{"id":"https://openalex.org/W3083758784","doi":"https://doi.org/10.14358/pers.86.9.547","title":"Semi-Automatic Building Extraction from WorldView-2 Imagery Using Taguchi Optimization","display_name":"Semi-Automatic Building Extraction from WorldView-2 Imagery Using Taguchi Optimization","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3083758784","doi":"https://doi.org/10.14358/pers.86.9.547","mag":"3083758784"},"language":"en","primary_location":{"id":"doi:10.14358/pers.86.9.547","doi":"https://doi.org/10.14358/pers.86.9.547","is_oa":false,"landing_page_url":"https://doi.org/10.14358/pers.86.9.547","pdf_url":null,"source":{"id":"https://openalex.org/S99003644","display_name":"Photogrammetric Engineering & Remote Sensing","issn_l":"0099-1112","issn":["0099-1112","2374-8079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800734","host_organization_name":"American Society for Photogrammetry and Remote Sensing","host_organization_lineage":["https://openalex.org/P4320800734"],"host_organization_lineage_names":["American Society for Photogrammetry and Remote Sensing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Photogrammetric Engineering &amp; Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","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/A5014645913","display_name":"Hasan Tonbul","orcid":"https://orcid.org/0000-0003-4817-6542","observed_orcids":["https://orcid.org/0000-0003-4817-6542"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasan Tonbul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5046223798","display_name":"Ta\u015fk\u0131n Kavzo\u011flu","orcid":"https://orcid.org/0000-0002-9779-3443","observed_orcids":["https://orcid.org/0000-0002-9779-3443"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Taskin Kavzoglu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9001,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78605193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"86","issue":"9","first_page":"547","last_page":"555"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.6952999830245972,"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":0.6952999830245972,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.29350000619888306,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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":0.004000000189989805,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/building-extraction","display_name":"building extraction","score":0.9739999771118164},{"id":"https://openalex.org/keywords/worldview-2-imagery","display_name":"WorldView-2 imagery","score":0.972000002861023},{"id":"https://openalex.org/keywords/taguchi-method","display_name":"Taguchi method","score":0.9660000205039978},{"id":"https://openalex.org/keywords/multiscale-segmentation","display_name":"multi-scale segmentation","score":0.9549999833106995},{"id":"https://openalex.org/keywords/quality-rate","display_name":"quality rate","score":0.9620000123977661},{"id":"https://openalex.org/keywords/parameter-optimization","display_name":"parameter optimization","score":0.7570000290870667},{"id":"https://openalex.org/keywords/land-use-land-cover-classification","display_name":"land use and land cover classification","score":0.8539999723434448},{"id":"https://openalex.org/keywords/analysis-of-variance","display_name":"analysis of variance","score":0.7070000171661377},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.8180000185966492},{"id":"https://openalex.org/keywords/linear-regression","display_name":"linear regression","score":0.9639999866485596}],"concepts":[{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.6337047219276428},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6101463437080383},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5247057676315308},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5196143984794617},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.504336953163147},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.48904404044151306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43434906005859375},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42505815625190735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41841748356819153},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.41722536087036133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40736931562423706},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4026448726654053},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3975948393344879},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2957298159599304},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2767913341522217},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.21020367741584778},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.09713277220726013},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14358/pers.86.9.547","doi":"https://doi.org/10.14358/pers.86.9.547","is_oa":false,"landing_page_url":"https://doi.org/10.14358/pers.86.9.547","pdf_url":null,"source":{"id":"https://openalex.org/S99003644","display_name":"Photogrammetric Engineering & Remote Sensing","issn_l":"0099-1112","issn":["0099-1112","2374-8079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800734","host_organization_name":"American Society for Photogrammetry and Remote Sensing","host_organization_lineage":["https://openalex.org/P4320800734"],"host_organization_lineage_names":["American Society for Photogrammetry and Remote Sensing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Photogrammetric Engineering &amp; Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Life on land","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/15"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2911313947","https://openalex.org/W2323600994","https://openalex.org/W2382988678","https://openalex.org/W1967075819","https://openalex.org/W4214806112","https://openalex.org/W2963892648","https://openalex.org/W2466699932","https://openalex.org/W2791373126","https://openalex.org/W2058132610","https://openalex.org/W2374585118"],"abstract_inverted_index":{"Due":[0],"to":[1,49,72,112],"the":[2,12,29,54,74,77,88,114,117],"complex":[3],"spectral":[4],"and":[5,59,81,97,101,106,131,137],"spatial":[6],"structures":[7],"of":[8,14,31,35,67,76,95,116],"remotely":[9],"sensed":[10],"images,":[11],"delineation":[13],"land":[15],"use/land":[16],"cover":[17],"classes":[18],"using":[19,42,53],"conventional":[20],"approaches":[21],"is":[22],"a":[23,39],"challenging":[24],"task.":[25],"This":[26],"article":[27],"tackles":[28],"problem":[30],"seeking":[32],"optimal":[33,51],"parameters":[34,52,78],"multi-resolution":[36],"segmentation":[37],"for":[38,79,99,134],"classification":[40],"task":[41],"WorldView-2":[43],"imagery.":[44],"Taguchi":[45,123],"optimization":[46,124],"was":[47,69,87,125],"applied":[48],"search":[50],"plateau":[55],"objective":[56],"function":[57],"(POF)":[58],"quality":[60],"rate":[61],"(Qr)":[62],"as":[63],"fitness":[64],"criteria.":[65],"Analysis":[66],"variance":[68],"also":[70],"used":[71,111],"estimate":[73],"contributions":[75],"POF":[80,100,136],"Qr,":[82,102],"separately.":[83],"The":[84],"scale":[85],"parameter":[86],"most":[89],"effective":[90,127],"one,":[91],"with":[92],"contribution":[93],"levels":[94],"87.45%":[96],"56.87%":[98],"respectively.":[103],"Linear":[104],"regression":[105,108,130,133],"support-vector":[107,132],"methods":[109],"were":[110],"predict":[113],"results":[115,120],"experiment.":[118],"Test":[119],"revealed":[121],"that":[122],"more":[126],"than":[128],"linear":[129],"predicting":[135],"Qr":[138],"values.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2020-09-11T00:00:00"}
