Due to the heterogeneity of land surface features in a large-scale region, this study examines the effectiveness of a multiple models strategy in soil moisture retrieval from MODIS in Xinjiang, and established a robust model for soil moisture retrieval from remote sensing data in arid and semi-arid areas where diverse land surface covers such as bare soil, sparsely vegetated and densely-vegetated lands exist. Specifically, the composed inversion models: ATI-based, TVDI-based and an averaged model were developed and used to estimate land surface soil water content in bare-soil, densely-vegetated and sparsely-vegetated areas, respectively. The models were verified and validated using the in-situ measured data, and the result indicates that, the proposed composite model performed better and achieved more accurate estimate of Xinjiang surface soil moisture than either ATI-based model or TVDI model. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Zhao, J., Zhang, X., & Bao, H. (2011). Soil moisture retrieval from remote sensing data in arid areas using a multiple models strategy. Advances in Intelligent and Soft Computing, 105, 635–644. https://doi.org/10.1007/978-3-642-23756-0_102
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