{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T12:04:47Z","timestamp":1775563487601,"version":"3.50.1"},"reference-count":20,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T00:00:00Z","timestamp":1772582400000},"content-version":"vor","delay-in-days":62,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Procedia Computer Science"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1016\/j.procs.2026.03.036","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T12:39:40Z","timestamp":1774355980000},"page":"655-662","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Identifying and Modeling the Complex Relationships Among Landslide Causative Factors: A Wayanad Case study"],"prefix":"10.1016","volume":"278","author":[{"given":"C.V.","family":"Ambili","sequence":"first","affiliation":[]},{"given":"B.A.","family":"Sabarish","sequence":"additional","affiliation":[]},{"given":"R.","family":"Aarthi","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.procs.2026.03.036_bib1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/19475683.2020.1758207","article-title":"Spatial modelling of shallow landslide susceptibility: a study from the southern western ghats region of kerala, india","volume":"26","author":"Achu","year":"2020","journal-title":"Annals of GIS"},{"key":"10.1016\/j.procs.2026.03.036_bib2","doi-asserted-by":"crossref","unstructured":"Akosah, S., Gratchev, I., Kim, D.H., Ohn, S.Y., 2024. Application of artificial intelligence and remote sensing for landslide detection and prediction: systematic review. Remote Sensing 16, 2947.","DOI":"10.3390\/rs16162947"},{"key":"10.1016\/j.procs.2026.03.036_bib3","doi-asserted-by":"crossref","unstructured":"Anzalone, A., Pagliaro, A., Tutone, A., 2024. An introduction to machine and deep learning methods for cloud masking applications. Applied Sciences 14, 2887.","DOI":"10.3390\/app14072887"},{"key":"10.1016\/j.procs.2026.03.036_bib4","doi-asserted-by":"crossref","unstructured":"Arumugam, T., Kinattinkara, S., Velusamy, S., Shanmugamoorthy, M., Murugan, S., 2023. Gis based landslide susceptibility mapping and assessment using weighted overlay method in wayanad: A part of western ghats, kerala. Urban Climate 49, 101508.","DOI":"10.1016\/j.uclim.2023.101508"},{"key":"10.1016\/j.procs.2026.03.036_bib5","doi-asserted-by":"crossref","unstructured":"Bhuvaneswari, T., Sekar, R.C.G., Selvi, M.C., Rubavathi, J.J., Kaviyaa, V., 2024. Robust deep learning for accurate landslide identification and prediction, in: Doklady Earth Sciences, Springer. pp. 1700\u20131708.","DOI":"10.1134\/S1028334X23602961"},{"key":"10.1016\/j.procs.2026.03.036_bib6","doi-asserted-by":"crossref","unstructured":"Chowdhury, M.S., 2023. A review on landslide susceptibility mapping research in bangladesh. Heliyon 9.","DOI":"10.1016\/j.heliyon.2023.e17972"},{"key":"10.1016\/j.procs.2026.03.036_bib7","unstructured":"Down To Earth, 2019. Western ghats at risk: Deforestation data drives home point again. https:\/\/www.downtoearth.org.in\/forests\/western-ghats-at-risk-deforestation-data-drives-home-point-again-64470. Accessed: 2025-04-05."},{"key":"10.1016\/j.procs.2026.03.036_bib8","doi-asserted-by":"crossref","unstructured":"ED Chaves, M., CA Picoli, M., D. Sanches, I., 2020. Recent applications of landsat 8\/oli and sentinel-2\/msi for land use and land cover mapping: A systematic review. Remote Sensing 12, 3062.","DOI":"10.3390\/rs12183062"},{"key":"10.1016\/j.procs.2026.03.036_bib9","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1029\/2018RG000608","article-title":"An overview of global leaf area index (lai): Methods, products, validation, and applications","volume":"57","author":"Fang","year":"2019","journal-title":"Reviews of Geophysics"},{"key":"10.1016\/j.procs.2026.03.036_bib10","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1007\/s12518-022-00437-z","article-title":"A combined gis and remote sensing approach for monitoring climate change- related land degradation to support landscape preservation and planning tools: The basilicata case study","volume":"15","author":"Gabriele","year":"2023","journal-title":"Applied Geomatics"},{"key":"10.1016\/j.procs.2026.03.036_bib11","doi-asserted-by":"crossref","unstructured":"Ghorbanzadeh, O., Crivellari, A., Ghamisi, P., Shahabi, H., Blaschke, T., 2021. A comprehensive transferability evaluation of u-net and resu-net for landslide detection from sentinel-2 data (case study areas from taiwan, china, and japan). Scientific Reports 11, 14629.","DOI":"10.1038\/s41598-021-94190-9"},{"key":"10.1016\/j.procs.2026.03.036_bib12","doi-asserted-by":"crossref","unstructured":"Goffi, A., Stroppiana, D., Brivio, P.A., Bordogna, G., Boschetti, M., 2020. Towards an automated approach to map flooded areas from sentinel-2 msi data and soft integration of water spectral features. International Journal of Applied Earth Observation and Geoinformation 84, 101951.","DOI":"10.1016\/j.jag.2019.101951"},{"key":"10.1016\/j.procs.2026.03.036_bib13","doi-asserted-by":"crossref","first-page":"2954","DOI":"10.1016\/j.jrmge.2023.03.001","article-title":"Uncertainties of landslide susceptibility prediction considering different landslide types","volume":"15","author":"Huang","year":"2023","journal-title":"Journal of Rock Mechanics and Geotechnical Engineering"},{"key":"10.1016\/j.procs.2026.03.036_bib14","doi-asserted-by":"crossref","unstructured":"Imbrenda, V., Coluzzi, R., Di Stefano, V., Egidi, G., Salvati, L., Samela, C., Simoniello, T., Lanfredi, M., 2022. Modeling spatio-temporal divergence in land vulnerability to desertification with local regressions. Sustainability 14, 10906.","DOI":"10.3390\/su141710906"},{"key":"10.1016\/j.procs.2026.03.036_bib15","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/978-3-031-44296-4_8","article-title":"Community scale landslide resilience: A citizen-science approach","volume":"2","author":"Ramesh","year":"2023","journal-title":"Progress in Landslide Research and Technology"},{"key":"10.1016\/j.procs.2026.03.036_bib16","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1007\/s001090000086","article-title":"Clinical implications of dysregulated cytokine production","volume":"78","author":"Slifka","year":"2000","journal-title":"J. Mol. Med."},{"key":"10.1016\/j.procs.2026.03.036_bib17","first-page":"20","article-title":"Potential geotourism and the prospect of raising awareness about geoconservation of landslides as geomorphosites in munnar -rajamala areas, idukki district, kerala, india","volume":"23","author":"Wadhawan","year":"2022","journal-title":"SGAT Bulletin"},{"key":"10.1016\/j.procs.2026.03.036_bib18","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1007\/s12594-023-2361-6","article-title":"A novel application of catchment approach to assessment of 2021 rockfall and landslides vulnerabilities in tirumala hills, andhra pradesh, india","volume":"99","author":"Wadhawan","year":"2023","journal-title":"Journal of the Geological Society of India"},{"key":"10.1016\/j.procs.2026.03.036_bib19","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1007\/s10346-023-02029-3","article-title":"4d electrical resistivity to monitor unstable slopes in mountainous tropical regions: an example from munnar, india","volume":"20","author":"Watlet","year":"2023","journal-title":"Landslides"},{"key":"10.1016\/j.procs.2026.03.036_bib20","doi-asserted-by":"crossref","unstructured":"Zhao, S., Liu, M., Tao, M., Zhou, W., Lu, X., Xiong, Y., Li, F., Wang, Q., 2023. The role of satellite remote sensing in mitigating and adapting to global climate change. Science of the Total Environment 904, 166820.","DOI":"10.1016\/j.scitotenv.2023.166820"}],"container-title":["Procedia Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926006289?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926006289?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T11:23:01Z","timestamp":1775560981000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877050926006289"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":20,"alternative-id":["S1877050926006289"],"URL":"https:\/\/doi.org\/10.1016\/j.procs.2026.03.036","relation":{},"ISSN":["1877-0509"],"issn-type":[{"value":"1877-0509","type":"print"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Identifying and Modeling the Complex Relationships Among Landslide Causative Factors: A Wayanad Case study","name":"articletitle","label":"Article Title"},{"value":"Procedia Computer Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.procs.2026.03.036","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}