Title :
Soil moisture retrieval using RADARSAT-2 and HJ-1 CCD data in grassland
Author :
Minfeng Xing ; Binbin He ; Xiaowen Li ; Xingwen Quan
Author_Institution :
Sch. of Resources & Environ., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
A synergistic method of SAR and optical remote sensing data for retrieval of soil moisture was developed in this paper. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. Backscattering coefficients were simulated using the established backscattering model. Then, soil moisture was estimated using the inverted model. The results showed that the predicted soil moisture correlated with the measured soil moisture (R2 = 0.7075, RMSE = 3.3219 m2/m2).
Keywords :
remote sensing; soil; synthetic aperture radar; vegetation mapping; HJ-1 CCD data; RADARSAT-2 data; SAR synergistic method; backscattering coefficient; backscattering model; bare soil area; grassland; inverted model; optical data estimation; optical remote sensing data; predicted soil moisture correlation; soil moisture measurement; soil moisture retrieval; total backscattering; vegetation coverage; Backscatter; Optical scattering; Optical sensors; Soil moisture; Synthetic aperture radar; Vegetation mapping; Integral Equation Method; Soil moisture; Water Cloud Model; grassland;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947164
