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Chen Lin

Researcher at Chinese Academy of Sciences

Publications -  30
Citations -  517

Chen Lin is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Watershed & Eutrophication. The author has an hindex of 10, co-authored 27 publications receiving 269 citations. Previous affiliations of Chen Lin include Ministry of Land and Resources of the People's Republic of China.

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Carbon and nitrogen burial in a plateau lake during eutrophication and phytoplankton blooms.

TL;DR: Evaluating the response of the organic carbon accumulation rate (OCAR) to eutrophication and algal blooms over the past hundred years in Dianchi Lake found the high loss rate of OC and organic nitrogen leads to a long-term burial efficiency of only 10% and 5%, however, this efficiency can still lead to an increase in OCAR by a factor of 4.
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A New Method for Modifying Thresholds in the Classification of Tree Models for Mapping Aquatic Vegetation in Taihu Lake with Satellite Images

TL;DR: Three spectral features were selected to develop a CT model for identifying aquatic vegetation in Taihu Lake and two methods to modify CT model thresholds to adjust the traditional CT models based on image date were tested to determine if the results would enable us to map and classify aquatic vegetation for periods when no ground-based data.
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Impacts of future climate change and different management scenarios on water-related ecosystem services: A case study in the Jianghuai ecological economic Zone, China

TL;DR: In this article, the authors analyzed the impact of future climate change and land management scenarios on water-related ecosystem services by 2030 in the Jianghuai Ecological Economic Zone (JHEEZ).
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Detection of sensitive soil properties related to non-point phosphorus pollution by integrated models of SEDD and PLOAD

TL;DR: In this paper, an integrated model for the analysis of both dissolved P and particulate P loads, applied to the Meiliang Bay watershed, Taihu Lake, China, was developed.
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The refined spatiotemporal representation of soil organic matter based on remote images fusion of Sentinel-2 and Sentinel-3

TL;DR: The spatiotemporal dynamics of SOM highlighted the necessity of modeling with fused remote sensing images, and more effective modeling could be expected with the continued increase in SOM in future.