Mapping Annual Precipitation across Mainland China in the Period 2001-2010 from TRMM3B43 Product Using Spatial Downscaling Approach
文献类型：期刊论文
| 作者 | Shi, Yuli1; Song, Lei1; Xia, Zhen1; Lin, Yurong1; Myneni, Ranga B.1; Choi, Sungho1; Wang, Lin1; Ni, Xiliang1; Lao, Cailian1; Yang, Fengkai1 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 7期号:5页码:180-194 |
| 通讯作者 | Shi, YL (reprint author), Nanjing Univ Informat Sci & Technol, Sch Geog & Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China. |
| 英文摘要 | Spatially explicit precipitation data is often responsible for the prediction accuracy of hydrological and ecological models. Several statistical downscaling approaches have been developed to map precipitation at a high spatial resolution, which are mainly based on the valid conjugations between satellite-driven precipitation data and geospatial predictors. Performance of the existing approaches should be first evaluated before applying them to larger spatial extents with a complex terrain across different climate zones. In this paper, we investigate the statistical downscaling algorithms to derive the high spatial resolution maps of precipitation over continental China using satellite datasets, including the Normalized Distribution Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Global Digital Elevation Model (GDEM) from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and the rainfall product from the Tropical Rainfall Monitoring Mission (TRMM). We compare three statistical techniques (multiple linear regression, exponential regression, and Random Forest regression trees) for modeling precipitation to better understand how the selected model types affect the prediction accuracy. Then, those models are implemented to downscale the original TRMM product (3B43; 0.25 degrees resolution) onto the finer grids (1 x 1 km(2)) of precipitation. Finally we validate the downscaled annual precipitation (a wet year 2001 and a dry year 2010) against the ground rainfall observations from 596 rain gauge stations over continental China. The result indicates that the downscaling algorithm based on the Random Forest regression outperforms, when compared to the linear regression and the exponential regression. It also shows that the addition of the residual terms does not significantly improve the accuracy of results for the RF model. The analysis of the variable importance reveals the NDVI related predictors, latitude, and longitude, elevation are key elements for statistical downscaling, and their weights vary across different climate zones. In particular, the NDVI, which is generally considered as a powerful geospatial predictor for precipitation, correlates weakly with precipitation in humid regions. |
| 研究领域[WOS] | Remote Sensing |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000357596900005 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38439]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Shi, Yuli 2.Song, Lei 3.Xia, Zhen 4.Lin, Yurong 5.Wang, Lin 6.Yang, Fengkai] Nanjing Univ Informat Sci & Technol, Sch Geog & Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China 7.[Shi, Yuli 8.Ni, Xiliang] Inst Remote Sensing & Digital Earth CAS & Beijing, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 9.[Myneni, Ranga B. 10.Choi, Sungho |
| 推荐引用方式 GB/T 7714 | Shi, Yuli,Song, Lei,Xia, Zhen,et al. Mapping Annual Precipitation across Mainland China in the Period 2001-2010 from TRMM3B43 Product Using Spatial Downscaling Approach[J]. REMOTE SENSING,2015,7(5):180-194. |
| APA | Shi, Yuli.,Song, Lei.,Xia, Zhen.,Lin, Yurong.,Myneni, Ranga B..,...&Yang, Fengkai.(2015).Mapping Annual Precipitation across Mainland China in the Period 2001-2010 from TRMM3B43 Product Using Spatial Downscaling Approach.REMOTE SENSING,7(5),180-194. |
| MLA | Shi, Yuli,et al."Mapping Annual Precipitation across Mainland China in the Period 2001-2010 from TRMM3B43 Product Using Spatial Downscaling Approach".REMOTE SENSING 7.5(2015):180-194. |
入库方式： OAI收割
来源：遥感与数字地球研究所
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