{"id":"https://openalex.org/W4404821704","doi":"https://doi.org/10.3390/rs16234464","title":"Attention Swin Transformer UNet for Landslide Segmentation in Remotely Sensed Images","display_name":"Attention Swin Transformer UNet for Landslide Segmentation in Remotely Sensed Images","publication_year":2024,"publication_date":"2024-11-28","ids":{"openalex":"https://openalex.org/W4404821704","doi":"https://doi.org/10.3390/rs16234464"},"language":"en","primary_location":{"id":"doi:10.3390/rs16234464","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16234464","pdf_url":"https://www.mdpi.com/2072-4292/16/23/4464/pdf?version=1732783381","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/23/4464/pdf?version=1732783381","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104224129","display_name":"Bingxue Liu","orcid":"https://orcid.org/0000-0002-7335-4710"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingxue Liu","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029264369","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-3526-9160"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103268595","display_name":"Yuming Wu","orcid":"https://orcid.org/0000-0003-3062-9267"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuming Wu","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100622644","display_name":"Xing Gao","orcid":"https://orcid.org/0000-0002-0401-5125"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Gao","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103268595"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210160793"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":9.0279,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.97596876,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"16","issue":"23","first_page":"4464","last_page":"4464"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9991999864578247,"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":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/landslide","display_name":"Landslide","score":0.5520524978637695},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.551096498966217},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.45502716302871704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4225904941558838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39299845695495605},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3767702579498291},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.3724026679992676},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.357638955116272},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2668091058731079},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.15383508801460266}],"concepts":[{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.5520524978637695},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.551096498966217},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.45502716302871704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4225904941558838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39299845695495605},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3767702579498291},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.3724026679992676},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.357638955116272},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2668091058731079},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.15383508801460266}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16234464","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16234464","pdf_url":"https://www.mdpi.com/2072-4292/16/23/4464/pdf?version=1732783381","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fad1aca2be3c40f9b7005ebbad93e066","is_oa":true,"landing_page_url":"https://doaj.org/article/fad1aca2be3c40f9b7005ebbad93e066","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 23, p 4464 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16234464","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16234464","pdf_url":"https://www.mdpi.com/2072-4292/16/23/4464/pdf?version=1732783381","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4404821704.pdf"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2286929393","https://openalex.org/W2395611524","https://openalex.org/W2402764487","https://openalex.org/W2548181642","https://openalex.org/W2565639579","https://openalex.org/W2752782242","https://openalex.org/W2908624219","https://openalex.org/W2910853374","https://openalex.org/W2912361013","https://openalex.org/W2964077901","https://openalex.org/W2964309882","https://openalex.org/W2967019526","https://openalex.org/W2987544319","https://openalex.org/W3003882269","https://openalex.org/W3081064176","https://openalex.org/W3135436966","https://openalex.org/W3139263243","https://openalex.org/W3156421991","https://openalex.org/W3160702718","https://openalex.org/W4205138939","https://openalex.org/W4213060692","https://openalex.org/W4213358987","https://openalex.org/W4220957530","https://openalex.org/W4283022097","https://openalex.org/W4283030004","https://openalex.org/W4292059288","https://openalex.org/W4307939994","https://openalex.org/W4308080109","https://openalex.org/W4319083668","https://openalex.org/W4321232185","https://openalex.org/W4323519326","https://openalex.org/W4324030711","https://openalex.org/W4378385830","https://openalex.org/W4385491783","https://openalex.org/W4386221874","https://openalex.org/W4386574179","https://openalex.org/W4386590660","https://openalex.org/W4387507690","https://openalex.org/W4387993701","https://openalex.org/W4388085808","https://openalex.org/W4388103738","https://openalex.org/W4389722667","https://openalex.org/W4403847835","https://openalex.org/W6795435739"],"related_works":["https://openalex.org/W2389676928","https://openalex.org/W3169474304","https://openalex.org/W2369104181","https://openalex.org/W3201652628","https://openalex.org/W4212972401","https://openalex.org/W2389287188","https://openalex.org/W3081499580","https://openalex.org/W2615020820","https://openalex.org/W3106883776","https://openalex.org/W2950100253"],"abstract_inverted_index":{"The":[0,181,206,217],"development":[1],"of":[2,62,77,111,161,175,200,208,223,226,230,235],"artificial":[3],"intelligence":[4],"makes":[5],"it":[6],"possible":[7],"to":[8,137,164,178],"rapidly":[9],"segment":[10],"landslides.":[11],"However,":[12],"there":[13],"are":[14],"still":[15],"some":[16],"challenges":[17],"in":[18,53,87,104,113,129,214],"landslide":[19,155,170,204],"segmentation":[20,29,114],"based":[21,59],"on":[22,60,238],"remote":[23],"sensing":[24],"images,":[25],"such":[26],"as":[27,73],"low":[28],"accuracy,":[30],"caused":[31],"by":[32,126,157],"similar":[33],"features,":[34,36],"inhomogeneous":[35],"and":[37,68,80,107,144,195,232],"blurred":[38],"boundaries.":[39],"To":[40],"address":[41],"these":[42],"issues,":[43],"we":[44],"propose":[45],"a":[46,65,74,81],"novel":[47],"deep":[48],"learning":[49],"model":[50,57,210],"called":[51],"AST-UNet":[52,202,219],"this":[54],"paper.":[55],"This":[56],"is":[58,211],"structure":[61],"SwinUNet,":[63,196],"attaching":[64],"channel":[66,118,131],"Attention":[67],"spatial":[69,82,94,99,123,147],"intersection":[70,95],"(CASI)":[71],"module":[72,86,96,120,150],"parallel":[75],"branch":[76],"the":[78,88,93,98,105,109,117,122,130,134,146,152,159,162,169,173,198,215,239],"encoder,":[79],"detail":[83,148],"enhancement":[84,149],"(SDE)":[85],"skip":[89],"connection.":[90],"Specifically,":[91],"(1)":[92],"expands":[97],"attention":[100,119,124,160],"range,":[101],"alleviating":[102],"noise":[103],"image":[106],"enhances":[108],"continuity":[110],"landslides":[112],"results;":[115],"(2)":[116],"refines":[121],"weights":[125],"feature":[127],"modeling":[128],"dimension,":[132],"improving":[133],"model\u2019s":[135],"ability":[136],"differentiate":[138],"targets":[139],"that":[140],"closely":[141],"resemble":[142],"landslides;":[143],"(3)":[145],"increases":[151],"accuracy":[153],"for":[154,203],"boundaries":[156],"strengthening":[158],"decoder":[163],"detailed":[165],"features.":[166],"We":[167],"use":[168],"data":[171],"from":[172],"area":[174],"Luding,":[176],"Sichuan":[177],"conduct":[179],"experiments.":[180,216],"comparative":[182],"analyses":[183],"with":[184],"state-of-the-art":[185],"(SOTA)":[186],"models,":[187],"including":[188],"FCN,":[189],"UNet,":[190],"DeepLab":[191],"V3+,":[192],"TransFuse,":[193],"TranUNet,":[194],"prove":[197],"superiority":[199],"our":[201,209],"segmentation.":[205],"generalization":[207],"also":[212],"verified":[213],"proposed":[218],"obtains":[220],"an":[221],"F1-score":[222],"90.14%,":[224],"mIoU":[225],"83.45%,":[227],"foreground":[228],"IoU":[229],"70.81%,":[231],"Hausdorff":[233],"distance":[234],"3.73,":[236],"respectively,":[237],"experimental":[240],"datasets.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":6}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
