{"id":"https://openalex.org/W3038206524","doi":"https://doi.org/10.1109/jstars.2020.3006192","title":"Unsupervised Feature Learning to Improve Transferability of Landslide Susceptibility Representations","display_name":"Unsupervised Feature Learning to Improve Transferability of Landslide Susceptibility Representations","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3038206524","doi":"https://doi.org/10.1109/jstars.2020.3006192","mag":"3038206524"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2020.3006192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3006192","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2020.3006192","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046744673","display_name":"Qing Zhu","orcid":"https://orcid.org/0000-0002-0485-4965"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]},{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Zhu","raw_affiliation_strings":["Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-0485-4965","affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379185","display_name":"Li Chen","orcid":"https://orcid.org/0000-0001-8824-8542"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Chen","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-8824-8542","affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102022513","display_name":"Han Hu","orcid":"https://orcid.org/0000-0003-1137-2208"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Hu","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1137-2208","affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030017120","display_name":"Saied Pirasteh","orcid":"https://orcid.org/0000-0002-3177-037X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Saeid Pirasteh","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-3177-037X","affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398353","display_name":"Haifeng Li","orcid":"https://orcid.org/0000-0003-1173-6593"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Li","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-1173-6593","affiliations":[{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015086379","display_name":"Xiao Xie","orcid":"https://orcid.org/0000-0002-2598-0047"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao Xie","raw_affiliation_strings":["Zhejiang Hi-target Space Information Technology Company Ltd., Huzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Hi-target Space Information Technology Company Ltd., Huzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":14.1382,"has_fulltext":false,"cited_by_count":66,"citation_normalized_percentile":{"value":0.98648465,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"3917","last_page":"3930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9688000082969666,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7454432845115662},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6219511032104492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5380473136901855},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4958861768245697},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4811771810054779},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.47986143827438354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4361395537853241},{"id":"https://openalex.org/keywords/landslide","display_name":"Landslide","score":0.4271194636821747},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.41076207160949707},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39936092495918274},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3859931230545044},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36124634742736816},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1172930896282196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7454432845115662},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6219511032104492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5380473136901855},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4958861768245697},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4811771810054779},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.47986143827438354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4361395537853241},{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.4271194636821747},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.41076207160949707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39936092495918274},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3859931230545044},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36124634742736816},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1172930896282196},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2020.3006192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3006192","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:30ca4bff56c94eeea59d6530e44c49d7","is_oa":true,"landing_page_url":"https://doaj.org/article/30ca4bff56c94eeea59d6530e44c49d7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 3917-3930 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2020.3006192","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2020.3006192","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G1142009460","display_name":null,"funder_award_id":"41941019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W189596042","https://openalex.org/W273955616","https://openalex.org/W299701049","https://openalex.org/W1498436455","https://openalex.org/W1559060276","https://openalex.org/W1799366690","https://openalex.org/W1904365287","https://openalex.org/W1980293819","https://openalex.org/W2030991373","https://openalex.org/W2084430223","https://openalex.org/W2089468765","https://openalex.org/W2113242816","https://openalex.org/W2116064496","https://openalex.org/W2121821841","https://openalex.org/W2145094598","https://openalex.org/W2163922914","https://openalex.org/W2248620004","https://openalex.org/W2277106806","https://openalex.org/W2328338019","https://openalex.org/W2519746072","https://openalex.org/W2527851062","https://openalex.org/W2567854072","https://openalex.org/W2587598231","https://openalex.org/W2587950680","https://openalex.org/W2601450892","https://openalex.org/W2611950291","https://openalex.org/W2732724430","https://openalex.org/W2735233225","https://openalex.org/W2770617885","https://openalex.org/W2789099021","https://openalex.org/W2807656415","https://openalex.org/W2842511635","https://openalex.org/W2880239935","https://openalex.org/W2887280559","https://openalex.org/W2897555073","https://openalex.org/W2911749912","https://openalex.org/W2915483120","https://openalex.org/W2919115771","https://openalex.org/W2963341924","https://openalex.org/W2963739978","https://openalex.org/W2964161291","https://openalex.org/W2973428696","https://openalex.org/W2980353925","https://openalex.org/W2985076077","https://openalex.org/W2990986966","https://openalex.org/W2997574889","https://openalex.org/W2999015335","https://openalex.org/W3006103906","https://openalex.org/W3041133507","https://openalex.org/W4214879626","https://openalex.org/W4297808394","https://openalex.org/W6607775107","https://openalex.org/W6610017368","https://openalex.org/W6633301734","https://openalex.org/W6636308168","https://openalex.org/W6638444622","https://openalex.org/W6640036494","https://openalex.org/W6681096077","https://openalex.org/W6701617943","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6740483536","https://openalex.org/W6770009596","https://openalex.org/W6770432743","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W2150029999","https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W2068476337","https://openalex.org/W60493759","https://openalex.org/W4308619659","https://openalex.org/W3213069564","https://openalex.org/W4378421684","https://openalex.org/W4294203825"],"abstract_inverted_index":{"A":[0],"landslide":[1,28,199],"susceptibility":[2,29,200],"map":[3,201],"(LSM)":[4],"is":[5,203,217],"of":[6,35,42,54,160,188,241],"vital":[7],"importance":[8],"for":[9,225],"risk":[10],"recognition":[11],"and":[12,65,93,102,137,182,211,216,232],"prevention.":[13],"In":[14,158],"the":[15,27,32,40,47,66,70,108,113,119,128,132,147,179,186,198,206,229,239],"last":[16],"decade,":[17],"statistical":[18,56],"methods":[19,57,165],"have":[20,144],"gradually":[21],"exerted":[22],"their":[23],"impact":[24],"on":[25,238],"mapping":[26],"to":[30,39,46,68,73,105,126,131,175,185,195,220,228],"locate":[31],"high-risk":[33],"places":[34],"landslide.":[36,243],"However,":[37],"due":[38],"complexity":[41],"getting":[43],"full":[44],"access":[45],"thematic":[48,114],"information":[49],"in":[50,112,122,141],"large":[51,168],"scenarios,":[52],"most":[53],"these":[55,78],"generally":[58],"suffer":[59],"from":[60],"overfitting,":[61],"inadequate":[62],"representative":[63],"power,":[64],"inability":[67],"transfer":[69],"learned":[71,129],"representation":[72,85],"other":[74,164,196],"places.":[75],"To":[76],"solve":[77],"challenges,":[79],"this":[80],"study":[81],"designed":[82],"an":[83,123],"unsupervised":[84,106],"learning":[86],"module,":[87],"which":[88],"features":[89],"independence,":[90],"compactness,":[91],"robustness,":[92],"transferability.":[94],"Specifically,":[95],"we":[96,117],"first":[97],"stack":[98],"restricted":[99],"Boltzmann":[100],"machines":[101],"denoising":[103],"autoencoder":[104],"discover":[107],"underlying":[109],"representations":[110,130],"embedded":[111],"maps.":[115],"Then,":[116],"applied":[118],"transferring":[120],"strategy":[121],"adversarial":[124],"manner":[125],"generalize":[127],"sample-scarce":[133],"area.":[134],"Experimental":[135],"results":[136],"analyses":[138],"using":[139],"data":[140],"different":[142,155],"regions":[143],"revealed":[145],"that":[146,202],"proposed":[148,207],"method":[149,208],"can":[150],"be":[151],"generalized":[152],"well":[153],"between":[154],"LSM":[156],"scenarios.":[157],"terms":[159],"precision,":[161],"it":[162],"outperforms":[163],"by":[166,171,183,205],"a":[167,242],"margin,":[169],"e.g.,":[170],"around":[172],"7%":[173],"compared":[174,194],"multilayer":[176],"perceptrons":[177],"with":[178],"same":[180],"configuration,":[181],"3%\u20134%":[184],"state":[187],"art":[189],"algorithm":[190],"random":[191],"forest.":[192],"Besides,":[193],"methods,":[197],"predicted":[204],"featuring":[209],"smoothness":[210],"stableness":[212],"seems":[213],"more":[214,218],"reliable,":[215],"according":[219],"some":[221],"prior":[222],"knowledge":[223],"that,":[224],"example,":[226],"distance":[227],"drainage,":[230],"slope,":[231],"stratum,":[233],"should":[234],"exert":[235],"dominant":[236],"effects":[237],"occurrence":[240]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
