Genetic Algorithm for Assimilating Remotely Sensed Evapotranspiration Data using a Soil-Water-Atmosphere-Plant Model - Implementation Issues

要旨

Monitoring agricultural activities has benefited so much over the last 20 years from the advances in remote sensing (RS). Nowadays, operational algorithms are available to calculate evapotranspiration (ET) calculation at pixel level, which is an important state variable for agricultural and water management studies. Since these algorithms are based on thermal and visible information, their success of implementation depends highly on clear sky conditions. Oftentimes, agricultural managers monitoring requirements may not always match with the availability of satellite images in terms of spatial and temporal resolutions. Supplementing the RS data with high spatial and temporal resolution synthetic datasets is a promising option in this case.