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Water Quality Parameter Retrieval with GF5-AHSI Imagery for Dianchi Lake (China)
In response to the rapid changes in the chlorophyll-a concentration and eutrophication issues in lakes, with Dianchi Lake as an example, a remote sensing estimation model for chlorophyll-a, total phosphorus, and total nitrogen in Dianchi Lake was constructed using the three band method and ratio band method based on the visible-light shortwave infrared (AHSI) hyperspectral satellite data from Gaofen 5 (GF-5) and the water quality data collected at Dianchi Lake. The model results were compared with the multispectral data from the Gaofen 1 (GF-1) wide field-of-view (WFV) camera. The accuracy evaluation results indicate that the overall mean absolute percentage error of the remote sensing estimation models for chlorophyll a, total phosphorus, and total nitrogen are 7.658%, 4.511%, and 4.577%, respectively, which can meet the needs of lake water quality monitoring and evaluation. According to the remote sensing simulation results, chlorophyll a is mainly distributed in the northern part of Dianchi Lake, with phosphorus and nitrogen pollution throughout Dianchi Lake and relatively more abundant in the central and southern regions. The pollution is mainly concentrated in the northern and southern regions of Dianchi Lake, which is consistent with the actual situation. Further confirming the feasibility of using GF-5 satellite AHSI data for water quality parameter retrieval can provide new technical means for relevant departments to quickly and efficiently monitor the inland lake water environment.
Water Quality Parameter Retrieval with GF5-AHSI Imagery for Dianchi Lake (China)
In response to the rapid changes in the chlorophyll-a concentration and eutrophication issues in lakes, with Dianchi Lake as an example, a remote sensing estimation model for chlorophyll-a, total phosphorus, and total nitrogen in Dianchi Lake was constructed using the three band method and ratio band method based on the visible-light shortwave infrared (AHSI) hyperspectral satellite data from Gaofen 5 (GF-5) and the water quality data collected at Dianchi Lake. The model results were compared with the multispectral data from the Gaofen 1 (GF-1) wide field-of-view (WFV) camera. The accuracy evaluation results indicate that the overall mean absolute percentage error of the remote sensing estimation models for chlorophyll a, total phosphorus, and total nitrogen are 7.658%, 4.511%, and 4.577%, respectively, which can meet the needs of lake water quality monitoring and evaluation. According to the remote sensing simulation results, chlorophyll a is mainly distributed in the northern part of Dianchi Lake, with phosphorus and nitrogen pollution throughout Dianchi Lake and relatively more abundant in the central and southern regions. The pollution is mainly concentrated in the northern and southern regions of Dianchi Lake, which is consistent with the actual situation. Further confirming the feasibility of using GF-5 satellite AHSI data for water quality parameter retrieval can provide new technical means for relevant departments to quickly and efficiently monitor the inland lake water environment.
Water Quality Parameter Retrieval with GF5-AHSI Imagery for Dianchi Lake (China)
Hang Zhang (author) / Wenying Hu (author) / Yuanmei Jiao (author)
2024
Article (Journal)
Electronic Resource
Unknown
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