{"id":"https://openalex.org/W1975329551","doi":"https://doi.org/10.1109/igarss.2015.7326914","title":"Object-based change detection model using correlation analysis and classification for VHR image","display_name":"Object-based change detection model using correlation analysis and classification for VHR image","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1975329551","doi":"https://doi.org/10.1109/igarss.2015.7326914","mag":"1975329551"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7326914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326914","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/A5072604677","display_name":"Zhipeng Tang","orcid":"https://orcid.org/0000-0003-1885-340X"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Tang","raw_affiliation_strings":["Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051316999","display_name":"Hong Tang","orcid":"https://orcid.org/0000-0001-9058-5724"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Tang","raw_affiliation_strings":["Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106760865","display_name":"Shi He","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi He","raw_affiliation_strings":["Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114547020","display_name":"Ting Mao","orcid":"https://orcid.org/0009-0007-8926-8474"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Mao","raw_affiliation_strings":["Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academy of Disaster Reduction & Emergency Management, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Key Laboratory of Environmental Change & Natural Disaster of MOE, Beijing Normal University, Beijing 100875, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4840","last_page":"4843"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9865999817848206,"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"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9865999817848206,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.960099995136261,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6719641089439392},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.6660633087158203},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6629860997200012},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6391128897666931},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5737810134887695},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5589374303817749},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.53891521692276},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.45914149284362793},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.44238170981407166},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4300505816936493},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4231518805027008},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.337274968624115},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20709240436553955}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6719641089439392},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.6660633087158203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6629860997200012},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6391128897666931},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5737810134887695},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5589374303817749},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.53891521692276},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.45914149284362793},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.44238170981407166},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4300505816936493},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4231518805027008},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.337274968624115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20709240436553955},{"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/igarss.2015.7326914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326914","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1489537150","https://openalex.org/W1991546502","https://openalex.org/W2076576187","https://openalex.org/W2115367758","https://openalex.org/W4242841269","https://openalex.org/W7034239774"],"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/W2385200445","https://openalex.org/W2384344231","https://openalex.org/W2347818927","https://openalex.org/W4247859527","https://openalex.org/W1983425594"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,16,84,94],"introduce":[4],"an":[5,21],"object-based":[6],"change":[7,53,76,81],"detection":[8],"model":[9],"using":[10],"correlation":[11,41],"analysis":[12],"and":[13,40,51,78,117,135,139],"classification.":[14],"First":[15],"use":[17],"eCognition":[18],"to":[19,29,70],"obtain":[20],"over-segmentation":[22],"map.":[23],"Then":[24,83],"linear":[25],"regression":[26,37],"is":[27],"used":[28],"gain":[30],"three":[31,87],"unique":[32],"types":[33],"of":[34,123],"parameters":[35],"-":[36],"coefficient,":[38],"offset,":[39],"coefficient":[42],"which":[43],"can":[44],"provide":[45],"valuable":[46],"information":[47],"about":[48],"the":[49,57,61,66,86,111,137],"location":[50],"numeric":[52],"value":[54],"derived":[55],"within":[56],"segmentation":[58],"objects":[59],"in":[60],"two":[62,67],"data":[63,68],"sets.":[64],"Understandably,":[65],"tend":[69],"be":[71],"highly":[72],"correlated":[73],"when":[74,80],"little":[75],"occurs,":[77],"uncorrelated":[79],"occurs.":[82],"treat":[85],"variables":[88],"as":[89],"a":[90],"three-band":[91],"image.":[92],"Finally,":[93],"perform":[95],"maximum":[96],"likelihood":[97],"classification":[98],"with":[99],"training":[100],"examples.":[101],"The":[102,121],"result":[103],"shows":[104],"that":[105,127],"our":[106,124],"method":[107,125],"performs":[108,129],"better":[109],"than":[110],"methods":[112],"proposed":[113],"by":[114],"Yang":[115],"[2]":[116],"J.":[118],"Im":[119],"[3].":[120],"advantages":[122],"are":[126],"it":[128],"automatically":[130],"without":[131],"selecting":[132],"threshold":[133],"empirically":[134],"alleviates":[136],"\u201csalt":[138],"pepper\u201d":[140],"effect.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}