{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T14:02:12Z","timestamp":1785506532979,"version":"3.56.0"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,19]],"date-time":"2022-02-19T00:00:00Z","timestamp":1645228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National Key Research and Development Program of China","award":["2018YFC1505101, 2021YFC3000401"],"award-info":[{"award-number":["2018YFC1505101, 2021YFC3000401"]}]},{"name":"The Key Research and Development Program of Sichuan Province","award":["2020YFS0353"],"award-info":[{"award-number":["2020YFS0353"]}]},{"name":"the Open Fund of State Key Laboratory of Geohazard Prevention and Geoenviroment Protection","award":["SKLGP2017K016"],"award-info":[{"award-number":["SKLGP2017K016"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Landslide displacement prediction is crucial for the early warning of slope failure but remains a challenging task due to its spatiotemporal complexity. Although temporal dependency has been well studied and discussed, spatial dependence is relatively less explored due to its significant variations of the spatial structure of landslides. In this study, a novel graph convolutional incorporating GRU network (GC-GRU-N) is proposed and applied to landslide displacement forecasts. The model conducts attribute-augmented graph convolution (GC) operations on GNSS displacement data with weighted adjacency matrices and an attribute-augmented unit to combine features, including the displacements, the distance, and other external influence factors to capture spatial dependence. The output of multi-weight graph convolution is then applied to the gated recurrent unit (GRU) network to learn temporal dependencies. The related optimal hyper-parameters are determined by comparison experiments. When applied to two typical landslide sites in the Three Gorge Reservoir (TGR), China, GC-GRU-N outperformed the comparative models in both cases. The ablation experiment results also show that the attribute augmentation, which considers external factors of landslide displacement, can further improve the model\u2019s prediction performance. We conclude that the GC-GRU-N model can provide robust landslide displacement forecasting with high efficiency.<\/jats:p>","DOI":"10.3390\/rs14041016","type":"journal-article","created":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T08:34:47Z","timestamp":1645432487000},"page":"1016","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["A Graph Convolutional Incorporating GRU Network for Landslide Displacement Forecasting Based on Spatiotemporal Analysis of GNSS Observations"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0637-2978","authenticated-orcid":false,"given":"Yanan","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiyuan","family":"Luo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9181-1818","authenticated-orcid":false,"given":"Zhong","family":"Lu","sequence":"additional","affiliation":[{"name":"Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Liao","sequence":"additional","affiliation":[{"name":"Technology Service Center of Surveying and Mapping, Sichuan Bureau of Surveying, Mapping and Geoinformation, Chengdu 610081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0694-2018","authenticated-orcid":false,"given":"Huajin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Architecture and Civil Engineering, Chengdu University, Chengdu 610106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lina","family":"Hao","sequence":"additional","affiliation":[{"name":"College of Earth Science, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s10346-009-0142-y","article-title":"Some Catastrophic Landslides since the Twentieth Century in the Southwest of China","volume":"6","author":"Runqiu","year":"2009","journal-title":"Landslides"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2792","DOI":"10.1038\/s41467-020-16617-7","article-title":"Fielding. 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