Guijun Yang^a*^,b, Chunjiang Zhao^a, Wenjiang Huang^a ,Jihua Wang^a

^aBeijing Research Center for Information Technology in Agriculture,Beijing, 100097, P.R.China;

^bState Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Application of Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101, P.R.China;

Abstract

Radar data has important implications in agricultural fields monitoring, particularly in the retrieval of the crop height, leaf area index (LAI) and soil moisture information. The objective of this study was to estimate soil moisture contents based on RADARSAT-2 synthetic aperture radar (SAR) data acquired over wheat fields. The study area is a relatively flat agricultural region located in Qingyuan county (Longitude: 115°23′E, Latitude: 38°43′N), Hebei province, China. The area was mainly covered by winter wheat and villages. To obtain inversed soil moisture information from RADARSAT-2 data for the wheat fields based on the Water-Cloud and Oh models, a prior estimation of the wheat heights and wheat water contents is required. New empirical relationships were obtained by regression analysis of the co-polarized correlation coefficient and the ratio of the absolute value of the cross polarization to the wheat height with respect to wheat heights and wheat water contents.

The soil moisture inversion algorithm was based on semi-empirical backscattering models and the prior estimation of wheat heights and wheat water contents from RADARSAT-2 data. The co-polarized correlation coefficient and the ratio of the absolute value of the cross polarization to the crop height were analyzed with respect to variations in wheat height and wheat water content. The results showed average relative errors of 14%, 32% and 24% for the retrieval of wheat height, wheat water content and soil moisture, respectively.