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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Computer-aided classification for remote sensing in agriculture and forestry in Northern Italy

A set of results concerning the processing and analysis of data from LANDSAT satellite and airborne scanner is presented. The possibility of performing inventories of irrigated crops-rice, planted groves-poplars, and natural forests in the mountians-beeches and chestnuts, is investigated in the Po valley and in an alphine site of Northern Italy. Accuracies around 95% or better, 70% and 60% respectively are achieved by using LANDSAT data and supervised classification. Discrimination of rice varieties is proved with 8 channels data from airborne scanner, processed after correction of the atmospheric effect due to the scanning angle, with and without linear feature selection of the data. The accuracies achieved range from 65% to more than 80%. The best results are obtained with the maximum likelihood classifier for normal parameters but rather close results are derived by using a modified version of the weighted euclidian distance between points, with consequent decrease in computing time around a factor 3.

Dejace, J.↗
NASA NTRS1977

Reindeer range inventory in western Alaska from computer-aided digital classification of LANDSAT data

An inventory of reindeer-range resources was conducted for the USDA Soil Conservation Service of 1.6 million hectares of wildlands in western Alaska using clustering techniques with digital Landsat data. Computer-aided digital analysis produced a provisional map of rangeland types which was used to design the field collection of vegetation and soil types data. This field data facilitated refinement of the inventory map and was used to describe the map units. The informational classes important to range resources were wet, moist and alpine tundra, tidal marsh, brush and open spruce forest. A significant feature of the study was the extraction of acreage figures by administrative boundaries within the study area. In addition to soil and vegetation association map products (at scales of 1:250,000 and 1:63,360) acreage values were tallied from the digital data for each of the four grazing permit areas established by the Bureau of Land Management.

George, T. H.↗
NASA NTRS1974

The ERTS-1 investigation (ER-600): A compendium of analysis results of the utility of ERTS-1 data for land resources management

The results of the ERTS-1 investigations conducted by the Earth Observations Division at the NASA Lyndon B. Johnson Space Center are summarized in this report, which is an overview of documents detailing individual investigations. Conventional image interpretation and computer-aided classification procedures were the two basic techniques used in analyzing the data for detecting, identifying, locating, and measuring surface features related to earth resources. Data from the ERTS-1 multispectral scanner system were useful for all applications studied, which included agriculture, coastal and estuarine analysis, forestry, range, land use and urban land use, and signature extension. Percentage classification accuracies are cited for the conventional and computer-aided techniques.

Erb, R. B.↗
NASA NTRS1974

The ERTS-1 investigation (ER-600). Volume 1: ERTS-1 agricultural analysis

The Agriculture Analysis Team of the Johnson Space Center conducted a 1-year-long investigation of ERTS-1 multispectral data to evaluate how well features of agricultural importance could be detected, identified, and located; and their areal extent measured. Six study areas were selected in cooperation with the U.S. Department of Agriculture. Two basic analytical approaches were used to meet the objectives. The conventional image interpretation technique revealed that a particular color was an indication of the density of vegetative cover, not an indication of crop classification. Computer-aided techniques were used to classify crop types (i.e., small grains, truck farm crops, grasses, summer fallow) to accuracies as high as 95 percent on large (12 hectares or more) well-defined fields. A further breakdown into crop species (wheat, barley, soybeans, oats, corn) reduced the accuracy to 70 to 80 percent for single-date observations.

Erb, R. B.↗
NASA NTRS1974

Mapping soil features from multispectral scanner data

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

Kristof, S. J.↗
NASA NTRS1975

Solar and atmospheric effects on satellite imagery derived from aircraft reflectance measurements

Solar and atmospheric effects on satellite imagery were investigated by measuring terrain reflectance from low-flying aircraft. Radiometric data were recorded over three test sites in California, Georgia, and South Dakota. Radiance from Skylab (EREP) S190A and ERTS-1 (Landsat-1) sensors was linearly correlated with wide-band terrain reflectance. The results support the proposition that the coefficients of the regression equation are the path radiance and a quantity representing the product of total irradiance and beam transmittance at the time of satellite overflight. These coefficients should be useful as linear conversion coefficients for extending spectral signatures in computer-aided classification work on satellite imagery.

Dana, R. W.↗
NASA NTRS1976

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records.

Wiegand, C. L.↗
NASA NTRS1973

Forest and range mapping in the Houston area with ERTS-1

ERTS-1 data acquired over the Houston area has been analyzed for applications to forest and range mapping. In the field of forestry the Sam Houston National Forest (Texas) was chosen as a test site, (Scene ID 1037-16244). Conventional imagery interpretation as well as computer processing methods were used to make classification maps of timber species, condition and land-use. The results were compared with timber stand maps which were obtained from aircraft imagery and checked in the field. The preliminary investigations show that conventional interpretation techniques indicated an accuracy in classification of 63 percent. The computer-aided interpretations made by a clustering technique gave 70 percent accuracy. Computer-aided and conventional multispectral analysis techniques were applied to range vegetation type mapping in the gulf coast marsh. Two species of salt marsh grasses were mapped.

Heath, G. R.↗
NASA NTRS1974

The utility of ERTS-1 data for applications in land use classification

A comprehensive study has been undertaken to determine the extent to which conventional image interpretation and computer-aided (spectral pattern recognition) analysis techniques using ERTS-1 data could be used to detect, identify (classify), locate, and measure current land use over large geographic areas. It can be concluded that most of the level 1 and 2 categories in the USGS Circular no. 671 can be detected in the Houston-Gulf Coast area using a combination of both techniques for analysis. These capabilities could be exercised over larger geographic areas, however, certain factors such as different vegetative cover, topography, etc. may have to be considered in other geographic regions. The best results in identification (classification), location, and measurement of level 1 and 2 type categories appear to be obtainable through automatic data processing of multispectral scanner computer compatible tapes.

Dornbach, J. E.↗
NASA NTRS1973

Development of a computer-aided procedure for the national program of inspection of dams

An effort was undertaken to determine the utility of ERTS-1 MSS data, together with automatic data processing (ADP) techniques, to detect and locate surface water, and transfer the related technology to the Texas Water Rights Commission (TWRC). A test site was selected, ERTS-1 MSS and ancillary data obtained, and existent ADP classification programs applied. During the course of this effort a linear discriminant function was developed. The results were evaluated for potential candidates for a transferable procedure. A computer-aided technique using a linear discriminant function was selected and recommended, for inclusion in an operational system, which met detection and location criteria. Specifically, evaluation of the selected computer-aided procedure for the test site resulted in the detection of 100 percent of areas of surface water 10 acres or greater in areal extent and the geographic location of areas classified as water to a positional accuracy of 1000 feet or closer. The procedure was recommended for inclusion in an operational computer-aided procedure for transfer to TWRC.

Source record↗
NASA NTRS1973

Evaluation and comparison of ERTS measurements of major crops and soil associations for selected sites in the central United States

The author has identified the following significant results. An unsupervised classification was run for an area around Tahoka Lake, Texas. Classes from the unsupervised were correlated with the available ground observations. Unsupervised classes which corresponded to major rangeland composition groups were used as a basis for a classification of most of Lynn County. Three classes of pasture were identified: (1) clear pasture, mostly grasses; (2) mixture of grasses and mesquite; and (3) areas of thick mesquite. In addition, one class called other included lakes and agricultural areas. It was found that differences in rangeland composition could be mapped from spectral data using computer-aided processing techniques. The T Bar Ranch, which surrounds the Double Lakes west of Tahoka, Texas, was chosen as a test area for the classification of rangeland. It was found that the classification was reasonably consistant with the low altitude oblique air photos.

Baumgardner, M. F.↗
NASA NTRS1971

ADP of multispectral scanner data for land use mapping

The advantages and disadvantages of various remote sensing instrumentation and analysis techniques are reviewed. The use of multispectral scanner data and the automatic data processing techniques are considered. A computer-aided analysis system for remote sensor data is described with emphasis on the image display, statistics processor, wavelength band selection, classification processor, and results display. Advanced techniques in using spectral and temporal data are also considered.

Hoffer, R. M.↗
NASA NTRS1974

The ERTS-1 investigation (ER-600). Volume 2: ERTS-1 coastal/estuarine analysis

The Coastal Analysis Team of the Johnson Space Center conducted a 1-year investigation of ERTS-1 MSS data to determine its usefulness in coastal zone management. Galveston Bay, Texas, was the study area for evaluating both conventional image interpretation and computer-aided techniques. There was limited success in detecting, identifying and measuring areal extent of water bodies, turbidity zones, phytoplankton blooms, salt marshes, grasslands, swamps, and low wetlands using image interpretation techniques. Computer-aided techniques were generally successful in identifying these features. Aerial measurement of salt marshes accuracies ranged from 89 to 99 percent. Overall classification accuracy of all study sites was 89 percent for Level 1 and 75 percent for Level 2.

Erb, R. B.↗
NASA NTRS1974

International Symposium on Remote Sensing of Environment, 9th, University of Michigan, Ann Arbor, Mich., April 15-19, 1974, Proceedings. Volumes 1, 2 & 3

The present work gathers together numerous papers describing the use of remote sensing technology for mapping, monitoring, and management of earth resources and man's environment. Studies using various types of sensing equipment are described, including multispectral scanners, radar imagery, spectrometers, lidar, and aerial photography, and both manual and computer-aided data processing techniques are described. Some of the topics covered include: estimation of population density in Tokyo districts from ERTS-1 data, a clustering algorithm for unsupervised crop classification, passive microwave sensing of moist soils, interactive computer processing for land use planning, the use of remote sensing to delineate floodplains, moisture detection from Skylab, scanning thermal plumes, electrically scanning microwave radiometers, oil slick detection by X-band synthetic aperture radar, and the use of space photos for search of oil and gas fields. Individual items are announced in this issue.

Source record↗
NASA NTRS1974

An interdisciplinary analysis of Colorado Rocky Mountain environments using ADP techniques

The author has identified the following significant results. Good ecological, classification accuracy (90-95%) can be achieved in areas of rugged relief on a regional basis for Level 1 cover types (coniferous forest, deciduous forest, grassland, cropland, bare rock and soil, and water) using computer-aided analysis techniques on ERTS/MSS data. Cost comparisons showed that a Level 1 cover type map and a table of areal estimates could be obtained for the 443,000 hectare San Juan Mt. test site for less than 0.1 cent per acre, whereas photointerpretation techniques would cost more than 0.4 cent per acre. Results of snow cover mapping have conclusively proven that the areal extent of snow in mountainous terrain can be rapidly and economically mapped by using ERTS/MSS data and computer-aided analysis techniques. A distinct relationship between elevation and time of freeze or thaw was observed, during mountain lake mapping. Basic lithologic units such as igneous, sedimentary, and unconsolidated rock materials were successfully identified. Geomorphic form, which is exhibited through spatial and textual data, can only be inferred from ERTS data. Data collection platform systems can be utilized to produce satisfactory data from extremely inaccessible locations that encounter very adverse weather conditions, as indicated by results obtained from a DCP located at 3,536 meters elevation that encountered minimum temperatures of -25.5 C and wind speeds of up to 40.9m/sec (91 mph), but which still performed very reliably.

Hoffer, R. M.↗
NASA NTRS1975

Computer-aided analysis of Skylab multispectral scanner data in mountainous terrain for land use, forestry, water resource, and geologic applications

The author has identified the following significant results. One of the most significant results of this Skylab research involved the geometric correction and overlay of the Skylab multispectral scanner data with the LANDSAT multispectral scanner data, and also with a set of topographic data, including elevation, slope, and aspect. The Skylab S192 multispectral scanner data had distinct differences in noise level of the data in the various wavelength bands. Results of the temporal evaluation of the SL-2 and SL-3 photography were found to be particularly important for proper interpretation of the computer-aided analysis of the SL-2 and SL-3 multispectral scanner data. There was a quality problem involving the ringing effect introduced by digital filtering. The modified clustering technique was found valuable when working with multispectral scanner data involving many wavelength bands and covering large geographic areas. Analysis of the SL-2 scanner data involved classification of major cover types and also forest cover types. Comparison of the results obtained wth Skylab MSS data and LANDSAT MSS data indicated that the improved spectral resolution of the Skylab scanner system enabled a higher classification accuracy to be obtained for forest cover types, although the classification performance for major cover types was not significantly different.

Hoffer, R. M.↗
NASA NTRS1973

ERIM progress report on use of ERTS-1 data: Summary report of work on ten tasks

The author has identified the following significant results. Several of the tasks have produced significant results which are summarized: (1) Absolute water depth can be calculated from a ratio of signals from bands MSS 4 and MSS 5. (2) A 13 category terrain feature classification map of Yellowstone National Park has been produced using supervised pattern recognition techniques. (3) ERTS-1 data has been shown to provide a detection and monitoring capability for a number of water quality problems associated with off-shore ocean dumping sites and inland lakes. (4) A corrected ratio of bands MSS-5 and MSS-7 signals has been formed. (5) A concise format has been devised for storing the ratio signatures of geologic rock and mineral materials determined from laboratory reflectance spectra. (6) Results of work in information extraction demonstrate: signal variability exists among ERTS-1 detectors in any one spectral band that will impact users doing quantitative analysis on successive ERTS-1 images; a newly developed computer-aided procedure for correlating ERTS-1 pixels to ground features; the strong influence of atmospheric effects in ERTS-1 data; and area estimation accuracies are better using the ERIM proportion estimation algorithm than for conventional recognition techniques.

Thomson, F. J.↗
NASA NTRS1975

Discriminating coastal rangeland production and improvements with computer aided techniques

The feasibility and utility of using satellite data and computer-aided remote sensing analysis techniques to conduct range inventories were tested. This pilot study was focused over a 250,000 acre site in Galveston and Brazoria Counties along the Texas Gulf Coast. Rectified enlarged aircraft color infrared photographs of this site were used as the ground truth base. The different land categories were identified, delineated, and measured. Multispectral scanner (MSS) bulk data from LANDSAT-1 was received and analyzed with the Image 100 pattern recognition system. Features of interest were delineated on the image console giving the number of picture elements classified; the picture elements were converted to acreages and the accuracy of the technique was evaluated by comparison with data base results for three test sites. The accuracies for computer aided classification of coastal marshes ranged from 89% to 96%.

Reeves, C. A.↗