Yuanwei  Qin

Dr. Yuanwei Qin

Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, USA

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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29 April 2021 in Nature Climate Change
Verified
Journal Article
Closed access
PDF file
Yuanwei  Qin Yuanwei Qin
Yuanwei Qin
Xiangming XiaoXiangming Xiao
Xiangming Xiao
Jean-Pierre WigneronJean-Pierre Wigneron
Jean-Pierre Wigneron
PCPhil Ciais
Phil Ciais
MBMartin Brandt
Martin Brandt
BMBerrien Moore
Berrien Moore

26 March 2018 in Proceedings of the National Academy of Sciences
Verified
Journal Article
Open access
PDF file
Zhenhua ZouZhenhua Zou
Zhenhua Zou
Xiangming XiaoXiangming Xiao
Xiangming Xiao
JDJinwei Dong
Jinwei Dong
Yuanwei  Qin Yuanwei Qin
Yuanwei Qin
RDRussell Doughty
Russell Doughty
JWJie Wang
Jie Wang
Significance: Strong variations in open-surface water body areas have impacted United States agriculture, economy, society, and ecosystems. This study presents the uneven water-resource distribution across the contiguous United States with the western half of the United States having less water body area but stronger interannual variability compared with the eastern half. Divergent trends of open-surface water body area in the last three decades, mainly driven by climate, indicated that the water-poor regions of the Southwest and Northwest United States were getting poorer, while the water-rich regions of Southeast and far north Great Plains were getting richer. Surface water body shrinkage in drought years led to massive groundwater mining and the rapid decrease of land water storage in California and the southern Great Plains.

28 October 2021 in Nature Sustainability
Verified
Journal Article
Closed access
PDF file
XWXinxin Wang
Xinxin Wang
Xiangming XiaoXiangming Xiao
Xiangming Xiao
XXXiao Xu
Xiao Xu
ZZZhenhua Zou
Zhenhua Zou
BCBangqian Chen
Bangqian Chen
BLBo Li
Bo Li

29 July 2019 in Nature Plants
Verified
Journal Article
Closed access
Lei FanLei Fan
Lei Fan
Jean-Pierre WigneronJean-Pierre Wigneron
Jean-Pierre Wigneron
PCPhil Ciais
Phil Ciais
JCJérôme Chave
Jérôme Chave
MBMartin Brandt
Martin Brandt
Josep PenuelasJosep Penuelas
Josep Penuelas

5 April 2017 in Water
Verified
Journal Article
Open access
PDF file
YZYan Zhou
Yan Zhou
JDJinwei Dong
Jinwei Dong
Xiangming XiaoXiangming Xiao
Xiangming Xiao
TXTong Xiao
Tong Xiao
ZYZhiqi Yang
Zhiqi Yang
Yuanwei  Qin Yuanwei Qin
Yuanwei Qin
Open surface water bodies play an important role in agricultural and industrial production, and are susceptible to climate change and human activities. Remote sensing data has been increasingly used to map open surface water bodies at local, regional, and global scales. In addition to image statistics-based supervised and unsupervised classifiers, spectral index- and threshold-based approaches have also been widely used. Many water indices have been proposed to identify surface water bodies; however, the differences in performances of these water indices as well as different sensors on water body mapping are not well documented. In this study, we reviewed and compared existing open surface water body mapping approaches based on six widely-used water indices, including the tasseled cap wetness index (TCW), normalized difference water index (NDWI), modified normalized difference water index (mNDWI), sum of near infrared and two shortwave infrared bands (Sum457), automated water extraction index (AWEI), land surface water index (LSWI), as well as three medium resolution sensors (Landsat 7 ETM+, Landsat 8 OLI, and Sentinel-2 MSI). A case region in the Poyang Lake Basin, China, was selected to examine the accuracies of the open surface water body maps from the 27 combinations of different algorithms and sensors. The results showed that generally all the algorithms had reasonably high accuracies with Kappa Coefficients ranging from 0.77 to 0.92. The NDWI-based algorithms performed slightly better than the algorithms based on other water indices in the study area, which could be related to the pure water body dominance in the region, while the sensitivities of water indices could differ for various water body conditions. The resultant maps from Landsat 8 and Sentinel-2 data had higher overall accuracies than those from Landsat 7. Specifically, all three sensors had similar producer accuracies while Landsat 7 based results had a lower user accuracy. This study demonstrates the improved performance in Landsat 8 and Sentinel-2 for open surface water body mapping efforts.

1 September 2016 in Remote Sensing of Environment
Verified
Journal Article
Closed access
YZYao Zhang
Yao Zhang
XXXiangming Xiao
Xiangming Xiao
CJCui Jin
Cui Jin
JDJinwei Dong
Jinwei Dong
SZSha Zhou
Sha Zhou
BMBerrien Moore
Berrien Moore