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16 May 2011 Research of soil moisture retrieval in arid region on the moistureshed scale
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Soil moisture is an indispensable parameter of water, heat and carbon cycle processes in the earth surface system, and plays a key role in the formation of run-off in arid areas. The retrieval of regional-scale soil moisture is significant in the monitoring of crop growth and drought in arid regions, and in the modeling of global climatic dynamic surface processes. The use of multi-source remote sensing data in the soil moisture retrieval can improve the accuracy of reversion and generally over perform the use of a single remote sensing data due to that the data acquired by different remote sensors can provide complementary information about the soil moisture. The co-reversion of multi-source remotely sensed data is a cutting-edge technique for soil moisture retrieval. This study tries to optimize and adjust the existing reversion models available for different land cover types. A co-reversion scheme model will be designed and used to retrieve soil moisture of different vegetation types of the arid area by using MODIS and AMSR-E remote sensing data. The downscaling strategy and field verification will be used to analyze the accuracy, uncertainty and sensitivity of the reversion models. The popularity and regionality of the model will be also examined to explore the possibility of the model used for large-scale and dynamic monitoring of soil moisture.
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Qing Zhang and Kefa Zhou "Research of soil moisture retrieval in arid region on the moistureshed scale", Proc. SPIE 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, 80291D (16 May 2011);


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