Spaceborne GNSS Reflectometry for Vegetation and Inland Water Monitoring: Progress, Challenges, Opportunities, and Potential

Global navigation satellite system reflectometry (GNSS-R) uses the reflection characteristics of navigation satellite signals reflected from the earth’s surface to provide an innovative tool for remote sensing, especially for monitoring surface and atmospheric environmental variables, such as wind speed, soil moisture, vegetation, and sea ice parameters. This paper focuses on the current application and future potential of spaceborne GNSS-R in vegetation remote sensing and the retrieval of inland water environmental and physical parameters. This paper reviews the technical progress of GNSS-R in detail, from early feasibility studies to multiple application examples at this stage, from the United Kingdom Disaster Monitoring Constellation (UK-DMC) satellite in 2003 to other recent GNSS-R missions. These cases demonstrate the unique advantages of GNSS-R in terms of global coverage, low cost, and real-time monitoring. This paper explores the application of GNSS-R technology in vegetation parameters and inland water monitoring, especially its potential in vegetation parameters and surface water monitoring applications. The article also mentioned that the accuracy and efficiency of parameter retrieval can be significantly improved by improving models and algorithms, such as using neural networks and data fusion technology. Finally, the article points out the future direction of spaceborne GNSS-R technology in vegetation remote sensing and the retrieval of inland water environment and physical parameters, including expanding its application areas to a broader range of environmental monitoring and resource management. It emphasized its essential role in monitoring the global ecosystem and monitoring water resources.

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Publication Details

Journal
Remote Sensing
Published
2025-03-27
DOI
https://doi.org/10.3390/rs17071199
Citations
3
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
2.40

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article

Spaceborne GNSS Reflectometry for Vegetation and Inland Water Monitoring: Progress, Challenges, Opportunities, and Potential

Jiyang Xie, Jinwei Bu, Huan Li, Qiulan Wang
3 citations
Remote Sensing
Soil Moisture and Remote Sensing
2.40
article

Spaceborne GNSS Reflectometry for Vegetation and Inland Water Monitoring: Progress, Challenges, Opportunities, and Potential

Jiyang Xie, Jinwei Bu, Huan Li, Qiulan Wang
article en
3 citations

Abstract

Global navigation satellite system reflectometry (GNSS-R) uses the reflection characteristics of navigation satellite signals reflected from the earth’s surface to provide an innovative tool for remote sensing, especially for monitoring surface and atmospheric environmental variables, such as wind speed, soil moisture, vegetation, and sea ice parameters. This paper focuses on the current application and future potential of spaceborne GNSS-R in vegetation remote sensing and the retrieval of inland water environmental and physical parameters. This paper reviews the technical progress of GNSS-R in detail, from early feasibility studies to multiple application examples at this stage, from the United Kingdom Disaster Monitoring Constellation (UK-DMC) satellite in 2003 to other recent GNSS-R missions. These cases demonstrate the unique advantages of GNSS-R in terms of global coverage, low cost, and real-time monitoring. This paper explores the application of GNSS-R technology in vegetation parameters and inland water monitoring, especially its potential in vegetation parameters and surface water monitoring applications. The article also mentioned that the accuracy and efficiency of parameter retrieval can be significantly improved by improving models and algorithms, such as using neural networks and data fusion technology. Finally, the article points out the future direction of spaceborne GNSS-R technology in vegetation remote sensing and the retrieval of inland water environment and physical parameters, including expanding its application areas to a broader range of environmental monitoring and resource management. It emphasized its essential role in monitoring the global ecosystem and monitoring water resources.

Remote SensingVol. 17(7)
Kunming University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Soil Moisture and Remote Sensing
2.40
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