文献类型： 外文期刊
作者： Yang, G. -J. 1 ; Zhao, C. -J. 1 ; Huang, W. -J. 1 ; Wang, J. -H. 1 ;
作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing, Peoples R China
2.Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing Applicat, Beijing, Peoples R China
3.Beijing Normal Univ, Beijing 100875, Peoples R China
期刊名称：HYDROLOGY AND EARTH SYSTEM SCIENCES （ 影响因子：5.748； 五年影响因子：6.45 ）
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收录情况： SCI
摘要： Soil moisture links the hydrologic cycle and the energy budget of land surfaces by regulating latent heat fluxes. An accurate assessment of the spatial and temporal variation of soil moisture is important to the study of surface biogeophysical processes. Although remote sensing has proven to be one of the most powerful tools for obtaining land surface parameters, no effective methodology yet exists for in situ soil moisture measurement based on a Bidirectional Reflectance Distribution Function (BRDF) model, such as the Hapke model. To retrieve and analyze soil moisture, this study applied the soil water parametric (SWAP)-Hapke model, which introduced the equivalent water thickness of soil, to ground multi-angular and hyperspectral observations coupled with, Powell-Ant Colony Algorithm methods. The inverted soil moisture data resulting from our method coincided with in situ measurements (R~2 Combining double low line 0.867, RMSE Combining double low line 0.813) based on three selected bands (672 nm, 866 nm, 2209 nm). It proved that the extended Hapke model can be used to estimate soil moisture with high accuracy based on the field multi-angle and multispectral remote sensing data.
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