IMPROVEMENT THE EVAPOTRANSPIRATION ESTIMATES USING REMOTE SENSING TECHNIQUES AND FUZZY REGRESSION

Through the use of remote sensing techniques, multiple regression analysis is related to evapotranspiration computed from two components: thermal infrared and spectral reflectance bands. Improvement the regression analysis with emphasis on the used components is the aim of this research which the vegetation indices is the desired one. In this regard, the performance of Soil Adjusted Vegetation Index (SAVI) in some synoptic stations of East Azarbaijan Province (Ahar, Tabriz and Mianeh stations) was compared with Normalized Difference Vegetation Index (NDVI) performance. Increasing of L in the SAVI calculation caused the increasing of estimated evapotranspiration. The change of vegetation index led to error decreasing for example the value of RMSE decreasing was 14.29% and 9.9% in case of Mianeh and Ahar stations, respectively. The vegetation cover was the main factor in improvement of evapotranspiration estimates using SAVI. The precise estimation of fuzzy regression parameters is more important which the variation of confidence level had no effect on the center of fuzzy number but the increasing of confidence level parameter led to increasing the spread of fuzzy number.