Debin Song
Chinese Academy of Sciences
11 Papers
8 Citations
Debin Song is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Environmental science & Biomass (ecology). The author has an hindex of 4, co-authored 11 publications.
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Papers
GIS-based health assessment of the marine ecosystem in Laizhou Bay, China.
Debin Song,Zhiqiang Gao,Hua Zhang,Fuxiang Xu,Xiangyu Zheng,Jinquan Ai,Xiaoke Hu,Guopei Huang,Haibo Zhang +8 more
TL;DR: The land-based pollutants that discharge into the sea may be the leading factors that are causing ecological environment deterioration in the Laizhou Bay, and the reclamation work ongoing around the port has exacerbated the ecological risk.
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A UAV and S2A data-based estimation of the initial biomass of green algae in the South Yellow Sea.
TL;DR: An biomass estimation model was proposed for green algae biomass in the radial sand ridge area based on Sentinel-2A image (S2A) and UAV images, and the result showed that the green algae was detected highly accurately with the normalized green-red difference index (NGRDI).
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Analysis of environmental factors affecting the large-scale long-term sequence of green tide outbreaks in the Yellow Sea
TL;DR: Using the Google Earth Engine (GEE) platform, the semi-automatic extraction of green tide information using multi-source satellite data was achieved for the first time in this paper.
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Characteristics and influence of green tide drift and dissipation in Shandong Rongcheng coastal water based on remote sensing
TL;DR: In this paper, the influence of green tides on marine aquaculture in the Rongcheng coastal water (the northernmost sea area influenced by green tide) was analyzed using the MODIS, GaoFen-1 (GF-1) satellite imagery and the sea surface wind (SSW) data.
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Validation of MODIS-based monitoring for a green tide in the Yellow Sea with the aid of unmanned aerial vehicle
TL;DR: In this paper, a comparison between quasi synchronous MODIS images and in situ observation data, as well as an unmanned aerial vehicle (UAV) image was conducted to quantify the uncertainty in mapping of the green tide using MODIS data.
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