{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T10:29:13Z","timestamp":1786357753239,"version":"build-2736575974"},"reference-count":31,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,9]],"date-time":"2026-08-09T00:00:00Z","timestamp":1786233600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fujian Provincial Natural Science Foundation Guiding Project","award":["2024Y0057"],"award-info":[{"award-number":["2024Y0057"]}]},{"name":"Fujian Construction Science and Technology Research and Development Project","award":["2025-K-66"],"award-info":[{"award-number":["2025-K-66"]}]},{"name":"Fujian Provincial Natural Resources Science and Technology Innovation Project of the Year 2025","award":["KY-100000-04-2025-023"],"award-info":[{"award-number":["KY-100000-04-2025-023"]}]},{"name":"Fujian Provincial Undergraduate Education and Teaching Research Project","award":["FBJY20240095"],"award-info":[{"award-number":["FBJY20240095"]}]},{"name":"Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application, Ministry of Natural Resources","award":["24201"],"award-info":[{"award-number":["24201"]}]},{"name":"Open Research Fund of Guangxi Key Laboratory of Culture and Tourism Intelligent Technology, Guilin Tourism University","award":["2026-GXKL-CTIT-M016"],"award-info":[{"award-number":["2026-GXKL-CTIT-M016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Continuous Global Navigation Satellite System (GNSS) monitoring is essential for characterizing surface subsidence in underground coal-mining areas. However, monitoring-station site selection remains strongly dependent on empirical judgment. Furthermore, steep deformation gradients can cause interferometric synthetic aperture radar (InSAR) decorrelation, phase-unwrapping failure, and data gaps in areas where ground-based monitoring is most needed. This study develops a quantitative, multi-source remote-sensing-assisted framework for GNSS monitoring-station site selection under a short-baseline real-time kinematic (RTK) configuration. Sentinel-1A, Sentinel-2C, unmanned aerial vehicle (UAV) photogrammetric products, and road-network data were integrated to construct eight evaluation factors: normalized difference vegetation index (NDVI), slope, terrain ruggedness index, deformation intensity, cumulative subsidence, InSAR coverage, distance to the subsidence edge, and distance to roads. An analytic hierarchy process (AHP) was used as the primary suitability assessment framework, while a random forest (RF) model was introduced with a limited weight to provide auxiliary information only in InSAR data-sparse areas. Grid-level aggregation, three-component Gaussian mixture model (GMM) screening, minimum-distance thinning, field reconnaissance, and monitoring-network review were subsequently combined to convert the continuous suitability surface into deployable station candidates. The resulting high-suitability areas were concentrated mainly along subsidence margins and near InSAR coverage gaps, reflecting the combined effects of deformation representativeness, supplementary monitoring demand, observation conditions, and engineering accessibility. Sixteen candidate stations were identified, of which S12, S3, and S10 were finally recommended to improve the northern, southwestern, and southeastern coverage of the existing monitoring network, respectively. Sensitivity analyses confirmed that the overall suitability pattern and recommended-station rankings remained stable under moderate parameter perturbations. Comparison with two existing GNSS stations further showed that the station with the higher suitability score exhibited a higher fitted subsidence rate (0.438 versus 0.320 mm day\u22121). Given the two-station and two-month validation dataset, this agreement represents preliminary consistency evidence rather than statistical proof of general effectiveness. The proposed framework links regional remote-sensing assessment with site-scale engineering review and monitoring-network optimization, providing practical decision support for GNSS deployment in underground mining-subsidence areas.<\/jats:p>","DOI":"10.3390\/s26165057","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T09:24:53Z","timestamp":1786353893000},"page":"5057","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Multi-Source Remote-Sensing-Assisted Method for GNSS Station Site Selection in Underground Coal-Mining Subsidence Areas"],"prefix":"10.3390","volume":"26","author":[{"given":"Yuanrong","family":"He","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiwei","family":"Su","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Culture and Tourism Intelligent Technology, Guilin Tourism University, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiying","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qun","family":"Su","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisheng","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiyuan","family":"Feng","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhitian","family":"Lin","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruting","family":"Su","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,9]]},"reference":[{"key":"ref_1","first-page":"44","article-title":"Chinese coal industry status quo in new period and countermeasures study","volume":"33","author":"Yang","year":"2021","journal-title":"Coal Geol. China"},{"key":"ref_2","first-page":"1","article-title":"Mining subsidence area status, syntheses governance model and governance recommendation","volume":"23","author":"Hu","year":"2018","journal-title":"Coal Min. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"159018","DOI":"10.1109\/ACCESS.2021.3126787","article-title":"Methods for monitoring fast and large-gradient subsidence in coal mining areas using SAR images: A review","volume":"9","author":"Hu","year":"2021","journal-title":"IEEE Access"},{"key":"ref_4","first-page":"104143","article-title":"Integrating spatial modeling-assisted InSAR phase unwrapping with temporal analysis for advanced mine subsidence time series mapping","volume":"133","author":"Ng","year":"2024","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Hu, Q., Hou, R., Kou, Y., Wang, P., Liu, Z., Li, H., Liu, W., Wang, X., Yi, S., and Zhang, F. (2026). Investigating mining-induced surface subsidence in mountainous areas using integrated InSAR and GNSS monitoring. Sensors, 26.","DOI":"10.3390\/s26041222"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/s43020-023-00095-5","article-title":"GNSS techniques for real-time monitoring of landslides: A review","volume":"4","author":"Huang","year":"2023","journal-title":"Satell. Navig."},{"key":"ref_7","first-page":"2226","article-title":"Stability evaluation of Dangchuan loess landslide in Heifangtai based on integration of engineering geological data and GNSS high-precision monitoring information","volume":"51","author":"Ling","year":"2022","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1186\/s43020-023-00119-0","article-title":"Stability analysis of reference station and compensation for monitoring stations in GNSS landslide monitoring","volume":"4","author":"Wang","year":"2023","journal-title":"Satell. Navig."},{"key":"ref_9","unstructured":"(2024). Specifications for Survey and Measurement of Global Navigation Satellite System (Standard No. GB\/T 18314\u20142024)."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kakoullis, D., Fotiou, K., Melillos, G., and Danezis, C. (2022). Considerations and multi-criteria decision analysis for the installation of collocated permanent GNSS and SAR infrastructures for continuous space-based monitoring of natural hazards. Remote Sens., 14.","DOI":"10.3390\/rs14041020"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1080\/19475705.2020.1766580","article-title":"The design and application of landslide monitoring and early warning system based on microservice architecture","volume":"11","author":"Bai","year":"2020","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1007\/s10346-023-02188-3","article-title":"Site selection for landslide GNSS monitoring stations using InSAR and UAV photogrammetry with analytical hierarchy process","volume":"21","author":"Xu","year":"2024","journal-title":"Landslides"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1061\/geosek.0000386","article-title":"Megaproject monitoring by satellite: InSAR-based settlement-time history","volume":"25","author":"Salazar","year":"2021","journal-title":"GeoStrata"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Kyriou, A., Nikolakopoulos, K., Koukouvelas, I., and Lampropoulou, P. (2021). Repeated UAV campaigns, GNSS measurements, GIS, and petrographic analyses for landslide mapping and monitoring. Minerals, 11.","DOI":"10.3390\/min11030300"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill.","DOI":"10.21236\/ADA214804"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"33492","DOI":"10.1109\/ACCESS.2022.3161742","article-title":"MCDM and various prioritization methods in AHP for CSS: A comprehensive review","volume":"10","author":"Gyani","year":"2022","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mangan, P., Pandi, D., Haq, M.A., Sinha, A., Nagarajan, R., Dasani, T., Keshta, I., and Alshehri, M. (2022). Analytic hierarchy process based land suitability for organic farming in the arid region. Sustainability, 14.","DOI":"10.3390\/su14084542"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1016\/0301-4215(93)90186-J","article-title":"Increasing the utilization of solar energy technologies (SET) in Jordan: Analytic hierarchy process","volume":"21","author":"Elkarmi","year":"1993","journal-title":"Energy Policy"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1016\/j.apenergy.2017.10.024","article-title":"Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia","volume":"206","author":"Awasthi","year":"2017","journal-title":"Appl. Energy"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1016\/j.rser.2019.06.035","article-title":"Integrated multi-criteria decision making methodology for pumped hydro-energy storage plant site selection from a sustainable development perspective with an application","volume":"112","author":"Nzotcha","year":"2019","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Mallick, J., Ibnatiq, A.A., Kahla, N.B., Alqadhi, S., Singh, V.P., Hoa, P.V., Hang, H.T., Hong, N.V., and Le, H.A. (2022). GIS-based decision support system for safe and sustainable building construction site in a mountainous region. Sustainability, 14.","DOI":"10.3390\/su14020888"},{"key":"ref_22","first-page":"102640","article-title":"High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques","volume":"105","author":"Li","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yuan, M., Li, M., Liu, H., Lv, P., Li, B., and Zheng, W. (2021). Subsidence monitoring base on SBAS-InSAR and slope stability analysis method for damage analysis in mountainous mining subsidence regions. Remote Sens., 13.","DOI":"10.3390\/rs13163107"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"107000","DOI":"10.1016\/j.cie.2020.107000","article-title":"Gaussian mixture model with feature selection: An embedded approach","volume":"152","author":"Fu","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Tang, W., Wang, M., Li, P., Wang, G., Yan, Y., and Yan, W. (2023). Ground subsidence associated with mining activity in the Ningdong coal base area, northwestern China revealed by InSAR time series analysis. Front. Earth Sci., 11.","DOI":"10.3389\/feart.2023.1132890"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"12445","DOI":"10.1038\/s41598-024-63400-5","article-title":"Integrated high-precision monitoring method for surface subsidence in mining areas using D-InSAR, SBAS, and UAV technologies","volume":"14","author":"Zhu","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"113456","DOI":"10.1016\/j.rse.2023.113456","article-title":"Contextual uncertainty assessments for InSAR-based deformation retrieval using an ensemble approach","volume":"287","author":"Olsen","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"104331","DOI":"10.1016\/j.cageo.2019.104331","article-title":"Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction","volume":"133","author":"Yunjun","year":"2019","journal-title":"Comput. Geosci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent scatterers in SAR interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.isprsjprs.2016.03.018","article-title":"Improved persistent scatterer analysis using amplitude dispersion index optimization of dual polarimetry data","volume":"117","author":"Esmaeili","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/16\/5057\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T09:37:54Z","timestamp":1786354674000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/16\/5057"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,9]]},"references-count":31,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["s26165057"],"URL":"https:\/\/doi.org\/10.3390\/s26165057","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,9]]}}}