长时序大范围内陆水体光学遥感研究进展
Recent research progress on long time series and large scale optical remote sensing of inland water
- 2021年25卷第1期 页码:37-52
纸质出版日期: 2021-01-07
DOI: 10.11834/jrs.20210570
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纸质出版日期: 2021-01-07 ,
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张兵,李俊生,申茜,吴艳红,张方方,王胜蕾,姚月,郭立男,殷子瑶.2021.长时序大范围内陆水体光学遥感研究进展.遥感学报,25(1): 37-52
Zhang B,Li J S,Shen Q,Wu Y H,Zhang F F,Wang S L,Yao Y,Guo L N and Yin Z Y. 2021. Recent research progress on long time series and large scale optical remote sensing of inland water. National Remote Sensing Bulletin, 25(1):37-52
地球表面的江河、湖泊和水库等内陆水体是水资源的主要组成部分,由气候变化和人类活动所引起的内陆水体分布和水质时空变化等问题已成为各国科学家和政府关注的热点。相比常规实地采样监测手段,卫星遥感在长时序、大范围内陆水体监测方面具有重要优势。受到海洋水色遥感理论和方法的推动,同时也得益于内陆水体光学特性数据的不断积累,近年来内陆水体光学遥感研究取得了很大的进展,已经从典型研究区的典型算法实验性研究,拓展到长时序、大范围水体产品生产;从水色遥感算法的科学研究,发展到内陆水体参量时空变化分析和水环境监管决策支持方面。尤其是在水体分布提取、水体遥感数据大气校正、叶绿素a浓度反演、水体颜色监测、浑浊程度监测、营养状态评价、黑臭水体监测、湖冰监测等方面都已经取得了重要进展,形成了一些面向长时序、大范围内陆水体的光学遥感产品。未来,为了进一步提高内陆水体光学遥感的应用效果,需要进一步加强不同类型内陆水体光学特性数据获取和分析工作,完善面向长时序、大范围内陆水体的水色遥感算法。此外,有必要发射面向内陆水体监测的卫星星座,或者在通用陆地卫星星座遥感器设计中兼顾内陆水体的应用需求,从数据源上解决内陆水体光学遥感面临的问题。
Inland water
including rivers
lakes and reservoirs on the earth’s surface
is the main component of water resources. It is related to human life
ecological environment construction and protection
and social and economic sustainable development. The temporal and spatial distribution and variation of inland water body and water quality triggered by climate change and human activities have caused attention of scientists and governments all around the world. Compared with conventional field sampling monitoring methods
remote sensing monitoring has the advantages of long time series and large-scale coverage. There are series of optical remote sensing satellites which mainly based on visible/near-infrared bands and have a long history. In addition to monitor water surface information
they can also obtain water substances information within water. Therefore
optical remote sensing plays a particularly important role in inland water environment monitoring. Compared with the ocean water with simple optical properties
the optical properties of inland water body are more complex and vary greatly with region and season. Moreover
there is a lack of satellite specially designed for inland water
so the water color remote sensing of inland water is more difficult. However
due to the promotion of ocean color remote sensing theory and methods
as well as the continuous accumulation of inland water optical property data
the research of optical remote sensing of inland water has made great progress in recent years. It has developed from the experimental research of typical algorithms in typical study areas to the production of long time series and large-scale water products
and from the scientific research of water color remote sensing algorithm to the geological discovery of spatio-temporal variation of inland water body parameters and finally to provide enhanced decision support to water environment supervision sectors. In particular
important progress has been made in water distribution extraction
atmospheric correction for water body
chlorophyll-a concentration inversion
water color monitoring
water clarity inversion
trophic state evaluation
black and odorous water monitoring
lake ice monitoring
etc.
and some water color remote sensing products for long time series and large-scale inland water bodies have been produced. In the future
in order to further improve the application of optical remote sensing of inland water
it is necessary to further strengthen the acquisition and analysis of optical property data from different types of inland water
and also improve the water color remote sensing algorithms for long time series and large-scale inland water. In addition
to solve the problem of the lack of useful satellite data source
it is necessary to launch satellite constellation specially designed for inland water monitoring
or to consider the needs for inland water monitoring in the sensor design in general land satellite constellation.
内陆水体水色遥感长时序大范围光学遥感
inland waterwater color remote sensinglong time serieslarge-scaleoptical remote sensing
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