Variable rate irrigation machines or solid set systems have become technically feasible; however, crop water status mapping is necessary as a blueprint to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide these maps in sufficient detail and at a timely delivery. 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 the soil by air temperature- related upper and lower thresholds, and canopy temperatures were calculated from the coldest 33% of the pixel histogram. Wetted artificial surfaces provided reference temperatures for crop water stress index (CWSI) normalization to ambient conditions. Cotton leaf water potentials related linearly to CWSI values with R2= 0.816, n=56. Aerial scans of cotton-, process tomatoes-, and peanut field-generated crop stress level maps corresponded well both with ground-based observations by the farm operators and irrigation history. Numeric quantification of stress levels was provided to support sectioning decisions in spatially variable irrigation scheduling.