Satellite imagery can support water planning in the Central Valley

Abstract

Most agricultural systems in California's Central Valley are purposely flexible and intentionally designed to meet the demands of dynamic markets such as corn, tomatoes and cotton. As a result, crops change annually and semiannually, which makes estimating agricultural water use difficult, especially given the existing method by which agricultural land use is identified and mapped. A minor portion of agricultural land is surveyed annually for land-use type, and every 5 to 8 years the entire valley is completely evaluated. We explore the potential of satellite imagery to map agricultural land cover and estimate water usage in Merced County. We evaluated several data types and determined that images from the Moderate Resolution Imaging Spectrometer (MODIS) onboard NASA satellites were feasible for classifying land cover. A technique called "supervised maximum likelihood classification" was used to identify land-cover classes, with an overall accuracy of 75% achievable early in the growing season.