7 Papers
23 Citations
Yan Shen is an academic researcher from China Meteorological Administration. The author has contributed to research in topics: Precipitation & Rain gauge. The author has an hindex of 4, co-authored 7 publications. Previous affiliations of Yan Shen include Nanjing University of Information Science and Technology.
Chat about Author
Papers
A new satellite-based monthly precipitation downscaling algorithm with non-stationary relationship between precipitation and land surface characteristics
TL;DR: In this article, a new downscaling algorithm was proposed by introducing a regional regression model termed as geographically weighted regression (GWR) to explore the spatial heterogeneity of the precipitation-NDVI and precipitation-DEM relationships.
163
Evaluation of the IMERG version 05B precipitation product and comparison with IMERG version 04A over mainland China at hourly and daily scales
Shiguang Xu,Yan Shen,Zheng Niu +2 more
TL;DR: In this article, the performance of IMERG 05B is assessed at the hourly and daily scales against dense rain gauge measurements in mainland China from May to September 2015, and a comparison between IMERG version 04A (IMERG 04A) and IMERG 5B is introduced to test whether it can provide better precipitation estimates.
17
Understanding the dependence of the uncertainty in a satellite precipitation data set on the underlying surface and a correction method based on geographically weighted regression
Shiguang Xu,Zheng Niu,Yan Shen +2 more
TL;DR: In this article, the authors investigated the correlation between the errors in satellite precipitation data sets and the underlying surface and found that 39.4% and 50.5% of the variance of the Bias and Ɛ, respectively, could be explained by the digital elevation model, the normalized difference vegetation index and land s...
9
•Journal Article
Estimation models for vegetation water content at both leaf and canopy levels
Yan Shen,Zheng Niu,Chunyan Yan +2 more
TL;DR: Soil-adjusted water index (SAWI) was proposed at the first time to indicate the information of near-infrared and short-wave infrared canopy reflectance and could dramatically eliminate the soil background, and effectively retrieve the vegetation Cw at canopy level.
6