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王桥.2021.中国环境遥感监测技术进展及若干前沿问题.遥感学报，25（1）： 25-36
Wang Q. 2021. Progress of environmental remote sensing monitoring technology in China and some related frontier issues. National Remote Sensing Bulletin， 25（1）：25-36
新时期中国环境污染防治和生态文明建设的迫切需求催生了环境遥感监测技术的迅速发展，20多年来，中国环境遥感监测从无到有，从弱到强，逐渐进入到国家生态环境保护的主战场，并成为国家环境管理决策不可或缺的重要技术手段，发挥了关键性支撑作用。面对实行最严格的生态环境保护制度、科学治污、精准治污、依法治污的新形势和新要求，中国环境遥感监测面临前所未有的机遇和挑战。本文首先以环境监测卫星建设和应用为主线，回顾了中国环境遥感监测工作历程；然后从典型关键技术研究概况入手，总结了水环境遥感监测、大气环境监测、生态环境监测关键技术的进展；最后，结合高性能对地观测、大数据等先进技术的发展，对后续环境卫星、生态环境问题遥感主动发现、环境遥感监测大数据、基于深度学习的环境遥感反演等前沿问题进行了探讨，指出了中国环境遥感急需解决的问题和发展方向，并对相关技术的发展和应用前景进行了分析和展望。可以看到，在国家有关部门的高度重视和作者所带领团队及大量相关研究人员的共同努力下，中国已初步建立了环境遥感监测技术体系，并形成了业务化应用能力，以高分辨率探测为核心的新一代环境监测卫星正在得到快速发展，环境专用卫星载荷的技术性能将得到大幅提升，同时，环境遥感机理研究正得到进一步加强，环境遥感监测的精度和效率将得到进一步提升，中国环境遥感监测正在与人工智能、大数据等新技术加速融合，从以数理建模为核心的模型驱动时代进入到以智能感知为特征的数据驱动时代，由此将催生新的环境遥感应用场景和大数据产品不断涌现，推动环境遥感监测向智能感知、智能预警、智能决策、智能服务的方向发展。
The urgent need of environmental pollution prevention and ecological civilization construction in the new period has promoted the rapid development of environmental remote sensing monitoring technology. Over the past 20 years and more
China’s environmental remote sensing monitoring has gradually entered the main battlefield of national ecological and environmental protection from scratch. It has become an indispensable and important technical means for national environmental management and decision making
playing a key supporting role. Faced with the new situation and new requirements of implementing the strictest ecological and environmental protection system
scientific
precise
and law-based pollution control
China’s environmental remote sensing monitoring is faced with unprecedented opportunities and challenges. This paper first reviews the work history of environmental remote sensing monitoring in China with the construction and application of environmental monitoring satellites as the main line. Starting with the research overview of typical key technologies
this paper then summarizes the progress of key technologies of water environment remote sensing monitoring
atmospheric environment monitoring
and ecological environment monitoring. Combined with the development of advanced technologies
such as high-performance Earth observation and big data
the frontier issues of subsequent environmental satellites
active remote sensing discovery of ecological environmental problems
big data of remote sensing monitoring
and environmental remote sensing inversion based on deep learning
are discussed. The problems and development direction of environmental remote sensing in China are pointed out. The development and application prospects of relevant technologies are analyzed and prospected. The national environmental remote sensing monitoring technology system has been successfully established
and the operational capability of environmental remote sensing has been basically formed. These achievements are due to the great attention of relevant national departments and the joint efforts of the author’s team and relevant researchers. A new generation of environmental monitoring satellites featuring high-resolution detection is rapidly developing
The technical performance of the environmental satellite payloads will be greatly improved. The study of environmental remote sensing mechanism is attracting much attention
and the accuracy and efficiency of environmental remote sensing monitoring will be improved. China’s environmental remote sensing monitoring is integrated with artificial intelligence
big data
and other new technologies
and accelerates from the model-driven era centered on mathematical modeling to the data-driven era characterized by intelligent perception. These conditions will give birth to new environmental remote sensing application scenarios and big data products and make environmental remote sensing monitoring develop toward intelligent perception
intelligent warning
intelligent decision
and intelligent service.
生态环境遥感监测高性能环境卫星大数据深度学习
remote sensing monitoring of ecological environmenthigh performance environment satellitebig data of environmental monitoringdeep learning
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