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

被引:0
|
作者
Li H. [1 ]
Wan W. [1 ]
Ji R. [1 ]
Li G. [2 ]
Chen X. [3 ]
Zhu S. [1 ]
Liu B. [1 ]
Xu Y. [1 ]
Luo Z. [4 ]
Wang S. [5 ]
Cui Y. [1 ]
机构
[1] Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing
[2] Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing
[3] State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing
[4] School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan
[5] Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
land surface water resources; remote sensing big data; satellite plan suggestions; water resource monitoring by satellite remote sensing;
D O I
10.11834/jrs.20220576
中图分类号
学科分类号
摘要
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. © 2023 National Remote Sensing Bulletin. All rights reserved.
引用
收藏
页码:1554 / 1573
页数:19
相关论文
共 131 条
  • [51] Li Y, Gao H L, Zhao G, Tseng K H, A high-resolution bathymetry dataset for global reservoirs using multi-source satellite imagery and altimetry, Remote Sensing of Environment, 244, (2020)
  • [52] Li Y H, Ding J L, Yan R H, Extraction of small river information based on China-made GF-1 remote sense images, Resources Science, 37, 3, pp. 408-416, (2015)
  • [53] Liang S L, Bai R, Chen X N, Cheng J, Fan W J, He T, Jia K, Jiang B, Jiang L M, Jiao Z T, Liu Y B, Ni W J, Qiu F, Song L L, Sun L, Tang B H, Wen J G, Wu G P, Xie D H, Yao Y J, Yuan W P, Zhang Y G, Zhang Y Z, Zhang Y T, Zhang X T, Zhao T J, Zhao X, Review of China's land surface quantitative remote sensing development in 2019, Journal of Remote Sensing, 24, 6, pp. 618-671, (2020)
  • [54] Liao A P, Chen L J, Chen J, He C Y, Cao X, Chen J, Peng S, Sun F D, Gong P, High-resolution remote sensing mapping of global land water, Science China Earth Sciences, 57, 10, pp. 2305-2316, (2014)
  • [55] Liu B, Wang Y, Lou Z S, Zhan W, The MODIS PWV correction based on CMONOC in Chinese mainland, Acta Geodaetica et Cartographica Sinica, 48, 10, pp. 1207-1215, (2019)
  • [56] Liu B J, Wan W, Xie H J, Li H, Zhu S Y, Zhang G Q, Wen L J, Hong Y, A long-term dataset of lake surface water temperature over the Tibetan Plateau derived from AVHRR 1981- 2015, Scientific Data, 6, 1, (2019)
  • [57] Liu S Y, Yao X J, Guo W Q, Xu J L, Shangguan D H, Wei J F, Bao W J, Wu L Z, The contemporary glaciers in China based on the second chinese glacier inventory, Acta Geographica Sinica, 70, 1, pp. 3-16, (2015)
  • [58] Luojus K, Pulliainen J, Takala M, Lemmetyinen J, Moisander M, GlobSnow v3.0 snow water equivalent (SWE), (2020)
  • [59] Ma X Q, Lu S L, Ma J, Zhu L P, Lake water storage estimation method based on topographic parameters: a case study of Nam Co Lake, Remote Sensing for Land and Resources, 31, 4, pp. 167-173, (2019)
  • [60] MacCallum S N, Merchant C J, Surface water temperature observations of large lakes by optimal estimation, Canadian Journal of Remote Sensing, 38, 1, pp. 25-45, (2012)