предыдущий|следующий

Inspects and prospects of satellite remote sensing monitoring ability for land surface water in China

  • role： First author第一作者
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

  • Email：huan.li@pku.edu.cn
  • Introduction：李欢，研究方向为遥感水循环、海洋遥感、冰冻圈遥感、遥感大数据挖掘。E-mail： huan.li@pku.edu.cn
LI Huan1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

  • Email：w.wan@pku.edu.cn
  • Introduction：万玮，研究方向为GNSS遥感和湖泊遥感研究。E-mail： w.wan@pku.edu.cn
WAN Wei1*,  
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

JI Rui1,  
  • Affiliation：

    Land Satellite Remote Sensing Application Center,Ministry of Natural Resources, Beijing 100048, China

LI Guoyuan2,  
  • Affiliation：

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

CHEN Xiaona3,  
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

ZHU Siyu1,  
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

LIU Baojian1,  
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

XU Yue1,  
  • Affiliation：

    School of Geography and Information Engineering,China University of Geosciences (Wuhan), Wuhan 430074, China

LUO Zengliang4,  
  • Affiliation：

    Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

WANG Shenglei5,  
  • Affiliation：

    Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China

CUI Yaokui1

реферат

We investigate the worldwide monitoring of land surface water by satellite remote sensing and the corresponding ability of Chinese satellites for the 14th five-year plan under the general goals of the Ministry of Natural Resources of the People’s Republic of China to plan for the new generation of satellites for water resource monitoring. First, this work reviews the current status of the water resource monitoring by the Chinese and international satellites from several perspectives, including liquid surface water (water extent, water level, water volume, water temperature, and water quality), solid surface water (glacier, snow, and frozen ground), and water vapor in the atmosphere. Then, the capability of land natural resources satellites for land surface water monitoring is inspected. Afterward, the ability of water resources monitoring with various types of remote sensing satellites, including optical, laser, RADAR, and gravity satellites, is summarized and analyzed. Advice and suggestions for Chinese satellite planning of water resources monitoring are proposed by concentrating on the current status and the shortage of water resource monitoring with satellite remote sensing in China. The advice and suggestions include planning the observation, technique, product, and service systems. First, a new generation of cloud water resources monitoring satellites combining infrared and active/passive microwaves is recommended to be developed for the observation system. Moreover, the evolution of radar satellites should be accelerated to make up for the deficiency of optical satellites. Altimetry satellites and gravity satellites must be vigorously cultivated. Furthermore, small satellite constellations for water resources monitoring integrating satellite “communication-navigation-remote sensing” should be promoted. Advanced thermal infrared and hyperspectral satellites with strong temporal and spatial resolution are also recommended to be developed. Second, for the technique system, exploring general remote sensing data processing technologies, including data correction/splicing technology and multisensor data fusion technology, are recommended to improve the quality of domestic satellite data for operational water resources monitoring. Moreover, water resource element extraction/retrieval models must be promoted. The techniques for high-quality long-term water resource products should be also developed. Finally, for the service system, providing a dataset-sharing service of the long-term global water cycle flux and storage elements with high spatiotemporal granularity is recommended. Moreover, the overall development of Chinese satellites for water resources monitoring has started from scratch toward boosting, and these natural resource satellites have basic capabilities for water resources survey. Natural resources satellite datasets are abundant. However, nationwide long-term series of water resources data mainly based on domestically made satellites remain lacking. This gap can be improved from two perspectives.Developing operational natural resources retrieval models from the data perspective following the scientific concept of “remote sensing big data + artificial intelligence” is necessary for timely acquisition, processing, distribution, and providing service while ensuring the stability of satellite remote sensing data. It can realize all-time, all-weather, and all-element satellite remote sensing monitoring for natural resources based on cloud services. From the satellite perspective, the next step for on-orbit satellites is to produce application-oriented operational water resource element products, combining multisource satellite data on the premise of improving satellite data quality. For satellites under planning, relevant departments should work closely to establish goals with different priorities under the guidance of scientific and application issues and full consideration of costs.

ключеви́че слова́

Land surface water resources;water resource monitoring by satellite remote sensing;remote sensing big data;satellite plan suggestions

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