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Sekhon, R. S.

Publications and source records attributed to Sekhon, R. S..

Relative Accuracy Assessment of LANDSAT-4 MSS and TM Data for Level 1 Land Cover Inventory

Digital data for the Washington, DC scene simultaneously acquired by the LANDSAT-4 Multispectral Scanner (MSS) and the LANDSAT-4 thematic mapper (TM) was compared. Classification success for the TM and MSS data sets was determined by a per pixel comparison with digitized ground verification data (GVD). These GVD were comprised of Level 7 land cover (developed, agriculture, forest, water, wetlands, and barren) for four USGS 7.5 minute topographic quadrangle maps. The relative improvement in classification success for TM was between 11% and 14%, or about a factor of 1.3, for these data. This represents a meaningful improvement in accuracy for Level 7 land cover categorization for TM relative to MSS, particularly when errors of omission and commission were considered.

Middleton, E. M.↗

Relative Accuracy Assessment of LANDSAT-4 MSS and TM Data for Level 1 Land Cover Inventory

Digital data for the Washington, D.C. scene from the LANDSAT-4 Multispectral Scanner (MSS) and the LANDSAT-4 Thematic Mapper (TM) are compared. Classification success for the TM and MSS data sets was determined by a per pixel comparison with digitized ground verification data (GVD). These GVD were comprised of Level I land cover (developed, agriculture, forest, water, wetlands, and barren) for four USGS 7.5-minute topographic quadrangle maps. Classification accuracy was computed as an average value and for each cover type. Accuracy was expressed two ways: (1) as the percent correspondence with GVD (% correct) and (2) as the percent correspondence relative to both the GVD and LANDSAT classification schemes. Errors of omission and commission associated with the LANDSAT classifications were also computed. Specific results are discussed.

Middleton, E. M.↗

Testing the radiometric stability of HCMM thermal infrared data

A study conducted to test the radiometric stability of thermal infrared (TIR) data from the heat-capacity mapping mission (HCMM) satellites is considered. The radiance values associated with various land use and cover types in a regional study area centered on Washington, D.C. are examined. The study shows that for three different day TIR-data sets, the relative ranking of mean thermal values associated with five Level I and three Level II land-use/land-cover categories remains constant over time. Although HCMM predicted temperatures show variability up to 5 C from ground observed temperatures, the thermal measurements recorded by the satellite are fairly stable as indicators of surface temperature. A method for combining HCMM thermal data and Landsat multispectral scanner (MSS) data to improve the classification of Level I land-cover categories, and in particular the separability of urban and nonurban areas is described. A merged HCMM-MSS data set is found to yield the best results in terms of thematic-map accuracy.

Witt, R. G.↗

Using HCMM Thermal Data to Improve Classification of MSS Data

Spectral overlap between urban and rural land use/land cover categories can lead to unacceptable map accuracy levels in the classification of LANDSAT multispectral scanner (MSS) data. The four MSS bands used alone are not always adequate to distinguish among various land uses and cover types having similar spectral responses. The use of thermal data from the Heat Capacity Mapping Mission (HCMM) satellite as a means of improving MSS land cover classification accuracies for urban versus rural categories was investigated. The approaches used to integrate the HCMM data are described.

Witt, R. G.↗