Exploring the Feasibility of Using GNSS Transmissive Signals to Retrieve Near-Surface Soil Salinity
Soil salinity is challenging to measure accurately because soil is highly heterogeneous. This study first explores the feasibility of retrieving near-surface soil salinity using the GNSS transmissive signals received by an antenna shallowly buried underground. Soil salinity is measured by calculating the power attenuation of the signal in the soil received by the underground antenna with respect to the reference antenna mounted above the ground using GNSS Carrier-to-Noise Ratio (CNR) observations. Three-day observations in the Yellow River Delta, a typical saline-alkali land, are used to verify the approach. The results show that GNSS-derived soil salinity across different bands follows the overall trend measured by the laboratory. The GPS L1 and BDS B3 bands exhibit the highest retrieval accuracy, with the Root Mean Square Error (RMSE) being 0.15% and 0.25%, respectively, and achieved an average RMSE of 0.20%. The findings of this study initially show the potential of the proposed GNSS transmission mode to retrieve soil salinity and provide supportive information for the future development of new instruments.
Authors
- Zhi Gong (ORCID: https://orcid.org/0000-0001-9464-5851)
- Jie Zhang (ORCID: https://orcid.org/0000-0001-7821-4808)
- Wencai Ma (ORCID: https://orcid.org/0009-0003-6123-3932)
- Shanwei Liu (ORCID: https://orcid.org/0000-0002-5049-9394)
- Chengjia Liang
- Wei Wan (ORCID: https://orcid.org/0000-0002-7925-1210)
- Xinliang Niu (ORCID: https://orcid.org/0000-0001-7253-2098)
- Ting Yang (ORCID: https://orcid.org/0000-0002-5485-8243)
Institutions
- Hunan University (CN)
- China Academy of Space Technology (CN)
- Peking University (CN)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- China University of Petroleum, East China (CN)
Publication Details
- Journal
- IEEE Geoscience and Remote Sensing Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/lgrs.2025.3568631
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province
- Natural Science Foundation of Shandong Province