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Spatial Differentiation Analysis of Water Quality in Dianchi Lake Based on GF-5 NDVI Characteristic Optimization
Journal of Spectroscopy ( IF 2 ) Pub Date : 2021-08-26 , DOI: 10.1155/2021/5542126
Hu Lin 1 , Gan Shu 1, 2 , Yuan Xiping 2, 3 , Li Yan 1 , Chen Guokun 1 , Gao Sha 1
Affiliation  

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.

中文翻译:

基于GF-5 NDVI特征优化的滇池水质空间分异分析

水生植被遥感监测是高原湖泊水质评价的关键。为清楚了解滇池水环境状况,采用基于GF-5高光谱特征的最优NDVI方法对水生植被覆盖进行量化并分析水质。通过特征波段识别,得到最优的NDVI;分析了滇池水生植物的空间分布和水质。结果表明:(1)对于草海,最佳NDVI值由红波段范围内的B86和近红外波段范围内的B151计算,获得了最佳的光谱响应。对于外海,红波段范围为B86,近红外波段为B99。(2) 我们还发现研究区的水生植物分布存在显着的区域差异。草海以水生植物为主,优质水域仅出现在北端。外海的情况虽然乐观,但水质较差的地区主要集中在北部和南部。水质也从湖滨区向湖心区呈下降趋势。(3) 与以往的研究相比,我们得出结论,政府在过去几年中实施的政策干预和水保护措施非常有效。最佳 NDVI 方法提供了可靠的评估,并且有可能作为快速评估水质的可靠方法转移到其他高原湖泊地区。草海以水生植物为主,优质水域仅出现在北端。外海的情况虽然乐观,但水质较差的地区主要集中在北部和南部。水质也从湖滨区向湖心区呈下降趋势。(3) 与以往的研究相比,我们得出结论,政府在过去几年中实施的政策干预和水保护措施非常有效。最佳 NDVI 方法提供了可靠的评估,并且有可能作为快速评估水质的可靠方法转移到其他高原湖泊地区。草海以水生植物为主,优质水域仅出现在北端。外海的情况虽然乐观,但水质较差的地区主要集中在北部和南部。水质也从湖滨区向湖心区呈下降趋势。(3) 与以往的研究相比,我们得出结论,政府在过去几年中实施的政策干预和水保护措施非常有效。最佳 NDVI 方法提供了可靠的评估,并且有可能作为快速评估水质的可靠方法转移到其他高原湖泊地区。水质较差的地区主要分布在北部和南部。水质也从湖滨区向湖心区呈下降趋势。(3) 与以往的研究相比,我们得出结论,政府在过去几年中实施的政策干预和水保护措施非常有效。最佳 NDVI 方法提供了可靠的评估,并且有可能作为快速评估水质的可靠方法转移到其他高原湖泊地区。水质较差的地区主要分布在北部和南部。水质也从湖滨区向湖心区呈下降趋势。(3) 与以往的研究相比,我们得出结论,政府在过去几年中实施的政策干预和水保护措施非常有效。最佳 NDVI 方法提供了可靠的评估,并且有可能作为快速评估水质的可靠方法转移到其他高原湖泊地区。
更新日期:2021-08-26
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