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Abstract
This paper compares digital, multi-spectral imagery from the Landsat 5 Thematic Mapper with that of the Landsat 7
Enhanced Thematic Mapper when used to discriminate crop types for area estimation. Comparisons are done for
different types of crop areas in several states, using images that are only one day apart. The overlaps between
adjacent paths in several major crops states are used to define the analysis areas. A simple non-parametric paired
sample sign test is used to determine statistical significance of differences. Standardized techniques as used in the
Agency's Cropland Data Layer Project are used for image processing, including a modified supervised pattern
recognition /clustering approach for cover type signatures and maximum likelihood for categorization. Ground truth
data consist of 211 one and two square mile areas selected in a stratified random sample and visited in June of the
corresponding crop year. Sampling rates for the ground data range from one in 30 to one in 166 depending on the
state and land use stratum.