Theretrieval of Vegetation Water Content based on ASTER Images in Middle of Heihe River Basin

Abstract

Vegetation Water Content(VWC)is one of the main limiting factors of affecting growth of plants,which is an important parameter to character vegetation physiological status and morphology.Quantitative estimation of VWC by utilizing remote sensing technology has important significances for agricultural drought monitoring,crop yield estimation and scientific research.In this paper,six periods ASTER images and ground-based measurements of VWC at 11 sampling sites are used to develop the empirical inversion model of VWC,which are obtained during the Heihe Watershed Allied Telemetry Experimental Research(Hi-WATER)in 2012.The four types of vegetation indexes(NDVI,RVI,SAVI,and MSAVI)are adopted in this study.We analyze the relationship between different vegetation indexes and the measured VWC,then develop and validate these VI-based empirical models for VWC retrieval.Results show that the correlation is very high between the measured VWC and the selected four vegetation indexes(R20.846).It indicates that we can retrieve VWC with high accuracy by using the four types of vegetation indexes.Among these vegetation indexes,the MSAVI-based retrieval model achieves the highest accuracy and the root mean square error(RMSE)is only 0.794kg/m2.The study also prove that the developed VWC retrieval model with MSAVI is reliable and an effective way for monitoring spatial variation of regional VWC.