Ranhao Sun

Dr. Ranhao Sun

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2012 in Landscape and Urban Planning
Verified
Journal Article
Closed access
RSRanhao Sun
Ranhao Sun
LCLiding Chen
Liding Chen

1 September 2012 in Ecological Indicators
Verified
Journal Article
Closed access
RSRanhao Sun
Ranhao Sun
ACAilian Chen
Ailian Chen
LCLiding Chen
Liding Chen
YLYihe Lü
Yihe Lü

1 December 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
MXMuqi Xiong
Muqi Xiong
RSRanhao Sun
Ranhao Sun
LCLiding Chen
Liding Chen

1 March 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
XCXian Cheng
Xian Cheng
LCLiding Chen
Liding Chen
RSRanhao Sun
Ranhao Sun
PKPeiru Kong
Peiru Kong

1 June 2019 in Geoderma
Verified
Journal Article
Closed access
MXMuqi Xiong
Muqi Xiong
RSRanhao Sun
Ranhao Sun
LCLiding Chen
Liding Chen

26 May 2023 in Scientific Data
Verified
Journal Article
Open access
PDF file
JLJialei Li
Jialei Li
HHHongbin He
Hongbin He
QZQinghua Zeng
Qinghua Zeng
LCLiding Chen
Liding Chen
RSRanhao Sun
Ranhao Sun
Soil conservation service (SC) is defined as the ability of terrestrial ecosystems to control soil erosion and protect soil function. A long-term and high-resolution estimation of SC is urgent for ecological assessment and land management on a large scale. Here, a 300-m resolution Chinese soil conservation dataset (CSCD) from 1992 to 2019, for the first time, is established based on the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE modelling was conducted based on five key parameters, including the rainfall erosivity (interpolation of daily rainfall), land cover management (provincial data), conservation practices (weighted by terrain and crop types), topography (30 m), and soil properties (250 m). The dataset agrees with previous measurements in all basins (R2 > 0.5) and other regional simulations. Compared with current studies, the dataset has long-term, large-scale, and relatively high-resolution characteristics. This dataset will serve as a base to open out the mechanism of SC variations in China and could help assess the ecological effects of land management policies.