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地表水环境遥感监测关键技术与系统
引用本文:张兵,李俊生,申茜,吴艳红,张方方,王胜蕾.地表水环境遥感监测关键技术与系统[J].中国环境监测,2019,35(4):1-9.
作者姓名:张兵  李俊生  申茜  吴艳红  张方方  王胜蕾
作者单位:中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094,中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094,中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094,中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094,中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094,中国科学院遥感与数字地球研究所,数字地球重点实验室,北京100094
基金项目:中国科学院战略性先导科技专项(XDA19080304)
摘    要:介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取;提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列;发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性;构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测;在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。

关 键 词:水体分布提取  水量估算  水质参数反演  水环境遥感监测系统
收稿时间:2019/3/21 0:00:00
修稿时间:2019/5/23 0:00:00

Key Technologies and Systems of Surface Water Environment Monitoring by Remote Sensing
ZHANG Bing,LI Junsheng,SHEN Qian,WU Yanhong,ZHANG Fangfang and WANG Shenglei.Key Technologies and Systems of Surface Water Environment Monitoring by Remote Sensing[J].Environmental Monitoring in China,2019,35(4):1-9.
Authors:ZHANG Bing  LI Junsheng  SHEN Qian  WU Yanhong  ZHANG Fangfang and WANG Shenglei
Institution:Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China,Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China,Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China,Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China,Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China and Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China
Abstract:This paper introduces some key technologies and systems of remote sensing monitoring of surface water environment and their typical applications. Its representative models and applications mainly come from some recent progress made by the Hyperspectral Remote Sensing Team of the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. An automatic remote sensing extraction method of water distribution based on improved bimodal method is established, which realizes simple, efficient and high precision water extraction. A method for estimating long-time series water volume of large lakes is proposed. Taking the lake area of the Qinghai-Tibet Plateau as an example, the area, water level and water volume series of typical lakes are reconstructed. A method for estimating long-time series water volume of large lakes is proposed. Taking the lake area of the Qinghai-Tibet Plateau as an example, the area, water level and water volume series of typical lakes are reconstructed. The retrieving method of chlorophyll-a concentration in typical inland water based on soft-classification was developed, and a semi-analytical retrieving method of suspended matter concentration in highly turbid water based on bio-optical model was constructed, which improved the regional and seasonal applicability of the retrieving methods. A remote sensing monitoring method for nutrient status and transparency of large-scale lakes and reservoirs based on water color index was constructed. It was the remote sensing monitoring of nutrient status of large-scale lakes and reservoirs in the world and monitoring of transparency of national large-scale lakes and reservoirs were realized. On this basis, a surface water environment remote sensing monitoring system is developed, which improves the efficiency of water environment remote sensing monitoring and promotes the high-precision operational application of satellite remote sensing in water environment monitoring.
Keywords:water distribution extraction  water volume estimation  water quality parameter inversion  remote sensing monitoring system for water environment
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