Rengui Jiang

Dr. Rengui Jiang

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

View All Publications
12 October 2014 in Natural Hazards
Verified
Journal Article
Closed access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
JXJiancang Xie
Jiancang Xie
Hailong HeHailong He
Hailong He
JLJungang Luo
Jungang Luo
JZJiwei Zhu
Jiwei Zhu

31 October 2015 in Theoretical and Applied Climatology
Verified
Journal Article
Closed access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
TGThian Yew Gan
Thian Yew Gan
JXJiancang Xie
Jiancang Xie
NWNi Wang
Ni Wang
CGChunchao Guo
Chunchao Guo

8 September 2016 in Theoretical and Applied Climatology
Verified
Journal Article
Closed access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
JXJiancang Xie
Jiancang Xie
YZYong Zhao
Yong Zhao
Hailong HeHailong He
Hailong He
GHGuohua He
Guohua He

2 July 2021 in Scientific Reports
Verified
Journal Article
Open access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
Jichao LiangJichao Liang
Jichao Liang
YZYong Zhao
Yong Zhao
HWHao Wang
Hao Wang
JXJiancang Xie
Jiancang Xie
FLFawen Li
Fawen Li
Terrestrial vegetation growth activity plays pivotal roles on regional development, which has attracted wide attention especially in water resources shortage areas. The paper investigated the spatiotemporal change characteristics of vegetation growth activity using satellite-based Vegetation Health Indices (VHIs) including smoothed Normalized Difference Vegetation Index (SMN), smoothed Brightness Temperature (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and VHI, based on 7-day composite temporal resolution and 16 km spatial resolution gridded data, and also estimated the drought conditions for the period of 1982–2016 in Jing-Jin-Ji region of China. The Niño 3.4 was used as a substitution of El Niño Southern Oscillation (ENSO) to reveal vegetation sensitivity to ENSO using correlation and wavelet analysis. Results indicated that monthly SMN has increased throughout the year especially during growing season, starts at approximate April and ends at about October. The correlation analysis between SMN and SMT, SMN and precipitation indicated that the vegetation growth was affected by joint effects of temperature and precipitation. The VCI during growing season was positive trends dominated and vice versa for TCI. The relationships between VHIs and drought make it possible to identify and quantify drought intensity, duration and affected area using different ranges of VHIs. Generally, the intensity and affected area of drought had mainly decreased, but the trends varied for different drought intensities, regions and time periods. Large-scale global climate anomalies such as Niño 3.4 exerted obvious impacts on the VHIs. The Niño 3.4 was mainly negatively correlated to VCI and positively correlated to TCI, and the spatial distributions of areas with positive (negative) correlation coefficients were mainly opposite. The linear relationships between Niño 3.4 and VHIs were in accordance with results of nonlinear relationships revealed using wavelet analysis. The results are of great importance to assess the vegetation growth activity, to monitor and quantify drought using satellite-based VHIs in Jing-Jin-Ji region.

14 January 2016 in International Journal of Biometeorology
Verified
Journal Article
Closed access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
JXJiancang Xie
Jiancang Xie
Hailong HeHailong He
Hailong He
CGChunchao Guo
Chunchao Guo
JZJiwei Zhu
Jiwei Zhu
MYMingxiang Yang
Mingxiang Yang

23 October 2017 in Theoretical and Applied Climatology
Verified
Journal Article
Closed access
PDF file
Rengui JiangRengui Jiang
Rengui Jiang
XYXiang Yu
Xiang Yu
JXJiancang Xie
Jiancang Xie
YZYong Zhao
Yong Zhao
FLFawen Li
Fawen Li
MYMingxiang Yang
Mingxiang Yang