Abstract
Remote sensing monitoring of aquatic vegetation is critical to the water quality evaluation of plateau lakes. To obtain a clear understanding of the water environment status of Dianchi Lake, a GF-5 hyperspectral characteristics-based optimal NDVI approach was employed to quantify the aquatic vegetation cover and analyze water quality. By characteristic bands recognition, the optimal NDVI was obtained; the spatial distribution of aquatic plants and water quality in Dianchi Lake were then analyzed. Results showed the following: (1) For Caohai, the optimal NDVI value was calculated by B86 in the red band range and B151 in the near-infrared band range, which achieve the best spectral response. For Waihai, the respective bands were B86 in the red band range and B99 in the near-infrared band range. (2) We also found significant regional differences in aquatic plants distribution for the study area. Caohai was dominated by aquatic plants and high-quality water areas only occurred in the northern tip. While the situation for Waihai was much optimistic, areas with poor water quality were mainly found in the north and south parts. Water quality also showed a descending trend from the lakeside zone to the lake center. (3) By comparing to previous studies, we concluded that policy interventions and water protection measures carried out by the government during the past years are extremely effective. The optimal NDVI method provides a reliable evaluation and is potentially transferable to other plateau lake areas as a robust approach for the rapid assessment of water quality.
Highlights
Eutrophication causes abnormal proliferation of cyanobacteria, which leads to water blooms and further destroys the ecosystem of lake water and seriously affects human health and socioeconomic development [1]
(3) By comparing to previous studies, we concluded that policy interventions and water protection measures carried out by the government during the past years are extremely effective. e optimal Normalized Difference Vegetation Index (NDVI) method provides a reliable evaluation and is potentially transferable to other plateau lake areas as a robust approach for the rapid assessment of water quality
Remote sensing monitoring approaches incorporating the growth of aquatic plants into decision making associated with water quality evaluation, water ecological environment and environmental effects of aquatic plants have been increasingly recognized by scientists and policymakers worldwide [3]
Summary
Eutrophication causes abnormal proliferation of cyanobacteria, which leads to water blooms and further destroys the ecosystem of lake water and seriously affects human health and socioeconomic development [1]. Environmental changes produce pressure on aquatic plants, leading to changes in aquatic plants and ecosystem service functions [2]. Remote sensing monitoring approaches incorporating the growth of aquatic plants into decision making associated with water quality evaluation, water ecological environment and environmental effects of aquatic plants have been increasingly recognized by scientists and policymakers worldwide [3]. Dianchi Lake is one of the 9 lakes in Yunnan-Guizhou Plateau where aquatic plants (e.g., cyanobacteria bloom, etc.) are most likely to occur leading to poor water quality [4]. In the 1990s, it was considered inferior to that of the past; the water environment situation of Caohai was classified as superclass V and that of Waihai was class V [5]. Through the implementation of a series of governance works in Dianchi Lake, the water
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