Compared with other remote sensing rainfall products, TRMM rainfall products have been widely used in many regions of the world due to their high accuracy. However, when applied to the regional scale, due to its low spatial resolution (0.25 ° × 0.25 °), it often cannot meet the needs of hydrological and water resources research at the basin scale. Space degradation is an effective way to solve the above problems.
The research team of Jia Shaofeng of the Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, based on the close relationship between rainfall in Qaidam Basin and other environmental factors such as topography and vegetation, established TRMM rainfall data and SRTM DEM and SPOT VEGETATION The regression relationship of the high-resolution remote sensing data finally obtained the annual rainfall data with high spatial resolution (1km × 1km) in Qaidam Basin, and the data were verified by using the data of 6 rainfall sites in the study area. The results show that the spatial statistical degradation model established by the researchers can effectively reflect the annual trend of rainfall in the study area, and has achieved good results.
The research results were published in the journal Remote Sensing of Environment (Jia Shaofeng, Zhu Wenbin, L? Aifeng *, Yan Tingting. A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China. Remote Sensing of Environment, 2011. (12): 3069-3079).
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