bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantifying Uncertainties in Determining SW Cloud Radiative Forcing and Cloud Absorption due to Variability in Atmospheric Conditions
Authors: Li Z , Trishchenko A
Published: March 2017

The concept of cloud radiative forcing (CRF) has been widely employed in studying the effects of clouds on the earth's radiation budget and climate. CRF denotes, in principle, the net influence of cloud alone on the radiation budget of a system. In practice,
however, observational determination of CRF is fraught with uncertainties due to factors other than cloud that induce changes in atmospheric background conditions. The most notable variables include aerosol, water vapor, and the data sampling scheme. The impact of these factors on the derivation of
CRF and cloud absorption is investigated here by means of modeling and analysis of multiple datasets. Improved estimation of CRF is attempted at the top of the atmosphere (TOA) and at the surface from spatially and temporally collocated ground and satellite measurements for broadband shortwave
fluxes. Satellite data employed include pixel measurements from ERBE (1988-90), ScaRaB (1994-95), and CERES (1998), as well as surface data acquired across the Canadian radiation network, the ARM Central Facility site in Oklahoma, the US/NOAA SURFRAD networks, and the world BSRN (WMO) networks. It
is found that surface CRF is much more susceptible to the variability in background conditions than TOA CRF. Selection of overly clear sky conditions often leads to significant overestimation of surface CRF, but TOA CRF remains intact or only slightly affected. As a result, the ratio of CRF at the
surface and TOA is prone to overestimation. With careful treatments of these effects, the CRF ratio turns out to vary mostly between 0.9 and 1.1, implying approximately the same magnitude of atmospheric absorption under clear-sky and cloudy-sky conditions.
The ScaRaB Earth Radiation Budget Dataset
Authors: Kandel R , Viollier M , Raberanto P , Duvel J Ph , Pakhomov L
A , Golovko V A , Trishchenko A , Mueller J , Raschke E , Stuhlmann R
Published: March 2017

Following an overview of the scientific objectives and organization of the French-Russian-German Scanner for Radiation Budget (ScaRaB) project, brief descriptions of the instrument, its ground calibration, and in-flight operating and calibration procedures are
given. During the year (24 February 1994-6 March 1995) of ScaRaB Flight Model 1 operation on board Meteor-3/7, radiometer performance was generally good and well understood. Accuracy of the radi-ances is estimated to be better than 1% in the longwave and 2% in the shortwave domains. Data
processing procedures are described and shown to be compatible with those used for the National Aeronautics and Space Administration's (NASA) Earth Radiation Budget Experiment (ERBE) scanner data, even though time sampling properties of the Meteor-3 orbit differ considerably from the ERBE system
orbits. The resulting monthly mean earth radiation budget distri-butions exhibit no global bias when compared to ERBE results, but they do reveal interesting strong regional differences. The 'ERBE-like' scientific data products are now available to the general scientific research community.
Prospects for combining data from ScaRaB Flight Model 2 (to fly on board Ressurs-1 beginning in spring 1998) with data from the NASA Clouds and the Earth's Radiant Energy System (CERES) instrument on board the Tropical Rainfall Measure-ment Mission (TRMM) are briefly
discussed.
Tracking Uncertainty in Derived Height Data
Authors: Gibson J R , Buchheit M
Published: March 2017

This chapter discusses the tracking of uncertainty in height data derived from stereo imagery that has been obtained from an airborne electro-optical digital multi-spectral imaging system. The overall objective of the software described has been to prepare the
data for input into Geographic Information Systems, and to provide the ground coordinates of the data with the greatest accuracy possible. This article has two objectives: to provide a brief overview of the digital imagery procedures used to process the raw imagery and ancillary inertial navigation
system data to achieve photogrammetric adjustment, geometric correction, and terrain height extraction, and, second, to illustrate the results of processing a representative data set. One of the final products produced by the software processing systems is a mosaic of ortho-imagery, using the nadir
views and the terrain height data generated from the stereo imagery.
 The chapter discusses the methods and the procedures that are being developed at the Canada Centre for Remote Sensing for tracking or carrying the absolute and relative accuracies of the derived data
products from the raw data through to the final products. The paper con- cludes with an example of some processed imagery and derived height data along with the confidence measure or uncertainty of the derived height.
Ship-sea Contrast Optimization When Using Polarimetric SARs
Authors: Touzi R , Charbonneau F , Hawkins R K , Murnaghan K , Kavoun X
Published: March 2017

The polarization information was investigated in [8] for ship detection using calibrated polarimetric Convair-580 SAR data that were collected within the incidence angle range of 45° to 70°. It was shown that at operational satellite SAR incidence
angles (lower than 60°), there is a significant improvement of ship-sea contrast when the full polarimetric information is used instead of the in formation provided by the (scalar) one channel polarization (HH, VV, or HV). In this paper, the investigation is extended to lower incidence angles,
and the robustness of the polarimetric discriminators used for ship enhancement, is assessed at various wind conditions (7, 14 and 20 knots). Polarization channel phase information is also investigated. It is shown that the information contained in the HH-VV channel phase difference, looks to be
very promising for ship enhancement, mainly when a dual-polarized SAR is used.
Terrestrial Carbon Observation Initiative: an integrated satellite - in situ strategy
Authors: Cihlar J , Denning S , Tschirley J
Published: March 2017

The terrestrial component of the global carbon cycle has become the focus of intense attention by the scientific community, international environmental organisations, national governments, and increasingly more also by the private sector. A common factor among
this multitude of interests is the need for a 'system' capable of quantifying the net exchanges of carbon between the atmosphere and the terrestrial ecosystems. In this paper, we describe a recent initiative by the Integrated Global Observing Strategy Partnership (IGOS-P) aimed at establishing a
system-atic, long-term observing capability for estimating the spatial and temporal distribution of CO2 fluxes between the terrestrial ecosystems and the atmosphere.
The Canada Centre for Remote Sensing and the Canadian Astronaut Office Collaboration in the Space for Species Educational Program
Authors: Coulson J , Bruce W , Thirsk R
Published: March 2017

A partnership between the Canada Centre for Remote Sensing (CCRS), Natural Resources Canada, and the Canadian Astronaut Office (CAO), Canadian Space Agency, exists in order to promote Earth observation expertise from two unique perspectives; from satellites and
from manned platforms. This paper focuses on one area of this effort, Space for Species (SFS), a Web-based learning program that promotes the monitoring of migratory species and their habitats from a perspective beyond the Earth's atmosphere. SFS is a co-operative effort involving the Canadian Space
Agency (CSA), the Canadian Wildlife Service (CWS), the Canadian Wildlife Federation (CWF) and corporate sponsors. CCRS provides satellite imagery and research support to SFS. The program encourages students in grades six through nine to track the movements of four selected species at risk of
extinction in Canada by observing the habitats of these species from space by using satellite imagery and astronaut photographs, monitoring daily and seasonal climatological conditions that affect species' movements and evaluating threats to species along migratory routes. The program also provides
the opportunity for students to communicate with field biologists, remote sensing scientists and Canadian astronauts; all of whom will offer expertise, as well as, help students interpret collected data. Students also gain first-hand experience in developing species recovery plans. This paper
describes the SFS learning program and highlights the Earth observation component and content of the program Web site.
Satellite image fusion with multi-scale wavelet analysis: Preserving Spatial Information and Minimizing Artifacts (PSIMA)
Authors: Du Y , Vachon P W , van der Sanden J J
Published: March 2017

Image fusion is the combination of two or more different images to form a new image that contains enhanced information. Consistent with specific application goals, a variety of image products arises from the many available fusion algorithms. However, there is no
universal, quantitative performance measure to estimate image fusion quality. The essential objective of image fusion is that nearly all of the original application-specific information should be preserved, and artifacts should be minimized in the final product.
 The
wavelet transform, a well-known and solid mathematical tool, has already been applied to multi-sensor image fusion. The wavelet transform allows the decomposition of an image into its constituent spatial scale layers. Most image fusion techniques, including wavelet analysis, require that the input
images of different spatial resolutions and sample sizes first be re-sampled to achieve spatial registration. The re-sampling could cause a loss of spatial information or might introduce artifacts in the final fused image, especially when the resolutions of the input images are significantly
different.
 In this paper, as a further development of the application of wavelet analysis to image fusion, we propose a new scheme for multi-resolution image fusion, Preserving Spatial Information and Minimizing Artifacts (PSIMA) with multi-scale wavelet analysis. With
the PSIMA scheme, the images are fused in almost their original pixel size. Therefore, the finest spatial information of the input images can be preserved and artifacts minimized in the final fused product. We demonstrate the PSIMA scheme using RADARSAT-1 ScanSAR and NOAA AVHRR images. The results
show that the PSIMA scheme is superior to conventional wavelet analysis for image fusion in terms of spatial information preservation and artifact rejection.
RADARSAT-1 SAR for Hurricane Watch
Authors: Vachon P W , Black P , Dodge P , Katsaros K , Clemente-Colon P , Pichel W , MacDonell K
Published: March 2017

RADARSAT-1's ScanSAR wide (SCW) modes, with swath widths of 450 or 500 km and a spatial resolution of 100 m, can provide both near-synoptic scale and small-scale views of the imprint of mesoscale meteorological processes and features on the ocean surface's
roughness. In the case of hurricanes, the images show wind speed and direction effects around the relatively calm eye, as well as regions of intense convection, rainfall, organized boundary layer phenomena such as boundary layer rolls, and storm-generated swell. Although initial observations were
largely serendipitous, Hurricane Watchhas routinely acquired SCW imagery of hurricanes during the 1999 and 2000 Atlantic Basin hurricane seasons (nominally August through October). The Canadian Space Agency's Disaster Watch Program and Background Mission Program submitted SCW imagery requests in
support of this project. Disaster Watch made manual requests as late as 29 hours in advance of the pass time that were fewer in number but more accurate than those of the Background Mission. In this paper, we discuss some of the scheduling and swath coverage constraints, and show and discuss some of
the striking images that were acquired. New insights to storm morphology, storm dynamics, and SAR ocean imaging have followed from these observations. Hurricane Watch will be repeated in 2001, with a particular emphasis on the study of organized boundary layer structures between rain bands. The wide
spread extent of these structures was first revealed by RADARSAT-1 images.
Forest Type Discrimination Using SAR Polarization Information
Authors: Touzi R , Landry R , Charbonneau F
Published: March 2017

In order to promote the unique polarimetric capability of RADARSAT-2, CCRS has investigated the potential of fully polarimetric C-band SAR for forest type discrimination. Six forest types in Eastern Ontario (Mer Bleu) were considered in this study: mixed forest,
poplar, red pine, white pine, a mixed forest of red and white pines, and white spruce. In addition to the conventional linear polarizations HH, HV, and VV, various polarimetric discriminators, which were synthesized from the scattering matrix measurements, were investigated. It is shown that the
radiometric of the conventional C-band SAR polarizations HH, HV and VV can only perform a limited discrimination of various trees, and cannot separate deciduous from coniferous trees in spring and summer conditions. The polarimetric information provided by the polarimetric (co- and cross-polarized)
signatures, the circular polarizations, and the Cloude's parameters H/A/α/β, did not improve significantly forest type discrimination. The best results were obtained with the extrema of the completely polarized component of the scattered wave. These parameters permit even
the separation of deciduous from coniferous
Spectral Unmixing of Rock/Mineral Targets Based on Different Spatial Resolution Hyperspectral Data
Authors: Staenz K , Budkewitsch P , Neville R A , Hitchcock R , Nadeau C
Published: March 2017

The study presented in this paper investigated the influence of spatial resolution upon the spectral unmixing for rock/mineral identification and the interpretation for geological mapping in Arctic environments. Probe-1 data acquired near Nanisivik, Nunavut,
Canada on July 29, 1999 was used for this purpose. After re-calibrating the cube, its spatial resolution of 6.5 m was degraded using pixel block averaging to generate 13.0-m, 19.5-m, 32.5-m, and 52.0-m data sets. Subsequent processing included the retrieval of surface reflectance using MODTRAN4,
automatic endmember selection, and linear spectral unmixing. Ground reference information such as reference spectra of the different target types was used to validate the endmember and unmixing results. The mapping results indicate that the five different rock units examined could be identified
successfully across the different spatial resolutions. However, a more detailed delineation of the rock units could be achieved from the data cubes with finer spatial resolution.
Extraction du couvert végétal en forêt Brésilienne avec des images stéréoscopiques de RADARSAT (résumé étendu)
Authors: Toutin Th , Amaral S
Published: March 2017

This paper demonstrates the applicability of RADARSAT stereo-images for the interpretation and measurement of some characteristics of the Brazilian tropical rain forest. Clearing boundaries, vegetation cover and canopy heights were qualitatively interpreted and
quantitatively measured on a fine mode RADARSAT stereo-pair using a PC-based softcopy stereo workstation. Since no ground truth was specifically acquired for this project, the validation of the results is realized in two steps using previous research studies of the same site. The clearing boundaries
were first overlaid on a previously ortho-rectified Landsat-TM image to verify their planimetric accuracy and the interpretation of the vegetation cover. The planimetric positioning error of 30 metres for the clearing boundaries was mainly due to the accuracy of the input cartographic data. Larger
errors were a result of the deforestation and regeneration between image acquisition dates, the dominant scattering regime from the forest and the mis-interpretation of SAR backscatter. The computed canopy heights were then compared to an existing vegetation map, which described the tree species and
their characteristics of each class. The results in canopy heights were generally consistent and a good representation of terrain reality. With few exceptions, a mean height variation of about 5 metres with the expectedcanopy heights based on previous studies was obtained. In the context of
monitoring the Amazon forest in Brazil, these results based on radar stereo geometry show promise as a complementary tool to traditional methods based only on radar radiometry.
Unsupervised Landscape Unit Mapping Based on Multi-scale Analysis
Authors: Beauchemin M , Pan D , Fung K B
Published: March 2017

We present the preliminary development of a segmentation algorithm for landscape unit mapping. A multi-scale approach is used (i) to establish local proportion of land cover types within different window sizes centered around each pixel and (ii) to determine the
suitability of each window size to support pattern unit candidacy. A fusion process of the multi-scale proportion map is then carried out at each pixel position based on minimum acceptable size of pattern unit. An unsupervised segmentation algorithm is finally utilized to cluster the resulting fused
map into homogeneous regions. Preliminary results are presented for a 10-class land cover map derived from a supervised classification of a 30 km x 30 km subarea of a Landsat TM scene.
DEM with stereo IKONOS: a reality if...
Authors: Toutin Th , Cheng P
Published: March 2017

A digital elevation model (DEM), as a representation of the Earth's relief, is now one of the most important data structures used for geospatial analysis and modeling. The digital format of a DEM has made it easier to derive additional information for various
applications causing elevation modeling to become an important part of international research and development programs related to geo-spatial data. In fact, cartographers, engineers, geologists, hydrologists, and other geo-scientists largely use three-dimensinal (3D) information to understand better
the Earth's surface. Unfortunately, DEMs of usable details are unavailable for much of the Earth and when available frequently lack sufficient accuracy. IKONOS, the commercial satellite with the highest publicly available resolution, was successfully launched in September 1999. Since the satellite's
sensors can generate 1m panchromatic and 4m multiband images with off-nadir viewing up-to-60º in any azimuth, stereo capabilities are one of its strongest attributes. General users could apply photogrammetric techniques to IKONOS stereo images with softcopy stereo-workstations so as to extract
planimetric features, elevation information, such as DEMs or both. The high-spatial resolution stereo imagery sold by Space Imaging to government agencies will have "unlimited" uses for various applications, such as national mapping, environment monitoring, natural disaster assessment, and watershed
management. Stereo
data could also be used to help city administrators with 3D city models to plan, develop and manage utilities (gas, water and power transmission or distribution), and telecommunications networks.
3D Geometric Modelling of IKONOS Geo Images
Authors: Toutin Th , Chénier R , Carbonneau Y
Published: March 2017

Digital elevation model (DEM) extracted from IKONOS along-track stereo images with photogrammetric method is evaluated. As few as 12 GCPs are enough for the stereo photogrammetric bundle adjustment, which also filters the errors of the input data. With an
area-based image matching users may produce high resolution DEMs with LE68 errors of 1 m to 4 m depending on the land covers. The best results (1.1 m-2.6 m) are obtained in bare soils, lakes, residential areas and sparse forests. The surface elevation of some of the areas (residential/ forests) did
not affect too much the errors because the 1-2-storey houses in residential areas are sparse or because the images were acquired when there is no leave in the deciduous forests. An error evaluation as a function of the slope azimuths shows that the DEM error in sun-facing slopes is 1-m smaller than
the DEM error in slopes away from the sun. 5-10 m contour lines could thus be derived with the highest topographic standard.
Land Use and Cover with Intensity Assessment for Canada from Satellite and Census Data
Authors: Kerr J , Cihlar J
Published: March 2017

In this paper, we describe a new system for the construction of both land use and land use intensity (within agricultural regions) called LUCIA (land use and cover with intensity of agriculture). Our methodology combines the highly detailed Canadian Census of
Agriculture and recent growing season composites derived from the SPOT4/VEGETATION sensor. Census data are of much coarser resolution than the remotely sensed data, but, by removing non-agricultural pixels from each census sampling area, we were able to spatially refine the census data sufficiently
to allow it to be used as ground truth data in some areas. The refinedcensus data were then used in the final step of an unsupervised classification of the remotely sensed data.
The results of the land use classification are generally consistent with the input census data,
indicating that the LUCIA output reflects actual land use trends as determined by national census information. Land use intensity, defined as the principal component of census variables that relate to agricultural inputs and outputs (e.g. chemical inputs, fertilizer inputs, and manure outputs), is
highest in the periphery of the great plains region of central Canada but is also very high in southern Ontario and Québec.
Day and night-time active fire detection over North America using NOAA-16 AVHRR Data
Authors: Abuelgasim A , Fraser R
Published: March 2017

This paper presents an investigation of the applicability of NOAA-16/AVHRR (N-16) satellite data for detecting and mapping active wildfires across North American forest ecosystems. Two fire detection algorithms were developed for application to N-16 day and
night-time daily imagery. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. For daytime data collection N-16 provides 3 reflective bands, namely, red, near infrared and short-wave infrared (SWIR), in addition to two thermal brightness temperature
bands centred at 10.8mm and 12mm. During night's time data collection the short-wave infrared band is switched to the thermal brightness temperature band centred at 3.7mm. This band in particular has been extensively used for detecting active fires.
 The fire algorithms have
two major steps: detection of potential fires followed by false fire elimination. The threshold tests developed for fire identification and false fire removal were optimised through a trial-and-error approach using a database of active fire pixels over the whole of North America. The database was
generated from a large number of single-daytime and night-time AVHRR scenes, where the fire pixels were identified visually on the images aided by the associated daytime smoke plumes. The SWIR band was found to be sensitive only to large burning fires leading to a noticeable spike in the measured
reflectance. However, a serious limitation with the SWIR band is that small burning fires are not easily detectable and quite a number of active fires go undetected. Night detection does not pose such a limitation and has allowed for significantly higher detection rates. Overall night detection
provides reasonably good alternative for the reduced sensitivity of the SWIR band.
 The set of day and night algorithms was used to generate daily active fire maps across North America. Such a combined approach for fire detection leads to an improved detection rate.
Selected validation sites in western Canada and the United States, showed reasonable correspondence with the location of fires mapped by the Canadian Forest Service and the USDA Forest Service using conventional means.
Multi-temporal Burned area Mapping Using Logistic Regression Analysis and Change Metrics
Authors: Fraser R , Fernandes R , Latifovic R
Published: March 2017

This paper describes a procedure developed for continental-scale mapping of burned boreal forest at 10-day intervals. The basis of the technique is a multiple logistic regression model applied to 1 km SPOT VEGETATION (VGT) clear-sky composites. Independent
variables consist of multi-temporal change metrics representing 10-day and surrounding 30-day changes in reflectance and in two vegetation indices. The metrics account for seasonal phenological variation by normalizing them to the reflectance trajectory of background vegetation. Three
spatial-contextual tests are applied to the per-pixel logistic model output to remove false burned pixels and increase the sensitivity of detection. The procedure was tested over Canada using conventional fire surveys and burned area statistics from the 1998-2000 fire seasons. The area of falsely
mapped burns was small (2% commission error over two provinces), and most burns larger than 10 km2 were accurately detected and mapped (R2 = 0.90, P<0.005, n = 91). National-level VGT burned areas for 1998-2000 were within 3-17% of fire management agency burned area compiled by
the Canadian Interagency Forest Fire Centre (CIFFC).
Mapping leaf area index heterogeneity over Canada using directional reflectance and anisotropy canopy reflectance models using directional reflectance and anisotropy canopy reflectance models.
Authors: Leblanc S G , Chen J M , White H P , Latifovic R , Fernandes R , Roujean J
-L , Lacaze R
Published: March 2017

Leaf area index (LAI) retrieval from remote sensing is a very active research field. In heterogeneous canopies, simulations with the canopy reflectance model Five-Scale show that nadir view vegetation indices, such as NDVI and Simple Ratio (SR), based on near
infrared and red reflectance are more closely related to the gap fraction at the solar zenith angle than the LAI. The gap fraction is important in canopy light interception. At the solar zenith angle, it can be used to estimate the amount of sunlit LAI. But the knowledge of LAI and foliage
heterogeneity are both needed to estimate shaded leaves that are also important in the carbon cycle. In our previous studies, we developed a methodology to retrieve the foliage heterogeneity, represented by a clumping index, from remote sensing. The retrieval is accomplished with an anisotropy index
using broadband directional reflectance at the hotspot and at the darkspot. The combination of nadir, hotspot, and darkspot views allows the LAI retrieval for a given cover type. However, directional measurements are not usually acquired with the same sun-target-sensor geometry, so the anisotropy
kernel-based Four-scale Linear model for AnIsotropy Reflectance (FLAIR) is used to interpolate the directional reflectance from ADEOS-POLDER data to acquire hotspot and darkspot reflectance at a common geometry in the near infrared band. A landcover map at 1-km based on SPOT-VGT data acquired in
1998 and directional POLDER data acquired over Canada in June 1997, are used to map the clumping index. The results show consistent clumping index values compared to in-situ values, and that SR and the anisotropy index are not correlated to each other, indicating that both indices are related to
different canopy properties.
Path Processing and Block Bundle Adjustment with RADARSAT-1 SAR Images
Authors: Toutin Th , Carbonneau Y , Chénier R
Published: March 2017

Spatio-triangulation process is applied to 15 RADARSAT-SAR fine mode images (5 paths by 3 rows). The paths were acquired over Rocky Mountains, Canada from different look angles (F1 and F4), creating a weak 6° intersection geometry. Precise geometric
correction model and algorithms developed at CCRS were used. Results over 3-image paths and 5-path block gave errors of 20 m and 25-35 m, respectively. These final errors are mainly due to the weak 6°-intersection geometry, but also include the map errors. For better accuracy, the adjacent
paths should have 8° minimum difference in the look angles.
Remotely sensed habitat diversity predicts butterfly species richness and community similarity in Canada
Authors: Kerr J T , Southwood T R E , Cihlar J
Published: March 2017

Although there is no shortage of potential explanations for the large-scale patterns of biological diversity, the hypothesis that energy-related factors are the primary determinants is perhaps most extensively supported, especially in cold-temperate regions. By
using unusually high-resolution biodiversity and environmental data that have not previously been available, we demonstrate that habitat heterogeneity, as measured by remotely sensed land cover variation, explains Canadian butterfly richness better than any energy-related variable we measured across
spatial scales. Although species-richness predictability declines with progressively smaller quadrat sizes, as expected, we demonstrate that most variability (>90%) in butterfly richness may be explained by habitat heterogeneity with secondary contributions from climatic energy. We
also find that patterns of community similarity across Canada are strongly related to patterns of habitat composition but not to differences in energy-related factors. Energy should still be considered significant but its main role may be through its effects on within-habitat diversity and perhaps,
indirectly, on the sorts of habitats that may be found in a region. Effects of sampling intensity and spatial autocorrelation do not alter our findings.
Retrieval of Surface Reflectance from Hyperion Radiance Data
Authors: Staenz K , Neville R A , Clavette S , Landry R , White H P , Hitchcock R
Published: March 2017

Surface Reflectance was retrieved from Hyperion data by a procedure involving data preprocessing steps and atmospheric correction. Several steps are required to remove sensor artifacts in the spectral and spatial domain. These artifacts include a spatial shift in
the short-wave infrared (SWIR) data, an along-track striping, a spatial misalignment of the visible near infrared (VNIR) and SWIR data, and a cross-track spectral (smile/frown) effect. A look-up table approach in combination with the radiance transfer code MODTRAN4.2 was applied to preprocessed
at-sensor radiance data to retrieve surface reflectance. Results indicate that the spectral calibration data provided do not achieve a proper positioning of the bands' centre wavelengths. Wavelength shifts of up to 1 nm in the VNIR and up to 3 nm in the SWIR remain. This can be seen especially at
wavelengths affected by strong gaseous absorptions.
Mine Tailings Characterization Using PROBE Data (Preliminary Results)
Authors: Shang J , Staenz K , Lévesque J , Howarth P
J , Morris B , Lanteigne L
Published: March 2017

Acid Mine Drainage (AMD), caused by mine tailings, poses an environmental threat. AMD control is a major challenge facing the mining industries worldwide. An important initial step towards the reclamation of mine tailings sites is to identify the presence of
sulphide-rich minerals and their spatial distribution. This study investigated the potential of hyperspectral PROBE data for mine tailings characterization over the Copper Cliff's tailings site in northern Ontario, Canada. The results indicated that PROBE data could provide information on locating
oxidation zonations of the tailings. More importantly, it revealed that library mineral spectra could replace the scene-derived endmember spectra to unmix the PROBE image.
Temporal Soil Moisture Estimation of Pastures from Radarsat Data For Applications in Watershed Modelling
Authors: Pultz T J , Sokol J , Deschamps A , Jobin D
Published: March 2017

Estimating the amount of water stored in a soil profile is essential in most water management projects and for assessing the hydrologic state of a basin. It determines infiltration during a rainfall event and controls evapotranspiration between storms. Rarely,
however, are soil moisture data available for model input. In many cases, particularly watershed scale monitoring or modelling, soil moisture is inferred from more easily obtainable hydrologic variables such as rainfall, runoff and temperature.
 As such, there is a strong
need for procedures to estimate soil moisture in a watershed independently from the models. These procedures must provide not only basin average estimates but also the spatial distribution within a basin in order to meet the requirements of emerging distributed models. Active and passive microwave
imagery are both candidate sources for these data. Active SAR imagery, with its high resolution, is particularly attractive for use in areas of mixed land cover.
 This paper addresses the potential of Radarsat to extract information on soil moisture in pastures in a mixed
landcover watershed located in eastern Ontario, Canada. A series of 6 Radarsat Standard Beam Mode 1 images covering the watershed for the period of September 2000 through July 2001 were analyzed in relation to ground observations, weather radar and meteorological conditions. A method was then
developed to produce soil moisture maps for input to a hydrological model.
A Robust Approach for Estimating LAI from Landsat TM/ETM+ Imagery
Authors: Butson C , Fernandes R , Latifovic R , Chen W
Published: March 2017

Leaf area index (LAI) is a quantitative measure of vegetation cover and of use in models of carbon, water and energy budgets. The recent availability of well-calibrated coverages of Landsat ETM+ imagery over large areas offers an opportunity for production of LAI
estimates at fine spatial resolution. Empirical regressions between LAI and selected vegetation indices are applied to propagate uncertainties in calibration and atmospheric correction into LAI retrieval errors. Furthermore, the sensitivity to land cover mixtures is assessed by comparing retrievals
with Landsat scale land cover with a 1km land cover product. A single Canada-wide composite of LAI derived from available Landsat ETM+ imagery is produced.
Defining Shaded Spectra by Model Inversion for Spectral Unmixing of Hyperspectral Datasets - Theory and Preliminary Application
Authors: White H P , Deguise J -C , Schwarz J W , Hitchcock R , Staenz K
Published: March 2017

The potential of using hyperspectral imagery of canopies to retrieve vegetation and soil information using spectral mixture analysis (SMA) techniques has been the focus of several recent studies. The SMA method estimates the proportion of pixel area that can be
attributed to a cover type with a unique spectral profile. Shaded leaf, shaded residue, and shaded soil areas are generally ignored, or treated as equivalent.
 This paper presents a method of determining shaded spectral reflectance profiles for component cover types by
determining the mean multi-scattering ratio (the ratio of shaded-to-sunlit reflectance) and applying that mean to measured sunlit component spectral reflectance. In this method, the multi-scattering ratio is determined by FLAIR model inversion. The resulting component shaded spectral reflectance can
then be used as part of the SMA.
Characterization of Symmetric Scattering Using Polarimetric SARs
Authors: Touzi R , Charbonneau F
Published: March 2017

Cameron's coherent target decomposition (CTD) and classification are discussed in the context of SAR, and the limitations of Cameron's classification are examined. It is shown that these methods may lead to a coarse and misleading scattering segmentation because
of the large radiometric dispersion tolerated in each of the elemental scatterer classes, as well as the implicit assumption on the coherence nature of target scattering. A new method, named the symmetric scattering characterization method (SSCM), is introduced to better exploit the information
provided by the largest target symmetric scattering component, under coherent conditions. The SSCM, which expressed the symmetric scattering in term of the Poincaré sphere angles, permits a better characterization of target symmetric scattering and the generation of coherent scattering
segmentation of much higher resolution, in comparison with Cameron's segmentation.
The Use of Radar Remote Sensing for Identifying Environmental Factors Associated with Malaria Risk in Coastal Kenya
Authors: Kaya S , Pultz T J , Mbogo C M , Beier J
C , Mushinzimana E
Published: March 2017

Malaria remains one of the greatest killers of human beings, particularly in the developing world. The World Health Organization has estimated that over one million cases of Malaria are reported each year, with more than 80% of these found in Sub-Saharan
Africa. The anopheline mosquito transmits malaria, and breeds in areas of shallow surface water that are suitable to the mosquito and parasite development. These environmental factors can be detected with satellite imagery, which provide enhanced spatial and temporal coverage of most of the earth's
surface. The combined use of remote sensing and GIS provides an effective tool for monitoring environmental conditions that are conducive to malaria, and mapping the disease risk to human populations.
 Since many vector-borne diseases such as malaria are prevalent in
tropical areas, persistent cloud cover often presents a challenge to remote sensing operations. Radar remote sensing has the capability of penetrating clouds, providing a solution to the cloud-cover problem often experienced with optical satellite remote sensing. This research investigates the use
of RADARSAT-1 data for monitoring and mapping malaria risk in coastal Kenya. An object-oriented approach to image classification is taken in order to circumvent some of the limitations of traditional pixel-based classification of radar imagery. GIS routines are used to assess how classified land
cover variables relate to the presence and abundance of malaria-carrying mosquitoes and their proximity to populated areas, in order to generate a malaria risk map.
New Calculation Methods of Diurnal Distribution of Solar Radiation and its Interception by Canopy over Complex Terrain
Authors: Wang S , Chen W , Cihlar J
Published: March 2017

The prescription of diurnal radiation distribution and the consideration of topographic impact on canopy radiation interception are often required in ecological modelling studies. The most commonly used methods in current models are the sine-curve assumption for
diurnal radiation distribution and the topographic geometric projection for canopy radiation interception. In this study, the defects of these two methods are examined and two new methods are proposed. The new method for prescribing the diurnal radiation distribution is based on the assumption that
the direct normal radiation and diffusive radiation follow the sine-curve of solar zenith angle. This improvement is particularly important to the modelling strategies of separating canopy leaves into sunlit and shaded. It can also be used to extrapolating daily data to hourly values so that the
short time step models can be applied when only daily data are available. The new method for calculating canopy radiation interception over inclined surfaces is based on the hypothesis that the topographic variation of canopy radiation interception is caused by the variation of sunlit/shaded leaf
area index. This new method gives the same
A Comparison of Automated DEM Extraction Results Using Along-Track ASTER and Across-Track SPOT Stereo Images
Authors: Toutin Th , Cheng P
Published: March 2017

A digital elevation model (DEM) can be extracted automatically from stereo satellite images. During the past decade, the most common satellite data used to extract DEM used was the across-track SPOT. Recently, the addition of along-track ASTER data, which can be
downloaded freely, provides another attractive alternative to extract DEM data. This work compares the automated DEM extraction results using ASTER stereo pair and SPOT stereo pair, over an area of hilly mountains in Drum Mountain, Utah. The result shows that SPOT produces better DEM results in
terms of accuracy and details, if the radiometric variations between the images, taken on subsequent satellite revolutions, are small. Otherwise, ASTER stereo pair is a better choice because of simultaneous along-track acquisition during a single pass. In comparing to the USGS 7.5-minute DEM, the
ASTER and the SPOT extracted DEMs have a standard deviation of 11.6m and 4.6m, respectively.
LAI Measurements in White Beans and Corn Canopies with Two Optical Instruments
Authors: Pacheco A , Bannari A , Staenz K , McNairn H
Published: March 2017

Leaf Area Index (LAI) is a parameter used to describe the percentage of vegetation cover and to estimate productivity or yield of agriculture and forest canopies. LAI can be estimated using different techniques such as destructive sampling, vegetation indices and
optical instruments. This paper investigates LAI measurements in white beans and corn canopies using two optical instruments, the LI-COR LAI-2000 and the Tracing Radiation and Architecture of Canopies (TRAC), a prototype instrument designed by the Canada Centre for Remote Sensing (CCRS). LAI
estimates provided by each instrument are compared and analysed. Also, further investigation is done in regards to the percent crop cover data and LAI values from the LAI-2000 and the TRAC. Preliminary results indicate that LAI measurements with the LAI-2000 and the TRAC do not correlate very well.
It was also found that LAI-2000's LAI estimates correlate better with the percent crop cover than the TRAC. Accordingly, the LAI-2000 provides LAI values that are more accurate than those provided with the TRAC.
3D Mapping with High Resolution Images
Authors: Toutin Th , Chénier R , Carbonneau Y , Alcaïde N
Published: March 2017

High-resolution images, EROS-A1, IKONOS and QuickBird-2 from 2 m to 0.6 m pixel spacing re-spectively, are geometrically processed with a 3D parametric model developed at the Canada Centre for Remote Sensing. A positioning accuracy of one pixel for the
ortho-images can be obtained if 7-10 ground control points (GCPs) used in the 3D parametric model computation are better than 1-pixel accurate (carto-graphic and image coordinates) and if the digital terrain model (DTM) used in the ortho-rectification proc-ess is more accurate than 5-m. When the
GCPs are less accurate (around 3-5 m) 20 are necessary to avoid the error propagation through the 3D parametric model. Furthermore, a DTM is extracted from stereo IKONOS images using automatic image matching. A general accuracy of 6.5 m (68% level of confidence) when compared to an airborne
lidar DTM (0.5 m accurate) is obtained but is correlated with the land covers. However, the accuracy on bare soils improves to 1.5 m (68% level of confidence). Since the sur-face heights are included in DTM, the surface and the height of buildings can be extracted from the stereo IKONOS DTM.
Different methods are proposed, which should used an expert system to integrate a priori information on the buildings in the different processing steps.
Earth Observation for Landslide Assessment: CEOS Report Summary
Authors: Singhroy V , Ohkura H , Glenn N
Published: March 2017

This report provides a summary from the larger CEOS Landslide hazard team report, focusing on EO information requirements for landslide assessment.
Towards integrated Earth sensing: advanced technologies for in situ sensing in the context of Earth observation
Authors: Teillet P M , Gauthier R P , Chichagov A , Fedosejevs G
Published: March 2017

Significant advancements in Earth observation are expected to come about by developing more systematic capabilities for assimilating remote sensing observations and in situ measurements for use in models, at relevant scales, to generate geophysical and biospheric
information products. This paper provides an overview of the role of in situ sensing in the context of integrated Earth sensing. It also defines a framework for taking advantage of intelligent sensor webs based on the converging technologies of micro-sensors, computers, and wireless
telecommunications in support of critical activities such as the monitoring of remote environments, risk assessment and hazard mapping, and renewable resource information management. The knowledge gleaned from integrated Earth sensing has the potential to empower managers and decision makers to act
on critical climate, sustainable development, natural resource, and environmental issues.
Tracing Radiation and Architecture of Canopies TRAC MANUAL Version 2.1
Authors: Leblanc S G , Chen J M , Kwong M
Published: March 2017

TRAC is a new optical instrument for measuring the Leaf Area Index (LAI) and the Fraction of Photosynthetically Active Radiation absorbed by plant canopies (FPAR). TRAC measures canopy 'gap size' distribution in addition to canopy 'gap fraction'. Gap fraction is
the percentage of gaps in the canopy at a given solar zenith angle. It is usually obtained from radiation transmittance. Gap size is the physical dimension of a gap in the canopy. For the same gap fraction, gap size distributions can be quite different.
Estimation of Plant Water Content of Agricultural Canopies Using Hyperspectral Remote Sensing
Authors: Champagne C , Staenz K , Bannari A , White H
P , Deguise J -C , McNairn H
Published: March 2017

Hyperspectral models developed to estimate plant water content have had limited application under field conditions and have not been rigorously validated. A physical model using a spectrum matching technique was applied to hyperspectral data to directly calculate
the canopy equivalent water thickness (EWT) using a look-up table approach. The objective of this study was to test the validity of this algorithm using plant water content information collected under field conditions, and to relate this to the needs of precision agriculture. Image data were
acquired over two experimental test sites in Canada, near Clinton, Ontario and Indian Head, Saskatchewan, using the Probe-1 airborne hyperspectral sensor. Plant biomass samples were collected simultaneously from plots spanning fourteen fields of various crop types (wheat, canola, corn, beans and
peas). The model was validated against EWT estimated from biomass samples. The model predicts EWT in the range found with all crop types pooled together, a root mean squared error (RMSE) of 26.8 % of the average. The model was sensitive to within-crop variability for broad leaf crops such as
peas, corn, and beans (RMSE = 24.4%, 12.0, 21.8%, respectively).The RMSE for canola was relatively high (39.9%) as a result of a poor prediction at low water contents. The model proved a poor predictor of EWT in wheat (RMSE = 69.9%). EWT is related to plant biomass and leaf area
index (LAI).
Towards Integrated Earth Sensing: The Role of In Situ Sensing
Authors: Teillet P M , Gauthier R P , Chichagov A , Fedosejevs G
Published: March 2017

Significant advancements in Earth observation are expected to come about by developing more systematic capabilities for assimilating remote sensing observations and in situ measurements for use in models, at relevant scales, to generate geophysical and biospheric
information products. This paper provides an overview of the role of in situ sensing in the context of integrated Earth sensing. It also defines a framework for taking advantage of intelligent sensorwebs based on the converging technologies of micro-sensors, computers, and wireless
telecommunications in support of critical activities such as the monitoring of remote environments, risk assessment and hazard mapping, and renewable resource information management. The knowledge gleaned from integrated Earth sensing has the potential to empower managers and decision makers to act
on critical climate, sustainable development, natural resource, and environmental issues. The paper also describes early work on a prototype wireless intelligent sensorweb evaluation in the context of watershed management and flood forecasting.