Quantitative remote sensing of water deficit index based on evapotranspiration

Water shortage is already a serious problem in arid North-west China. As an indicator of water shortage, a new surface water deficit index to estimate soil moisture content from optical and thermal spectral information of ASTER imagery based on the surface energy balance was presented in this paper. Compared to models published previously, two improvements have been made: 1) In the vegetation area, to strip effectively the impact of surface soil, the series two-layer was applied to acquiring vegetation latent heat flux parameter in the surface water deficit index model; 2) Because most pixels in the ASTER image are mixed and consist of different types of land cover, to meet the practical needs of a quantitative remote sensing study, genetic inverse algorithm (GIA) was used to realize retrieval of component temperature parameter in the surface water deficit index model. Taking Yingke green land in China for example, field experiments were carried out to validate the developed model. Comparing simulated soil water retrieved by surface water deficit index model with field measured data, the experimental results show that the new method is feasible, which can provide a new way of thinking for retrieval of soil moisture.