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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition

An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

Ormsby, J. P.↗
NASA NTRS1982

Digital overlay of cartographic information on Landsat MSS data for soil surveys

Cartographic soils data were digitized, spatially registered, and merged with processed Landsat image data. The Landsat Multispectral Scanner Subsystem (MSS) image data were used to generate a thematic map representing different soil surface characteristics and an enhanced image. The thematic map was generated using supervised and unsupervised classification procedures. The enhanced image was generated by performing a linear contrast stretch on data altered by a principal components transformation. Although both procedures yielded images useful for soil unit delineation, image enhancement was determined to be more suitable because it was more expedient and inexpensive. Enhanced images cost $0.06 per hectare, spectral classifications cost $0.08 per hectare. The overlay of cartographic data on Landsat data facilitates comparisons between the various processing methods used for soil unit boundary determination, delineation, and verification. This technique also provides for accurate and expedient spatial referencing for field observations and cartographic correlation.

Imhoff, M. L.↗
NASA NTRS1982

The use of large-scale aerial photography for interpreting Landsat digital data in an elk habitat-analysis project

Large-scale aerial photography was used to interpret Landsat multispectral scanner data processed through an unsupervised classifier. After scale adjustment and interpretation by application of an elk-habitat photointerpretation legend, the photographs were registered with the spectral classification, and the co-occurrence of spectral picture elements with photointerpreted habitat classes was tabulated. Analysis of the resulting table of data permitted the description of spectral classes in terms meaningful and useful to elk research and management unit in the Blue Mountains of northeastern Oregon.

Isaacson, D. L.↗
NASA NTRS1982

Cooperative processes in image segmentation

Research into the role of cooperative, or relaxation, processes in image segmentation is surveyed. Cooperative processes can be employed at several levels of the segmentation process as a preprocessing enhancement step, during supervised or unsupervised pixel classification and, finally, for the interpretation of image segments based on segment properties and relations.

Davis, L. S.↗
NASA NTRS1978

LANDSAT image differencing as an automated land cover change detection technique

Image differencing was investigated as a technique for use with LANDSAT digital data to delineate areas of land cover change in an urban environment. LANDSAT data collected in April 1973 and April 1975 for Austin, Texas, were geometrically corrected and precisely registered to United States Geological Survey 7.5-minute quadrangle maps. At each pixel location reflectance values for the corresponding bands were subtracted to produce four difference images. Areas of major reflectance differences are isolated by thresholding each of the difference images. The resulting images are combined to obtain an image data set to total change. These areas of reflectance differences were found, in general, to correspond to areas of land cover change. Information on areas of land cover change was incorporated into a procedure to mask out all nonchange areas and perform an unsupervised classification only for data in the change areas. This procedure identified three broad categories: (1) areas of high reflectance (construction or extractive), (2) changes in agricultural areas, and (3) areas of confusion between agricultural and other areas.

Stauffer, M. L.↗
NASA NTRS1981

Analysis of the Tanana River Basin using LANDSAT data

Digital image classification techniques were used to classify land cover/resource information in the Tanana River Basin of Alaska. Portions of four scenes of LANDSAT digital data were analyzed using computer systems at Ames Research Center in an unsupervised approach to derive cluster statistics. The spectral classes were identified using the IDIMS display and color infrared photography. Classification errors were corrected using stratification procedures. The classification scheme resulted in the following eleven categories; sedimented/shallow water, clear/deep water, coniferous forest, mixed forest, deciduous forest, shrub and grass, bog, alpine tundra, barrens, snow and ice, and cultural features. Color coded maps and acreage summaries of the major land cover categories were generated for selected USGS quadrangles (1:250,000) which lie within the drainage basin. The project was completed within six months.

Morrissey, L. A.↗
NASA NTRS1981

Development and implementation of a low cost micro computer system for LANDSAT analysis and geographic data base applications

Since the implementation of the GRID and IMGRID computer programs for multivariate spatial analysis in the early 1970's, geographic data analysis subsequently moved from large computers to minicomputers and now to microcomputers with radical reduction in the costs associated with planning analyses. Programs designed to process LANDSAT data to be used as one element in a geographic data base were used once NIMGRID (new IMGRID), a raster oriented geographic information system, was implemented on the microcomputer. Programs for training field selection, supervised and unsupervised classification, and image enhancement were added. Enhancements to the color graphics capabilities of the microsystem allow display of three channels of LANDSAT data in color infrared format. The basic microcomputer hardware needed to perform NIMGRID and most LANDSAT analyses is listed as well as the software available for LANDSAT processing.

Faust, N.↗
NASA NTRS1981

Monitoring land conversions from forest/wetland to agriculture

The utility of LANDSAT data in monitoring largescale land clearance and drainage activities in a forest/wetland environment in northern Minnesota was investigated. LANDSAT tapes from 1973, 1978 and 1980 were used in a multitemporal unsupervised land cover classification of the 9 x 15 mile site. Results show quite clearly and in a cost-effective manner, where the greatest activity occurred. It was also possible to integrate the LANDSAT data with other data available through the Land Management Information Center's geographic information system.

Dudding, M. L.↗
NASA NTRS1981

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.

Bloemer, H. H. L.↗
NASA NTRS1981

Mapping sand and gravel pits in the Patuxent River watershed

LANDSAT data from July 1973 and June 1978 for the Patuxent River Watershed of Maryland were processed in an effort to devise an economical method of monitoring the reclamation of sand and gravel pits. ASTEP-II and IDIMS software were utilized to derive signatures for sand and gravel pits and other land use/land cover types. Both unsupervised and supervised classifications of the two data sets were produced. Resultant statistics and color output products were compared in order to determine the extent of reclamation and expansion of sand and gravel pits over the five-year time span and to check the locations of more recent sand and gravel pits. Preliminary results indicate that, for a selected northern sub-acre, signatures derived for sand and gravel pits were nearly 90 percent accurate.

Schmidt, T. J.↗
NASA NTRS1981

Monitoring wetlands change using LANDSAT data

A wetlands monitoring study was initiated as part of Delaware's LANDSAT applications demonstration project. Classifications of digital data are conducted in an effort to determine the location and acreage of wetlands loss or gain, species conversion, and application for the inventory and typing of freshwater wetlands. A multi-seasonal approach is employed to compare data from two different years. Unsupervised classifications were conducted for two of the four dates examined. Initial results indicate the multi-seasonal approach allows much better separation of wetland types for both tidal and non-tidal wetlands than either season alone. Change detection is possible but generally misses the small acreages now impacted by man.

Hardin, D. L.↗
NASA NTRS1983

Integration of environmental and spectral data for sunflower stress determination

Stress in sunflowers was assessed in western and northwestern Minnesota. Weekly ground observations (acquired in 1980 and 1981) were analyzed in concert with large scale aerial photography and concurrent LANDSAT data. Using multidate supervised and unsupervised classification procedures, it was found that all crops grown in association with sunflowers in the study area are spectrally separable from one another. Under conditions of extreme drought, severely stressed plants were differentiable from those not severely stressed, but between-crop separation was not possible. Initial regression analyses to estimate sunflower seed yield showed a sensitivity to environmental stress during the flowering and seed development stages. One of the most important biological factors related to sunflower production in the Red River Valley area was found to be the extent and severity of insect infestations.

Lillesand, T.↗
NASA NTRS1982

A Temporal Approach to Monitor Surface Mine Reclamation Progress via LANDSAT

Using LANDSAT satellite imagery, the mine reclamation process can be studied on a temporal and continuing basis. Not only can the progress of reclamation be readily monitored, but also a breakdown in the mining reclamation process can be detected. In viewing reclamation, it is important to monitor the mined site well past initial revegation stages. With present mining law and bonding procedures, fast revegetational growth is encouraged, often leading to poor soil fertilizing and inappropriate stabilizing species. As a result, the initial reclamation may exhibit good qualities for one or two years but then may experience vegetational deterioration after the state has relinquished the mining company from it's responsibility. It is this small-scale breakdown in the reclamation process that was detected using an unsupervised classification technique with eight-year temporal LANDSAT imagery coverage.

Davis, A. L.↗
NASA NTRS1983

Effect of scene illumination conditions on digital enhancement techniques of multispectral scanner LANDSAT images

Two sets of MSS/LANDSAT data with solar elevation ranging from 22 deg to 41 deg were used at the Image-100 System to implement the Eliason et alii technique for extracting the topographic modulation component. An unsupervised cluster analysis was used to obtain an average brightness image for each channel. Analysis of the enhanced imaged shows that the technique for extracting topographic modulation component is more appropriated to MSS data obtained under high sun elevation ngles. Low sun elevation increases the variance of each cluster so that the average brightness doesn't represent its albedo proprties. The topographic modulation component applied to low sun elevation angle damages rather than enhance topographic information. Better results were produced for channels 4 and 5 than for channels 6 and 7.

Parada, N. D. J.↗
NASA NTRS1982

The effects of seasonal differences in climatic conditions on Landsat spectral signatures and associated land cover classification

Unsupervised classification algorithms are used to analyze Landsat computer-compatible tape data for an area of approximately 840 sq km in central Oklahoma, over the period from June 12 to August 4, 1979. The results obtained show that changes in remotely sensed spectral signatures and land cover classes are associated with a period of transition from moisture availability in late spring to moisture deficit in midsummer, with the latter being marked by greater visible spectrum reflectance and greater near-IR absorption, although each surface cover type has responded differently to the seasonal change in water availability. Consideration of these results has led to the identification of important factors in the use of multidate satellite data in environmental change monitoring. Naturally induced trends in surface albedo introduce noise into studies aimed at identifying anthropogenic land cover change. Specific problems associated with prairie-forest ecotonal areas in the southern Great Plains involve the seasonally induced differences in separability of forest, bush, and grassland cover types.

Harrington, J. A., Jr.↗
NASA NTRS1982

Comparing digital data processing techniques for surface mine and reclamation monitoring

The results of three techniques used for processing Landsat digital data are compared for their utility in delineating areas of surface mining and subsequent reclamation. An unsupervised clustering algorithm (ISOCLS), a maximum-likelihood classifier (CLASFY), and a hybrid approach utilizing canonical analysis (ISOCLS/KLTRANS/ISOCLS) were compared by means of a detailed accuracy assessment with aerial photography at NASA's Goddard Space Flight Center. Results show that the hybrid approach was superior to the traditional techniques in distinguishing strip mined and reclaimed areas.

Witt, R. G.↗
NASA NTRS1983

Performance evaluation of the JPL interim digital SAR processor

The performance of the Interim Digital SAR Processor (IDP) was evaluated. The IDP processor was originally developed for experimental processing of digital SEASAT SAR data. One phase of the system upgrade which features parallel processing in three peripheral array processors, automated estimation for Doppler parameters, and unsupervised image pixel location determination and registration was executed. The method to compensate for the target range curvature effect was improved. A four point interpolation scheme is implemented to replace the nearest neighbor scheme used in the original IDP. The processor still maintains its fast throughput speed. The current performance and capability of the processing modes now available on the IDP system are updated.

Wu, C.↗
NASA NTRS1983

Evaluation of the effects of the seasonal variation of solar elevation angle and azimuth on the processes of digital filtering and thematic classification of relief units

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Two sets of LANDSAT data referring to the orbit 150 and row 28 were selected with illumination parameters varying from 43 deg to 64 deg for azimuth and from 30 deg to 36 deg for solar elevation respectively. IMAGE-100 system permitted the digital processing of LANDSAT data. Original images were transformed by means of digital filtering so as to enhance their spatial features. The resulting images were used to obtain an unsupervised classification of relief units. Topographic variables (declivity, altitude, relief range and slope length) were used to identify the true relief units existing on the ground. The LANDSAT over pass data show that digital processing is highly affected by illumination geometry, and there is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

Parada, N. D. J.↗