A new model for surface soil moisture retrieval from CBERS-02B satellite imagery in karst area

Most of the surface soil moisture (SSM) models developed in recent decades are not for karst area where the surface soil is thin. Consequently, this paper presents a novel algorithm for retrieval of the SSM on the basis of “Optical Vegetation Coverage” for CBERS-02B imagery. Jili village in a typical karst area is chosen as the study area, and the retrieved SSM by Landsat TM satellite imagery is chosen for evaluating the accuracy of the proposed model. It shows that the relative accuracy of the mean SSM overall reachs up to 91.26%, and the correlation coefficient R is up to 0.8. Moreover, the R of the rocky desertification land and the dry land even reaches more than 0.9. With these experimental results, it can be demonstrated that the proposed model based on CBERS-02B satellite imagery has a high precision in the retrieval of SSM in karst area.