Abstract
Studies in the midwestern United States have shown that crop variations associated with regionally varying environmental factors can be important to crop inventory design using Landsat multispectral scanner data. This study examined the consequences of a more complex environment and a higher resolution sensor. Unsupervised classification accuracy and divergence of crop spectra were determined for six crop classes from early season Landsat Thematic Mapper (TM) scenes for 31 sites across New York State. These indicators of crop separability were related to 12 environmental variables. Although statistically significant models were found for individual crops, no significant relationship was found to characterize general crop separability. Regional variation is too large to be ignored in an early season TM-based inventory of areas as complex as New York; however, stratification based on readily obtainable environmental data is of only moderate value in describing the variation.
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