High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations.

Haifeng Tian, Jian Wang, Jie Pei, Yaochen Qin, Lijun Zhang, Yongjiu Wang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Haifeng TianKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education/College of Environment and Planning, Henan University, Kaifeng 475001, China.

Jian WangDepartment of Geography, The Ohio State University, Columbus, OH 43210, USA.

Jie PeiSchool of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519000, China.

Yaochen QinKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education/College of Environment and Planning, Henan University, Kaifeng 475001, China.ORCID 0000-0002-6962-8838

Lijun ZhangKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education/College of Environment and Planning, Henan University, Kaifeng 475001, China.

Yongjiu WangKey Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions of Ministry of Education/College of Environment and Planning, Henan University, Kaifeng 475001, China.

Funding

Project funded by China Postdoctoral Science Foundation 2019M662478

6 · The paper itself

Abstract

Accurately quantifying spatiotemporal changes in surface water is essential for water resources management, nevertheless, the dynamics of Poyang Lake surface water areas with high spatiotemporal resolution, as well as its responses to climate change, still face considerable uncertainties. Using the time series of Sentinel-1 images with 6- or 12-day intervals, the Sentinel-1 water index (SWI), and SWI-based water extraction model (SWIM) from 2015 to 2020 were used to document and study the short-term characteristics of southwest Poyang Lake surface water. The results showed that the overall accuracy of surface water area was satisfactory with an average of 91.92%, and the surface water area ranged from 129.06 km

Indexed as

Google Earth EnginePoyang Lakeremote sensingSentinel-1surface waterSWI

Identifiers

PMID32872219

DOI10.3390/s20174872

PMCPMC7506707

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