Key points are not available for this paper at this time.
This study focuses on the use of Landsat image‐processing techniques to produce cropland and crop type statistics for input into agricultural water demand prediction procedures currently being employed by the Kern County Water Agency in Kern County, California. The potential of remote sensing to provide input to the Kern County Water Agency's groundwater basin model in a more accurate and timely fashion is the goal of the research discussed herein. Current accuracies associated with Landsat cropland/noncropland identifications are of the order of 98% absolute accuracy. These data are being operationally incorporated into model calculations on a quarterly basis. Crop specific accuracies, although somewhat lower, are steadily being improved, and prospects for eventual incorporation appear good.
Estes et al. (Sat,) studied this question.