TVDI based Soil Moisture Retrieval from Remotely Sensed Data over Large Arid Areas
Temperature Vegetation Dryness Index（TVDI） is an extensively used method for land surface soil moisture retrieval from optical and thermal-infrared remote sensing data.This study adapts the typical TVDI model that was proposed by Sandholt（2002）,to retrieve soil moisture information from TERRA/MODIS data in Xinjiang,west China.Improvements mainly include：① cloud-mask correction and 16-day averaged temperature composition approaches are used to reduce the impacts of clouds in TVDI-based soil moisture inversion;② the problems caused by the topographic,thermal radiation and land-cover differences over a large area are also addressed in the adjusted TVDI model;③ the modeling of TVDI dry edge is also adjusted to reduce the errors in soil moisture retrieval from MODIS data.In-situ measurements in the study area were collected with the soil sampling instrument,and used to derive the model parameters and verify the adjusted model outputs.The result shows that the modified TVDI model can give better estimation of land surface soil moisture from MODIS data in a typical arid area,Xinjiang.
NETL
NSTL
万方数据
维普
