
> dead. Includes mausoleums, service areas, and parking lots.
>
> **2240 Agriculture/Livestock**---Structures and all associated grounds
> used for raising plants or animals for food or fiber. Includes fish
> farms and hatcheries, feedlots, poultry farms, dairy farms, temporary
> shipping and holding pens, animal breeding or training facilities, and
> greenhouses. (Farmsteads including a dwelling are classified as
> residential, not Agricultural Business.)
>
> **2250 Transportation**---Roads, railroads, airports, port facilities,
> and their associated lands. Category includes bus stations, highway
> maintenance yards, school bus parking and service yards, and
> park-and-ride lots. Port facilities include loading and unloading
> facilities, docks, locks, and temporary storage areas. Associated
> warehousing and transfer stations for truck or rail are included only
> if they appear to be an integral part of the airport or port facility.
> Nearby but separate warehouses will be classified as light industry.

**2251 Primary Road**---Roads include rights-of-way, interchanges, and
median

strips.

> **2252 Railroad**---Railroads include rights-of-way, interchanges, and
> median strips. Category also includes railroad stations and railroad
> yards.
>
> **2253 Airport**---Includes the maintained active and overrun areas of
> the runways, landing strips, and taxiways, with the intervening land;
> also includes the plane tie-down areas, terminals, hangers, related
> fuel-storage facilities, service buildings, parking lots, navigation
> aids, and airport offices. Rental car lots integrated with the airport
> should be included with the airport.
>
> **2260 Recreation/Open space**---Areas and structures used
> predominantly for athletic or artistic events, or for leisure
> activities, and all associated lands and developed parking areas.
> Includes outdoor amphitheaters, drive-in theaters, campgrounds, zoos,
> sports arenas (including indoor arenas), developed parks and
> playgrounds, community recreation centers, museums, amusement parks,
> public swimming pools, fairgrounds, and ski complexes (not the ski
> slopes). Marinas with over 25 percent of water surface covered by
> docks and boats are included here.
>
> **2261 Golf Course**---All par 3 courses and above are included, both
> public and private. Courses can be identified by greens, fairways,
> sand traps, water hazards, clubhouses, and parking areas. Additional
> facilities often associated with golf courses, such as tennis courts,
> pools, parking, and so on, are not identified separately but are
> included in the 2261 category. Ponds, wetlands, and other water bodies
> are, however, identified separately under the appropriate category if
> they meet minimum polygon size.
>
> **2262 Urban Parks**---Designated open space in urban settings used
> for outdoor recreation. Category includes grass fields and associated
> structures, parking lots, and facilities. Includes city parks,
> "green-belt" urban parks, and athletic fields not associated with a
> school. Does not include undeveloped "open space" on the periphery of
> urban areas or undeveloped regional, state, or national park areas.
>
> **2263 Ski Runs**---Areas that have been cleared of vegetation for the
> purpose of downhill skiing and related activities.
>
> **2264 Campground/Picnic Area**---This category includes areas that
> are set aside for picnicking and camping specifically and for
> associated activities (hiking, and so on). Commercial and private tent
> and trailer campgrounds are included, unless they are part of a resort
> complex. Any open areas associated with either picnicking or camping
> areas that exceed 1 acre are mapped out under category 2264.
> Supplemental information may be needed to identify picnic or camping
> areas in forested regions.
>
> **2265 Marina/Boat Launch**---Public and private facilities consisting
> of docks, storage, storage buildings, boat ramps, jetties, piers, and
> parking areas are included in this category. Boats may or may not be
> visible because of photographic scale. Small, primarily State-owned
> launching sites will generally not be visible on the small-scale air
> photographs.
>
> **2266 Swimming Beaches**---These areas are specifically manmade
> beaches that are adjacent to lakes or ponds and have been developed
> for recreational activities. Parking areas are included, but the water
> is identified under the appropriate water category.
>
> **2300 Mixed Urban**---Developed areas with a mixture of residential
> and nonresidential features where no single feature meets the minimum
> mapping unit specification. This category is used when more than
> one-third of the features in an area do not fit into a single
> category. Often applicable in the central urban-core area of cities.
>
> **3000 BARE**---Undeveloped areas of Earth not covered by water that
> exhibit less than 25-percent vegetative cover or less than 5-percent
> vegetative cover if in an arid area. Earth's surface may be composed
> of bare soil, rock, sand, gravel, salt deposits, or mud.
>
> **3100 Transitional**---Areas dynamically changing from one land
> cover/land use to another, often because of land use activities.
> Includes all construction areas, areas undergoing transition between
> forest and agricultural land, and urban renewal areas that are in a
> state of transition.
>
> **3200 Quarries/Strip Mines/Gravel Pits**---Areas of extractive mining
> activities with significant surface disturbance. Vegetative cover and
> overburden are removed for the extraction of deposits such as coal,
> iron ore, limestone, copper, sand and gravel, or building and
> decorative stone. Current mining activity does not need to be
> identifiable. Inactive or unreclaimed mines and pits are included in
> this category until another land cover or land use has been
> established. Includes strip mines, open-pit mines, quarries, borrow
> pits, oil and gas drilling sites, and gravel pits, all with their
> associated structures, waste dumps, and stockpiles.
>
> **3300 Rock Faces, Rock Slides, Cliffs**---Includes rock faces on
> mountains, rock slides, talus cones, and cliffs that are sparsely
> vegetated. These exposed types have a large vertical component.
>
> **3400 Exposed Rock**---Includes bare bedrock, natural sand beaches,
> sand bars, deserts, desert pavement, lava, and glacial debris. Areas
> consisting of exposed bedrock or other accumulation of rocks lacking
> vegetative cover are included. These areas have a small vertical
> component compared with 3300.
>
> **3500 Disposal**---Designated areas where refuse is dumped or exists,
> such as landfills, trash dumps, or hazardous-waste disposal sites.
> Reclaimed disposal areas or those covered with vegetation do not
> qualify.
>
> **3600 Mixed Bare**---Any mixture of substrates making up a bare area,
> such as bare rock, soil, and/or sand, where the individual units do
> not meet the minimum mapping unit or do not fit in another 3000-series
> class.
>
> **4000 VEGETATED**---Areas having generally 10 percent or more of the
> land or water with vegetation. Arid or semiarid areas may have as
> little as 5-percent vegetation cover.
>
> **4100 Forest**---Land with at least 10-percent tree and/or
> brush/shrub canopy cover.
>
> **4110 Coniferous**---Land where natural coniferous (evergreen) stands
> form at least 10-percent canopy cover. Species include pine (such as
> ponderosa, Jeffery, lodgepole, sugar, western white, whitebark), fir
> (white, red), mountain hemlock, incense-cedar, and juniper.
>
> **4111 Coniferous, 10- to 50-Percent Crown Closure**---Natural
> coniferous stands with crown closure of at least 10 percent but les
> than 50 percent.
>
> **4112 Coniferous, \>50-Percent Crown Closure**---Natural coniferous
> stands with crown closure greater than 50 percent.
>
> **4120 Deciduous**---Land where natural deciduous stands form at least
> 10-percent canopy cover. Species include willow, quaking aspen, and
> cottonwood.
>
> **4121 Deciduous, 10- to 50-Percent Crown Closure**---Natural
> deciduous stands with crown closure of at least 10 percent but less
> than 50 percent.
>
> **4122 Deciduous, \>50-Percent Crown Closure**---Natural deciduous
> stands with crown closure greater than 50 percent.
>
> **4130 Coniferous/Deciduous Mixed**---Land where natural forest stands
> form at least
>
> 10-percent canopy cover and are dominated by coniferous species and
> mixed with deciduous species (such as aspen, alder, willow, maple, and
> cottonwood).
>
> **4131 Coniferous/Deciduous Mixed, 10- to 50-Percent Crown
> Closure**---Natural forest stands dominated by coniferous species and
> mixed with deciduous species with crown closure of at least 10 percent
> but less than 50 percent.
>
> **4132 Coniferous/Deciduous Mixed, \>50-Percent Crown
> Closure**---Natural forest stands dominated by coniferous species and
> mixed with deciduous species with crown closure greater than 50
> percent.
>
> **4140 Brush/Shrubland**---Forested areas dominated by woody
> vegetation predominately less than 20 feet in height (with large trees
> composing less than 10-percent crown closure). Vegetative communities
> in these areas may range from early successional species that are only
> a few years old, to climax or subclimax communities that are many
> years old. Clear-cut areas will exhibit a stage of shrub cover during
> the regrowth cycle. Also included in this category are old fields that
> are covered primarily by grasses and some shrubs. Includes evergreen
> and deciduous species of true shrubs, trees that are small or stunted
> because of environmental conditions (that is, *krummholz*), desert
> scrub, and chaparral. Common species include mountain sagebrush,
> manzanita, chinquapin, rabbit brush, bitterbrush, desert peach,
> willow, mountain mahogany, cream bush, huckleberry oak, tobacco brush,
> Ceanothus, and whitebark pine.
>
> **4150 Mixed Forest/Shrub**---Areas characterized by large coniferous
> and deciduous trees (taller than 20 feet) and shrubs, where neither
> trees nor shrubs dominate.
>
> **4160 Planted/Cultivated**---Areas containing plantings of evenly
> spaced trees, shrubs, bushes, or other cultivated climbing plants
> usually supported and arranged evenly in rows. Includes orchards,
> groves, vineyards, cranberry bogs, berry vines, and hops. Includes
> tree plantations planted for the production of fruit and nuts,
> Christmas tree farms, and commercial tree nurseries. Excludes pine
> plantations and other lumber or pulp wood plantings that are
> classified as 4110 Coniferous.
>
> **4200 Herbaceous**---Areas dominated by nonwoody plants, such as
> grasses, forbs, ferns, and weeds, either native, naturalized, or
> planted. Trees must account for less than 10-percent crown cover, and
> herbaceous plants dominate all existing vegetation.
>
> **4210 Natural Herbaceous**---Areas dominated by native or naturalized
> grasses, forbs, ferns, and weeds. Areas can be managed, maintained, or
> improved for ecological purposes, such as weed/brush control or soil
> erosion. Includes vegetated vacant lots and areas where it cannot be
> determined whether the vegetation was planted or cultivated, such as
> in areas of dispersed grazing by feral or domesticated animals.
> Includes landscapes dominated by natural grasses and grass-like
> plants, such as bunch grasses and tundra vegetation.
>
> **4220 Planted/Cultivated Herbaceous**---Areas of herbaceous
> vegetation planted and/or cultivated by humans for agronomic purposes
> in developed settings. Most of the vegetation in these areas is
> planted and/or maintained for the production of food, feed, fiber,
> pasture, or seed. Includes perennial grasses, legumes, or grass-legume
> mixtures that are planted by humans and used for erosion control, for
> seed or hay crops, for grazing animals, or for landscaping purposes.
> Temporarily flooded areas are included in this category.
>
> **4300 Wetland**---Areas where the water table is at, near, or above
> the land surface for a significant part of most years and vegetation
> indicative of this covers more than 25 percent of the land surface.
> Wetlands can include marshes; swamps situated on the shallow margins
> of bays, lakes, ponds, streams, or reservoirs; wet meadows or perched
> bogs in high mountain valleys; or seasonally wet or flooded low spots
> or basins. Do not include agricultural land flooded for cultivation
> purposes. Wetlands that have been modified for recreation,
> agriculture, or industry will not be included here but described under
> the specific use category.
>
> **4310 Wooded Wetland**---Wetlands dominated by coniferous and
> deciduous trees. In this category are seasonally flooded bottomland
> and wooded swamps, including those around bogs. Dominating species
> include willow, cottonwood, alder, aspen, and pine.
>
> **4320 Brush/Shrub Wetland**---Wetlands dominated by woody species
> that are less than 20 feet tall. These areas may be an early
> successionary stage to wetland dominated by canopy species or a
> shrub-dominated community associated with marshes, isolated wetlands,
> or bogs. Brush and shrub species are similar to those in 4130.
>
> **4330 Herbaceous Wetland**---Wetlands dominated by herbaceous
> vegetation, including fresh-water and brackish-water marshes, mountain
> meadows, and open bogs. Includes grass, sedge, rush, and cattail.
>
> **4400 Severely Burned Upland Vegetation**---Naturally vegetated
> upland areas that have been altered by intense burning. These burned
> areas have not revegetated sufficiently on the photographs, or at the
> time of any field inspection undertaken to support a mapping effort,
> to make a determination of the type of vegetation that will reappear
> in the burned area. The preburn cover type may be any of those listed
> above in the 4000 series. Where sufficient re-vegetation has occurred
> to determine a postburn cover type, the burned area is given the
> appropriate land cover code. However, where the revegetation has been
> insufficient, the 4500 code has been applied. Note that many different
> upland forest types may be included in this category.

**5000 UNMAPPED**