{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T22:10:52Z","timestamp":1777587052216,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T00:00:00Z","timestamp":1572480000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global navigation satellite system (GNSS) multipath signals received by a geodetic-quality GNSS receiver can be used to estimate the water content of soil around the antenna. The direct signals from satellite to GNSS antenna are the most valuable signals in geodetic measurement, such as positioning, navigation, GNSS control network, deformation monitoring, and so on. However, the GNSS antenna also captures the reflected signals from the ground, which contain information of surrounding environment, so that useful information about the reflection surface can be inferred by analyzing the reflected signal. This technique is termed as GNSS-interferometric reflectometry. The signal-to-noise ratio (SNR) data recorded by a receiver contains SNR component of reflected signals, which is related to the soil moisture of the ground. The changes of soil moisture content will cause the change of soil permittivity and reflectivity which are the key factors that make further change of the SNR of reflected signals. We used the measured data to evaluate the correlation between amplitude of multipath induced SNR time series and real soil moisture. An improved soil moisture estimation algorithm based on multipath induced SNR amplitude data is proposed in this paper. The performance of the proposed soil moisture estimation method is evaluated using the 15-month data recorded by PBO H2O GNSS station and a 14-day experiment in Wuhan, China. The experimental results show that the estimated soil moisture has a strong correlation with the real soil moisture and the estimation accuracy in terms of root-mean-square error (RMSE) is 0.0345 cm3cm\u22123 and 0.0339 cm3cm\u22123, respectively. Meanwhile, the application scope of the method is given.<\/jats:p>","DOI":"10.3390\/rs11212559","type":"journal-article","created":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T06:33:29Z","timestamp":1572503609000},"page":"2559","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Soil Moisture Estimation by GNSS Multipath Signal"],"prefix":"10.3390","volume":"11","author":[{"given":"Xin","family":"Chang","sequence":"first","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taoyong","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kegen","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4011-2018","authenticated-orcid":false,"given":"Yunwei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiancheng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chongqing Meteorological Bureau, Chongqing 401147, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6385","DOI":"10.1109\/TGRS.2015.2438395","article-title":"Multi-GNSS Meteorology: Real-Time Retrieving of Atmospheric Water Vapor from BeiDou, Galileo, GLONASS, and GPS Observations","volume":"53","author":"Li","year":"2015","journal-title":"IEEE Geosci. 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