Crop water stress mapping for site-specific irrigation by thermal imagery and artificial reference surfaces

Abstract

Variable-rate irrigation by machines or solid set systems has become technically feasible, however mapping crop water status is necessary to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide such maps in sufficient detail and in a timely way. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high-resolution thermal imagery and artificial reference surfaces. Canopy-related pixels were separated from those of the soil by upper and lower thresholds related to air temperature, and canopy temperatures were calculated from the coldest 33% of the pixel histogram. Artificial surfaces that had been wetted provided reference temperatures for the crop water stress index (CWSI) normalized to ambient conditions. Leaf water potentials of cotton were related linearly to CWSI values with R2 = 0.816. Maps of crop stress level generated from aerial scans of cotton, process tomatoes and peanut fields corresponded well with both ground-based observations by the farm operators and irrigation history. Numeric quantification of stress levels was provided to support decisions to divide fields into sections for spatially variable irrigation scheduling.