{"id":"https://openalex.org/W2026165658","doi":"https://doi.org/10.1109/igarss.2015.7326592","title":"Detecting damaged buildings caused by earthquake using local gradient orientation entropy statistics method","display_name":"Detecting damaged buildings caused by earthquake using local gradient orientation entropy statistics method","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2026165658","doi":"https://doi.org/10.1109/igarss.2015.7326592","mag":"2026165658"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7326592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100348108","display_name":"Xin Ye","orcid":"https://orcid.org/0000-0002-4795-1685"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Ye","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109077790","display_name":"Qiming Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiming Qin","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100774416","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-5717-1914"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420053","display_name":"Jianhua Wang","orcid":"https://orcid.org/0000-0003-2175-3610"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Wang","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067556699","display_name":"Xiucheng Yang","orcid":"https://orcid.org/0000-0001-5134-9614"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiucheng Yang","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078636710","display_name":"Xue-Bin Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuebin Qin","raw_affiliation_strings":["Institute of Remote Sensing and GIS, Peking University, Beijing, China","Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and GIS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing & GIS, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.104622,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"35","issue":null,"first_page":"3568","last_page":"3571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9943000078201294,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.926800012588501,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/prewitt-operator","display_name":"Prewitt operator","score":0.7904937267303467},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6263060569763184},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5487251877784729},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5433843731880188},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.48911911249160767},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.47994711995124817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42801207304000854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40792107582092285},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.34009748697280884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3400077819824219},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32507848739624023},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27076390385627747},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.2549028992652893},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.15597200393676758},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1539488434791565},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.15033137798309326}],"concepts":[{"id":"https://openalex.org/C155012704","wikidata":"https://www.wikidata.org/wiki/Q451898","display_name":"Prewitt operator","level":5,"score":0.7904937267303467},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6263060569763184},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5487251877784729},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5433843731880188},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.48911911249160767},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47994711995124817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42801207304000854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40792107582092285},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.34009748697280884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3400077819824219},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32507848739624023},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27076390385627747},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.2549028992652893},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.15597200393676758},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1539488434791565},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.15033137798309326},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2015.7326592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1883973623","https://openalex.org/W1965243553","https://openalex.org/W1978199959","https://openalex.org/W2028842634","https://openalex.org/W2060934798","https://openalex.org/W2082699349","https://openalex.org/W2130334431","https://openalex.org/W2157651575","https://openalex.org/W3041543760","https://openalex.org/W6780826181"],"related_works":["https://openalex.org/W2380459166","https://openalex.org/W4322626645","https://openalex.org/W2391401022","https://openalex.org/W2358977121","https://openalex.org/W2365950611","https://openalex.org/W2558461544","https://openalex.org/W4240186469","https://openalex.org/W2366481947","https://openalex.org/W4230921275","https://openalex.org/W2080130515"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,32,36,42,50,64,88,98,136],"new":[4,51],"method":[5,142],"to":[6,61,125],"detect":[7,126],"damaged":[8,37,105,127],"buildings":[9,106],"caused":[10],"by":[11,73],"earthquake":[12,134],"from":[13],"high":[14],"spatial":[15],"resolution":[16],"remote":[17],"sensing":[18],"image.":[19],"We":[20],"found":[21],"that":[22,40,140],"the":[23,78,146,154,160],"probability":[24],"of":[25,82,112,132],"multiple":[26],"gradient":[27,69,75,79],"orientations":[28],"is":[29,164],"greater":[30],"in":[31,41,87],"local":[33,43,89],"area":[34,44],"within":[35,45,97],"building":[38,65,99],"than":[39],"an":[46,117],"intact":[47],"building.":[48],"Therefore,":[49,116],"feature":[52],"(Local":[53],"Gradient":[54],"Orientation":[55],"Entropy,":[56],"LGOE)":[57],"was":[58,66,71,85,101,123,143,157],"put":[59],"forward":[60],"determine":[62],"whether":[63],"damaged.":[67],"First,":[68],"information":[70],"obtained":[72],"Prewitt":[74],"operator.":[76],"Second,":[77],"orientation":[80],"entropy":[81],"one":[83],"pixel":[84],"calculated":[86],"3":[90],"\u00d73":[91],"window.":[92],"Last,":[93],"average":[94],"LGOE":[95,109,119],"value":[96,121],"boundary":[100],"counted.":[102],"In":[103],"general,":[104],"have":[107],"higher":[108],"values":[110],"because":[111],"their":[113],"irregular":[114],"texture.":[115],"optimum":[118],"threshold":[120],"(LGOET)":[122],"set":[124],"buildings.":[128],"The":[129],"experiment":[130],"results":[131],"Yushu":[133],"using":[135],"Quickbird":[137],"image":[138],"demonstrated":[139],"our":[141],"effective.":[144],"Of":[145],"total":[147],"101":[148],"buildings,":[149],"87":[150],"were":[151],"detected":[152],"correctly,":[153],"overall":[155,161],"accuracy":[156],"86.14%,":[158],"and":[159],"kappa":[162],"coefficient":[163],"72.25%.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
