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A model for retrieving soil moisture saturation with Landsat remotely sensed data

Jian, Ji, Yang, Wunian, Jiang, Hong, Wan, Xinnan, Li, Yuxia, Peng, Li
International journal of remote sensing 2012 v.33 no.14 pp. 4553-4566
Landsat, disasters, drainage water, humus, landslides, models, prediction, remote sensing, rivers, soil types, soil water, vegetation, China
Soil moisture saturation indicates the capability of the vegetation humus layer and the soil layer to reabsorb and drain water in an area; it is crucial in predicting natural disasters, such as landslides and droughts. In this article, a model was created to retrieve soil moisture saturation based on multispectral remotely sensed data. Soil brightness and soil wetness, calculated from the tasseled cap transformation, were utilized to obtain soil moisture saturation. With the above model, a soil moisture saturation map of Maoergai District, which is located on the upper Minjiang River in northern Sichuan Province in the south-west of China, was created from a Landsat Enhanced Thematic Mapper Plus (ETM+) image in July 2002. Then, the soil type data and the vegetation distribution data of the year 2000 were used to evaluate the model. The result shows that the model for soil moisture saturation is viable and that the vegetation type, vegetation distribution and soil type have strong correlation with soil moisture saturation.