{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T22:00:50Z","timestamp":1770328850064,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T00:00:00Z","timestamp":1654560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Foundation of the United Laboratory of Numerical Earthquake Forecasting","award":["2021LNEF01"],"award-info":[{"award-number":["2021LNEF01"]}]},{"name":"Open Foundation of the United Laboratory of Numerical Earthquake Forecasting","award":["42074024"],"award-info":[{"award-number":["42074024"]}]},{"name":"Open Foundation of the United Laboratory of Numerical Earthquake Forecasting","award":["41672192"],"award-info":[{"award-number":["41672192"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021LNEF01"],"award-info":[{"award-number":["2021LNEF01"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42074024"],"award-info":[{"award-number":["42074024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41672192"],"award-info":[{"award-number":["41672192"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Seasonal variations in the vertical Global Positioning System (GPS) time series are mainly caused by environmental loading, e.g., hydrological loading (HYDL), atmospheric loading (ATML), and nontidal oceanic loading (NTOL), which can be synthesized based on models developed by various institutions. A comprehensive comparison among these models is essential to extract reliable vertical deformation data, especially on a regional scale. In this study, we selected 4 HYDL, 5 ATML, 2 NTOL, and their 40 combined products to investigate their effects on seasonal variations in vertical GPS time series at 27 GPS stations in Yunnan, southwest China. These products were provided by the German Research Center for Geosciences (GFZ), School and Observatory of Earth Sciences (EOST), and International Mass Loading Service (IMLS). Furthermore, we used the Cross Wavelet Transform (XWT) method to analyze the relative phase relationship between the GPS and the environmental loading time series. Our result showed that the largest average Root-Mean-Square (RMS) reduction value was 1.32 mm after removing the deformation associated with 4 HYDL from the vertical GPS time series, whereas the RMS reductions after 5 ATML and 2 NTOL model corrections were negative at most stations in Yunnan. The average RMS reduction value of the optimal combination of environmental loading products was 1.24 mm, which was worse than the HYDL (IMLS_GEOSFPIT)-only correction, indicating that HYDL was the main factor responding for seasonal variations at most stations in Yunnan. The XWT result showed that HYDL also explained the annual variations reasonably. Our finding implies that HYDL (IMLS_GEOSFPIT) contributes the most to the environmental loading in Yunnan, and that the ATML and NTOL models used in this paper cannot be effective to correct seasonal variations.<\/jats:p>","DOI":"10.3390\/rs14122741","type":"journal-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T23:55:24Z","timestamp":1655078124000},"page":"2741","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Comprehensive Analysis of Environmental Loading Effects on Vertical GPS Time Series in Yunnan, Southwest China"],"prefix":"10.3390","volume":"14","author":[{"given":"Shunqiang","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Earth and Space Sciences, South University of Science and Technology of China, Shenzhen 518055, China"}]},{"given":"Kejie","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Earth and Space Sciences, South University of Science and Technology of China, Shenzhen 518055, China"}]},{"given":"Hai","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Earth and Space Sciences, South University of Science and Technology of China, Shenzhen 518055, China"}]},{"given":"Changhu","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Earth and Space Sciences, South University of Science and Technology of China, Shenzhen 518055, China"}]},{"given":"Tan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}]},{"given":"Zhenyu","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}]},{"given":"Qian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Earthquake Science, China Earthquake Administration, Beijing 100036, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6590","DOI":"10.1002\/2015GL064665","article-title":"Evolution of unrest at Laguna del Maule volcanic field (Chile) from InSAR and GPS measurements, 2003 to 2014","volume":"42","author":"Feigl","year":"2015","journal-title":"Geophys. 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