{"id":"https://openalex.org/W2755559437","doi":"https://doi.org/10.1109/multi-temp.2017.8035245","title":"Urban area change detection based on generalized likelihood ratio test","display_name":"Urban area change detection based on generalized likelihood ratio test","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2755559437","doi":"https://doi.org/10.1109/multi-temp.2017.8035245","mag":"2755559437"},"language":"en","primary_location":{"id":"doi:10.1109/multi-temp.2017.8035245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2017.8035245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","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/A5107943874","display_name":"Weiying Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Weiying Zhao","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087677326","display_name":"Sylvain Lobry","orcid":"https://orcid.org/0000-0003-4738-2416"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sylvain Lobry","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031369629","display_name":"Henri Ma\u0131\u0302tre","orcid":"https://orcid.org/0000-0003-1314-2799"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Henri Maitre","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068697899","display_name":"Jean\u2010Marie Nicolas","orcid":"https://orcid.org/0000-0002-7952-846X"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Marie Nicolas","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077852561","display_name":"Florence Tupin","orcid":"https://orcid.org/0000-0002-3110-8183"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Florence Tupin","raw_affiliation_strings":["LTCI, Universit\u00e9 Paris-Saclay, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTCI, Universit\u00e9 Paris-Saclay, Paris, France","institution_ids":["https://openalex.org/I277688954","https://openalex.org/I4210165912"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3896,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52432753,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9987000226974487,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9623000025749207,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/change-detection","display_name":"Change detection","score":0.6893113255500793},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6167579889297485},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.4932484030723572},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.4927423298358917},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49167925119400024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4771425426006317},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4685939848423004},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4583858847618103},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4566144347190857},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.42516791820526123},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37121498584747314},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.342184841632843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2904680371284485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2608564496040344},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24905622005462646}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6893113255500793},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6167579889297485},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.4932484030723572},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.4927423298358917},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49167925119400024},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4771425426006317},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4685939848423004},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4583858847618103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4566144347190857},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.42516791820526123},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37121498584747314},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.342184841632843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2904680371284485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2608564496040344},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24905622005462646},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/multi-temp.2017.8035245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/multi-temp.2017.8035245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1995747879","https://openalex.org/W2015780366","https://openalex.org/W2069522573","https://openalex.org/W2077282160","https://openalex.org/W2121348175","https://openalex.org/W2121654385","https://openalex.org/W2419127331"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2116709453"],"abstract_inverted_index":{"Change":[0],"detection":[1,18,71,103],"methods":[2,39],"often":[3],"use":[4],"denoised":[5,34,54,95],"data":[6,25,55,84,96],"because":[7],"the":[8,17,57,70,86],"original":[9,32],"speckle":[10],"noise":[11],"has":[12],"a":[13],"strong":[14],"influence":[15],"on":[16,43,77],"results.":[19],"The":[20,73],"effect":[21],"of":[22,30,46,63,88,92,94],"using":[23,89],"different":[24,37],"sources":[26],"(different":[27],"equivalent":[28,61,90],"number":[29,62,91],"looks,":[31],"data,":[33,79],"data)":[35],"and":[36,56,97],"threshold":[38],"are":[40,65],"studied":[41],"based":[42],"four":[44],"kinds":[45],"generalized":[47],"likelihood":[48],"ratio":[49],"test":[50],"approaches.":[51],"NL-SAR":[52],"[1]":[53],"corresponding":[58,98],"spatially":[59],"varying":[60],"looks":[64,93],"taken":[66],"into":[67],"account":[68],"in":[69,104],"procedure.":[72],"bi-temporal":[74],"experimental":[75],"results":[76],"simulated":[78],"realistic":[80],"synthetic":[81],"Sentinel-1":[82],"SAR":[83],"show":[85],"improvement":[87],"adaptive":[99],"thresholds":[100],"for":[101],"change":[102],"urban":[105],"areas.":[106]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
