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NASA NTRS1982

An evaluation of Seasat SAR imagery for urban analysis

Digitally processed Seasat SAR imagery of the Denver, Colorado, area is analyzed with regard to the types of urban data that can be detected and/or inferred from satellite-borne L-band systems. Black-and-white images of the scene were generated at three scales to determine the advantages and detail discernible at each level of display. The large-scale imagery was density-sliced to evaluate the feasibility of producing a semiautomated land-cover classification from the SAR data. Gray level classes were assigned colors to aid interpretation and subsequently compared with the black-and-white images to assess the contribution of each technique and benefits of combining the data from both procedures.

Henderson, F. M.↗

NASA NTRS1983

Mapping and monitoring renewable resources with space SAR

The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

Ulaby, F. T.↗

NASA NTRS1984

Comparison of Land Cover Information from LANDSAT Multispectral Scanner (MSS) and Airborne Thematic Mapper Simulator (TMS) Data for Hydrologic Applications

Detailed land cover classifications were performed on the Thematic Mapper Simulator (TMS) and MSS data of the Clinton River Basin (acquired on August 19, 1981, and June 28, 1980, respectively) using supervised classification techniques. Differences in interclass separability were compared to select several promising TMS band combinations, selected from the 27 covering the Clinton River Basin. The TMS data produced a more accurate and spatially contiguous classification than MSS for this study site. While the accuracy of the 4-band TM data set was as good as the 7-band, the 3-band TMS data sets were also better than the MSS. These results indicate that both the increased spectral discrimination and spatial resolution contribute to improved classification accuracy. The possibility of reducing the data analysis burden associated with large TM data volumes through effective band selection therefore appears promising. The implications of the improved classification accuracy of TMS data are important for hydrologic and economic modeling. In particular, the higher accuracies for the developed categories (residential and commercial) should improve the predictions of runoff in flood forecasting models and of flood damage for damage calculation models appreciably.

Gervin, J. C.↗

NASA NTRS1983

Integration of Landsat data into the Saginaw River Basin geographic information system

One of the objectives of the Saginaw River Basin study is related to the development of a computer model to predict flood damages. The computer model is to be operational in June 1985. In order to achieve this objective, the input of land-use data into a data base consisting of 198,000 grid cells will be required. A planning technique using Spatial Analysis Methodology (SAM) was developed by the Corps of Engineers Hydrologic Engineering Center (HEC) to systematically handle these data. The HEC-SAM system uses the spatially oriented map data in a series of data management and analysis software programs for input to the Corps hydrologic and environmental models. Attention is given to data base development, Landsat digital data, the placement of the Landsat data into the grid cell data base, and the development of the land cover classification. The Landsat-2 MSS scene covering 85 percent of the Saginaw River Basin was geometrically corrected to a UTM coordinate system.

Mckim, H. L.↗

NASA NTRS1984

An overview of the evolution of Landsat-4

Landsat-4 was launched on July 16, 1982, from Vandenberg Air Force Base in California. This launch culminated over a decade of planning, design, and implementation effort. During this period, many decisions and choices had to be made involving such items as the characteristics of the second-generation observing instrument named the Thematic Mapper (TM), the orbital altitude and coverage pattern, the configuration of the ground processing systems, etc. In total, the design and operation of Landsat-4 depart substantially from those of the successful Landsat 1, 2, and 3 series. Results derived from the operation of Landsat-4 systems and analyses of data products indicate that there have been very significant successes associated with Landsat-4. The TM provides observations that are considerably improved over the Multispectral Scanner (MSS). The middle-infrared bands at 1.6 and 2.2 micrometers, for example, are providing land-cover classification results that meet or exceed expectations. It is now hoped that successful operation of Landsat-4, Landsat-D' (D-prime), and the Tracking and Data Relay Satellite System (TDRSS) will permit the acquisition of a worldwide set of TM and MSS observations.

Salomonson, V. V.↗

NASA NTRS1984

Studies of optical and biological properties of terrestrial land cover using multispectral linear array technology

A series of experiments to study the optical and biological properties of terrestrial land cover are planned for late 1987 using a six-channel imaging spectroradiometer based on newly developed multispectral linear array (MLA) detector technology. Data from selected portions of the Sahel and rain forests of Africa and South America will be used to delineate biomass classes and estimate spherical albedos. A spatial resolution of 15 meters in the four visible-near IR channels and 30 meters in two shortwave IR channels, including a 'new' channel centered at 1.24 micrometers when combined with a spectral width of 20 nm for all channels, will be used to investigate possible improvements in land cover classification. Technology demonstrations include a test of data compression on data quality, the first spaceborne utilization of short wave infrared Schottky barrier Pd2Si detector arrays, and the use of close-butted, multi-array modules with attached spectral filters.

Barnes, W. L.↗

NASA NTRS1984

The analysis of forest policy using Landsat multi-spectral scanner data and geographic information systems

The role of Landsat multi-spectral scanner (MSS) data for forest policy analysis in the state of California has been investigated. The combined requirements for physical, socio-economic, and institutional data in policy analysis were studied to explain potential data needs. A statewide MSS data and general land cover classification was created from which country-wide data sets could be extracted for detailed analyses. The potential to combine point sample data with MSS data was examined as a means to improve specificity in estimations. MSS data was incorporated into geographic information systems to demonstrate modeling techniques using abiotic, biotic, and socio-economic data layers. The review of system configurations to help the California Department of Forestry (CDF) acquire the capability demonstrated resulted in a sequence of options for implementation.

Peterson, D. L.↗

NASA NTRS1986

The effect of Thematic Mapper spectral properties on land cover mapping for hydrologic modeling

The accuracy of unsupervised land-cover classification from all seven Landsat TM bands and from six combinations of three or four bands is evaluated using images of the Clinton River Basin, a suburban watershed near Detroit. Data from aerial TMS photography, USGS topographic maps, and ground surveys are employed to determine the classification accuracy. The mapping accuracy of all seven bands is found to be significantly better (6 percent overall, 12 percent for residential areas, and 13 percent for commercial districts) than that with bands 2, 3, and 4; but almost the same accuracy is obtained by including at least one band from each major spectral region (visible, NIR, and mid-IR).

Gervin, J. C.↗

NASA NTRS1986

Floodplain land cover mapping using Thematic Mapper data

The accuracy of land-cover classifications based on Landsat-4 TM and MSS images (obtained in August 1982) and airborne TMS images (obtained in September 1981) of the New Martinsville, West Virginia area is evaluated by comparison with ground-truth data. TM, TMS, and MSS are found to have overall mapping accuracies 80.1, 78.5, and 75.6 percent; agriculture/grass accuracies 62.0, 29.7, and 46.6 percent; and developed-area accuracies 67.2, 77.8, and 59.4 percent, respectively.

Kerber, A. G.↗

NASA NTRS1986

Discrimination of natural and cultivated vegetation using Thematic Mapper spectral data

The availability of high quality spectral data from the current suite of earth observation satellite systems offers significant improvements in the ability to survey and monitor food and fiber production on both a local and global basis. Current research results indicate that Landsat TM data when used in either digital or analog formats achieve higher land-cover classification accuracies than MSS data using either comparable or improved spectral bands and spatial resolution. A review of these quantitative results is presented for both natural and cultivated vegetation.

Degloria, Stephen D.↗

NASA NTRS1987

Refining image segmentation by polygon skeletonization

A skeletonization algorithm was encoded and applied to a test data set of land-use polygons taken from a USGS digital land use dataset at 1:250,000. The distance transform produced by this method was instrumental in the description of the shape, size, and level of generalization of the outlines of the polygons. A comparison of the topology of skeletons for forested wetlands and lakes indicated that some distinction based solely upon the shape properties of the areas is possible, and may be of use in an intelligent automated land cover classification system.

Clarke, Keith C.↗

NASA NTRS1994

Land Use Patterns and Fecal Contamination of Coastal Waters in Western Puerto Rico

The Department of Environmental Health of the Graduate School of Public Health of the Medical Sciences Campus, University of Puerto Rico (UPR-RCM) conducted this research project on how different patterns of land use affect the microbiological quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Coastal shellfish growing areas, stream and ocean bathing beaches, and pristine marine sites in the Bay are affected by the discharge of the three study rivers. Satellite imagery was used to study watershed land uses which serve as point and nonpoint sources of pathogens affecting stream and coastal water users. The study rivers drain watersheds of different size and type of human activity (including different human waste treatment and disposal facilities). Land use and land cover in the study watersheds were interpreted, classified and mapped using remotely sensed images from NASA's Landsat Thematic Mapper (TM). This study found there is a significant relationship between watershed land cover and microbiological water quality of rivers flowing into Mayaguez Bay in Western Puerto Rico. Land covers in the Guanajibo, Anasco, and Yaguez watersheds were classified into forested areas, pastures, agricultural zones and urban areas so as to determine relative contributions to fecal water contamination. The land cover classification was made processing TM images with IDRISI and ERDAS software.

Norat, Jose↗

NASA NTRS2000

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

Spruce, Joseph↗

NASA NTRS2004

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1'(approximately 10 km) and coarser resolution equal-angle grids, and are computed for the first seven MODIS wavelengths, ranging from 0.47 through 2.1 microns, and for three broadband wavelengths, 0.3-0.7,0.3-5.0 and 0.7-5.0 microns.

King, Michael D.↗

NASA NTRS2006

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

King, Michael D.↗

NASA NTRS2006

An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

Hong, Yang↗

NASA NTRS2007

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.

Adler, Robert↗

NASA NTRS2007

Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.

Adler, Robert↗