This work provides a description of the research conducted to assess methods for the discrimination between irrigated and rainfed open-tree canopies using advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite imagery and discrete anisotropic radiative transfer (DART) radiative transfer 3D simulation model. Summer and winter ASTER images were acquired over a study area in southern Spain during a 6-year period. A total of 1076 olive orchards were monitored in this area, gathering the field location, field area, tree density, and whether the field was drip irrigated or rainfed. Surface temperature images from ASTER were estimated using the temperature and emissivity separation (TES) method. A panchromatic ortho-rectified imagery dataset collected over the entire area at 0.5 m resolution was used to estimate orchard vegetation cover for each field. Results for summer ASTER thermal images showed differences between irrigated and rainfed orchards of up to 2 K for fields with the same percentage cover, decreasing the differences in ASTER winter images. An approach based on a cumulative index using temperature and the normalized difference vegetation index (NDVI) information for the 6-year ASTER time-series was capable of detecting differences between irrigated and rainfed open-canopy orchards, obtaining 80% success on field-to-field assessments. The method considered that irrigated orchards with equal vegetation cover would yield lower temperature and NDVI than rainfed orchards; an overall accuracy of 75% and a kappa (k) of 0.34 was obtained with a supervised classification method using visible, near infrared and temperature information for the 6-year ASTER imagery series. These experimental ASTER results were confirmed with DART radiative transfer 3D model used to simulate the influence of vegetation cover, leaf area index (LAI) and background temperature on the irrigated and rainfed orchard temperature at the ASTER pixel size
