Spatial statistics of TRMM precipitation in the Tibetan Plateau using random forest algorithm
Binren XU1,2, Yuanyuan WEI1,2()
1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China 2. University of Chinese Academy of Sciences, Beijing 100049, China
So far, precipitation products with high spatial resolution have been crucial for the basin scale hydrology, meteorology and ecology. The climate in the Tibetan Plateau is of vital significance to global climate variation. So, the study of the distribution of precipitation with high spatial resolution is in the basic position of environmental science. Based on random-forest algorithm, the authors introduced environmental factors such as topography and vegetation, which was developed for downscaling the remote sensing precipitation products accurately and effectively. The non-linear spatial statistical downscaling model was demonstrated with the Tropical Rainfall Measuring Mission (TRMM) 3B43 dataset with the spatial resolution of 0.25°, the Normalized Difference Vegetation Index (NDVI) from NOAA-AVHRR with the spatial resolution of 8km, the Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM) with the spatial resolution of 90 m and the information of slope, aspect, longitude and latitude. And the model based on time series and vegetation factor, which was demonstrated with TRMM3B43 annual data in order to forecast the precipitation, was introduced in this paper. The downscaling results were validated by applying the observations from the rain gauges in the Tibetan Plateau and the coefficient of determination R2 is 0.89. The analytical results showed that the downscaling results improved the spatial resolution and accuracy by applying the random-forest algorithm and introducing environmental factors. And the model, which was developed for forecasting the precipitation, captured the trends in inter-annual variability and the magnitude of annual precipitation with the R2 ranging from 0.81 to 0.87.
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Binren XU, Yuanyuan WEI. Spatial statistics of TRMM precipitation in the Tibetan Plateau using random forest algorithm. Remote Sensing for Land & Resources, 2018, 30(3): 181-188.
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2018, Vol. 30 
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