A real-time crop classification system for evapotranspiration estimates in irrigated areas

One of the approaches of estimating crop evapotranspiration over large areas using remote sensing is the use of canopy reflectance (vegetation indices) derived from multi-temporal satellite imagery to estimate and update evapotranspiration crop coefficients. When this method is applied after the irrigation season is over, a spectral crop classification using one or more of the images can be conducted to produce a crop type map of the entire area, allowing the application of the appropriate crop coefficients on a field-by-field basis. However, if the application is to be run in real-time during an irrigation season using satellite images as they become available, a different classification scheme is required as early season images might not be optimally suited for a traditional spectral classification. This paper presents a real-time method of classification based on a combination of spectral classification and logic using the prior knowledge of the crop types and growth curves in the region. The method is applied to images acquired every two weeks over the 2004 irrigation season at the Lebrija Irrigation District on the Guadalquivir River in Southern Spain. Ground truth information was provided by the local irrigation district.