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At least 271 records · Page 15

Water resources, summary

The application of remote sensing products to the development and understanding of water resources problems is considered. Geology and hydrogeology, analysis of watersheds, snow and ice, prediction of runoff from snowmelt, hydrologic land use classifications, soil moisture, evapotranspiration, flood hazards, and water quality surveys are among the topics discussed. Suggestions for further use of remotely sensed data are given along with increased user requirements.

Simons, D. B.↗

Remote-sensing applications in the State of Mississippi

A computer derived land use classification scheme for infrared LANDSAT imagery was developed and applied to update existing Mississippi coastline data. Inventory classifications were accomplished by photographic enlargement and photointerpretations showing color coded resources on the ground.

Bankston, P. T.↗

Investigation of environmental change pattern in Japan

The author has identified the following significant results. A detailed land use classification for a large urban area of Tokyo was made using MSS digital data. It was found that residential, commercial, industrial, and wooded areas and grasslands can be successfully classified. A mesoscale vortex associated with large ocean current, Kuroshio, which is a rare phenomenon, was recognized visually through the analysis of MSS data. It was found that this vortex affects the effluent patterns of rivers. Lava flowing from Sakurajima Volcano was clearly classified for three major erruptions (1779, 1914, and 1946) using MSS data.

Maruyasu, T.↗

Selecting reconnaissance strategies for floodplain surveys

Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to flood-plain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The digital approach permitted LANDSAT results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas as opposed to areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.

Sollers, S. C.↗

Satellite land use acquisition and applications to hydrologic planning models

A developing operational procedure for use by the Corps of Engineers in the acquisition of land use information for hydrologic planning purposes was described. The operational conditions preclude the use of dedicated, interactive image processing facilities. Given the constraints, an approach to land use classification based on clustering seems promising and was explored in detail. The procedure is outlined and examples of application to two watersheds given.

Algazi, V. R.↗

Digital techniques for processing Landsat imagery

An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

Green, W. B.↗

Landsat-D thematic mapper simulation in an urban area using aircraft multispectral scanner data

A simulation of imagery from the Landsat-D thematic mapper was conducted in order to determine its usefulness for urban land-use classification. Aircraft 24-channel multispectral scanner imagery of the Los Angeles area at 7.5-m resolution was processed digitally by means of matrix averaging and image smoothing techniques to simulate the 30-m resolution of the thematic mapper. Mean and standard deviation statistics of training sites for resolutions of 7.5, 15, 30 and 60 m were used to generate final classification maps. Plots of relative standard deviation showed that for larger training sites, as the resolution decreased, the distribution range of density values also decreased, while plots of relative classification accuracies showed that as resolution decreased, classification accuracies for three levels of standard deviation increased. A point of diminishing returns was indicated, however, confirming the utility of the resolution intended for Landsat-D.

Clark, J.↗

Multispectral Resource Sampler - An experimental satellite sensor for the mid-1980s

An experimental pushbroom scan sensor, the Multispectral Resource Sampler (MRS), being developed by NASA for a future earth orbiting flight is presented. This sensor will provide new earth survey capabilities beyond those of current sensor systems, with a ground resolution of 15 m over a swath width of 15 km in four bands. The four arrays are aligned on a common focal surface requiring no beamsplitters, thus causing a spatial separation on the ground which requires computer processing to register the bands. Along track pointing permits stereo coverage at variable base/height ratios and atmospheric correction experiments, while across track pointing will provide repeat coverage, from a Landsat-type orbit, of every 1 to 3 days. The MRS can be used for experiments in crop discrimination and status, rock discrimination, land use classification, and forestry.

Schnetzler, C. C.↗

Evaluation of large area crop estimation techniques using LANDSAT and ground-derived data

The results of the Domestic Crops and Land Cover Classification and Clustering study on large area crop estimation using LANDSAT and ground truth data are reported. The current crop area estimation approach of the Economics and Statistics Service of the U.S. Department of Agriculture was evaluated in terms of the factors that are likely to influence the bias and variance of the estimator. Also, alternative procedures involving replacements for the clustering algorithm, the classifier, or the regression model used in the original U.S. Department of Agriculture procedures were investigated.

Amis, M. L.↗

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗

Discrimination of unique biological communities in the Mississippi lignite belt

Small scale hardcopy LANDSAT prints were manually interpreted and color infrared aerial photography was obtained in an effort to identify and map large contiguous areas of old growth hardwood stands within Mississippi's lignite belt which do not exhibit signs of recent disturbance by agriculture, grazing, timber harvesting, fire, or any natural catastrophe, and which may, therefore, contain unique or historical ecological habitat types. An information system using land cover classes derived from digital LANDSAT data and containing information on geology, hydrology, soils, and cultural activities was developed. Using computer-assisted land cover classifications, all hardwood remnants in the study area which are subject to possible disturbance from surface mining were determined. Twelve rare plants were also identified by botanists.

Miller, W. F.↗

Updating census urban area maps with LANDSAT data

The use of LANDSAT data for updating census maps of urbanized areas by identification of a fringe of suburban territory to be considered for inclusion within a revised urban area map is described. Methodologies of the application system verification and transfer project are evaluated. These include manual analysis of color photographs, line printer maps, and land cover classifications; change detection using an image differencing routine to depict changes in reflectance values between the two anniversary LANDSAT images; and use of the IBIS/VICAR digital image processing system. Application of IBIS/VICAR to mapping the Orlando, Florida area is described in detail.

Friedman, S. Z.↗

Preliminary results of mapping urban land cover with Seasat SAR imagery

The detectability of urban land cover types is explored using digitally processed Seasat SAR imagery of the Denver, Colorado area. Test sites within the metropolitan area were selected to include a cross section of Anderson, et. al. Level II land cover classes and cover types representative of the urban area growth stages. Using the Image 100 interactive processing system each test site was level sliced in an attempt to define specific reflectance boundaries for each cover type and to determine the spectral and spatial characteristics of homogeneous response regions. The rural-urban fringe boundary was readily definable, but a precise Level I and Level II land cover classification was not possible. High density housing could be separated from low density housing and from parks, but reflectance values were often look angle dependent. Confusion between some water and vegetation responses also posed problems.

Henderson, F. M.↗

LANDSAT landcover information applied to regional planning decisions

Land cover information derived from LANDSAT is being utilized by Piedmont Planning District Commission located in the State of Virginia. Progress to date is reported on a level one land cover classification map being produced with nine categories. The nine categories of classification are defined. The computer compatible tape selection is presented. Two unsupervised classifications were done, with 50 and 70 classes respectively. Twenty-eight spectral classes were developed using the supervised technique, employing actual ground truth training sites. The accuracy of the unsupervised classifications are estimated through comparison with local county statistics and with an actual pixel count of LANDSAT information compared to ground truth.

Dixon, C. M.↗

Ground water use inventory in Minnesota using LANDSAT data

An irrigation ground water use inventory in Sherburne County, Minnesota, was attempted by indirectly locating irrigation wells by determining the location of irrigated lands. Digital classification of LANDSAT MSS imagery was employed using the IDIMS at Goddard Space Flight Center. Single-date classification proved moderately successful after accurate ground truth data were obtained. A combination of supervised and unsupervised classification was used. Multitemporal analysis using August 10 and May 21, 1978 imagery was also attempted. This unsupervised classification proved most successful in identifying crops and irrigated fields.

Beissel, D. R.↗

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.↗

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.↗

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.↗