Temperature and vegetation indices based surface soil moisture estimation: A remote sensing data approach

Abstract

In environmental and agricultural modelling soil moisture condition is one of the main parameter. To estimate surface soil moisture using an operational algorithm at fine spatial and temporal resolutions (thermal and optical sensors) with the help of Ts(Land Surface Temperature)/VI(Vegetation Index) space based triangle method. Theoretical solutions of dry and wet edges were derived from this method. Based on this method we calculated Soil Moisture Index using more than 8 images for year from 2007 to may 2011 for a part of Murrumbidgee catchment in southern new south wales, Australia. Insitu Soil moisture data for 20 agricultural stations were used for validating the satellite observed Soil Moisture Index. The Results indicated that the general pattern of the SMI variation follows the trend of field soil moisture measurement. Different soil backgrounds influenced the SMI computing using optical satellite image. Estimation of regional soil moisture in areas with less ground information (insitu observations) is achieved with the help of SMI model.