CROP type analysis using Landsat digital data

Abstract

Classification and statistical sampling techniques for crop type discrimination using Landsat digital data have been developed by the University of California in cooperation with NASA and the California Department of Water Resources. Ratioed bands (MSS 7/5 and 5/4) and a sun-angle corrected Euclidean albedo band were prepared from data for the Sacramento Valley for five different dates. The test area was stratified into general crop groupings based on the particular patterns of irrigation timing for each crop. Data classified within each stratum were used to produce a crop type map. Comparison with ground data indicates that certain crops and crop groups are discernable. Small grains and rice are easily identifiable, as are deciduous fruit varieties as a group. However, it is not feasible to separate various fruit and nut varieties, or separate vegetable crops with these techniques at present.