{"id":"https://openalex.org/W2563453975","doi":"https://doi.org/10.1080/13658816.2016.1267736","title":"A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships","display_name":"A simplified linear feature matching method using decision tree analysis, weighted linear directional mean, and topological relationships","publication_year":2016,"publication_date":"2016-12-26","ids":{"openalex":"https://openalex.org/W2563453975","doi":"https://doi.org/10.1080/13658816.2016.1267736","mag":"2563453975"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2016.1267736","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2016.1267736","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},"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/A5043962129","display_name":"Ick-Hoi Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ick-Hoi Kim","raw_affiliation_strings":["Department of Geography, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Geography, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026836764","display_name":"Chen\u2010Chieh Feng","orcid":"https://orcid.org/0000-0003-0410-714X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Chen-Chieh Feng","raw_affiliation_strings":["Department of Geography, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Geography, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037305607","display_name":"Yi\u2010Chen Wang","orcid":"https://orcid.org/0000-0002-3034-7377"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yi-Chen Wang","raw_affiliation_strings":["Department of Geography, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Department of Geography, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026836764"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":2.2088,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.87728346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"31","issue":"5","first_page":"1042","last_page":"1060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9986000061035156,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7609829902648926},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.640233039855957},{"id":"https://openalex.org/keywords/conflation","display_name":"Conflation","score":0.6313312649726868},{"id":"https://openalex.org/keywords/hausdorff-distance","display_name":"Hausdorff distance","score":0.6211525201797485},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5873852372169495},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5453769564628601},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5280274748802185},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5159376263618469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5149510502815247},{"id":"https://openalex.org/keywords/optimal-matching","display_name":"Optimal matching","score":0.45993900299072266},{"id":"https://openalex.org/keywords/feature-matching","display_name":"Feature matching","score":0.4484744071960449},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.436258465051651},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43100452423095703},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3946738541126251},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3940306305885315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38569095730781555},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3502661883831024},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.27911949157714844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15075117349624634},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10344627499580383},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09699487686157227}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7609829902648926},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.640233039855957},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.6313312649726868},{"id":"https://openalex.org/C141898687","wikidata":"https://www.wikidata.org/wiki/Q1501997","display_name":"Hausdorff distance","level":2,"score":0.6211525201797485},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5873852372169495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5453769564628601},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5280274748802185},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5159376263618469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5149510502815247},{"id":"https://openalex.org/C123853557","wikidata":"https://www.wikidata.org/wiki/Q7098946","display_name":"Optimal matching","level":3,"score":0.45993900299072266},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.4484744071960449},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.436258465051651},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43100452423095703},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3946738541126251},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3940306305885315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38569095730781555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3502661883831024},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27911949157714844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15075117349624634},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10344627499580383},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09699487686157227},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/13658816.2016.1267736","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2016.1267736","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/140963","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/140963","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Taylor & Francis","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1518864151","https://openalex.org/W1542403326","https://openalex.org/W1601497261","https://openalex.org/W1964671814","https://openalex.org/W1969536374","https://openalex.org/W1977093968","https://openalex.org/W1977984281","https://openalex.org/W1995875735","https://openalex.org/W2000033515","https://openalex.org/W2003086357","https://openalex.org/W2004746914","https://openalex.org/W2015065043","https://openalex.org/W2017378397","https://openalex.org/W2025785578","https://openalex.org/W2031944479","https://openalex.org/W2044572444","https://openalex.org/W2045034287","https://openalex.org/W2049069062","https://openalex.org/W2055815280","https://openalex.org/W2071104750","https://openalex.org/W2102285165","https://openalex.org/W2125055259","https://openalex.org/W2127402163","https://openalex.org/W2149706766","https://openalex.org/W2160580257","https://openalex.org/W4236137412"],"related_works":["https://openalex.org/W2368294766","https://openalex.org/W140762774","https://openalex.org/W2102212252","https://openalex.org/W2012299618","https://openalex.org/W3146783134","https://openalex.org/W2166273079","https://openalex.org/W2370385090","https://openalex.org/W2370512216","https://openalex.org/W2353194901","https://openalex.org/W2972344601"],"abstract_inverted_index":{"Linear":[0],"feature":[1,37,100,205],"matching":[2,38,101,116,124,133,145],"is":[3,81,199],"one":[4],"of":[5,23,61,65,96,185],"the":[6,21,49,51,58,66,87,90,94,97,119,127,135,138,147,149,196],"crucial":[7],"components":[8],"for":[9,86,203],"data":[10,19,25,29],"conflation":[11],"that":[12,157,195],"sees":[13],"its":[14],"usefulness":[15,95],"in":[16,27],"updating":[17],"existing":[18],"through":[20],"integration":[22],"newer":[24],"and":[26,43,72,89,110,137,141,151,172,177,189],"evaluating":[28],"accuracy.":[30],"This":[31],"article":[32],"presents":[33],"a":[34],"simplified":[35],"linear":[36,68,99,204],"method":[39,198],"to":[40,83],"conflate":[41],"historical":[42],"current":[44],"road":[45],"data.":[46],"To":[47,92],"measure":[48],"similarity,":[50],"shorter":[52],"line":[53],"median":[54],"Hausdorff":[55],"distance":[56],"(SMHD),":[57],"absolute":[59],"value":[60],"cosine":[62],"similarity":[63],"(aCS)":[64],"weighted":[67],"directional":[69],"mean":[70],"values,":[71],"topological":[73,152,178],"relationships":[74],"are":[75,108],"adopted.":[76],"The":[77,192],"decision":[78],"tree":[79],"analysis":[80],"employed":[82],"derive":[84],"thresholds":[85],"SMHD":[88,128,136],"aCS.":[91],"demonstrate":[93],"simple":[98,200],"method,":[102],"four":[103],"models":[104],"with":[105,125,134,146,183],"incremental":[106],"configurations":[107],"designed":[109],"tested:":[111],"(1)":[112],"Model":[113,122,131,143,158],"1:":[114],"one-to-one":[115],"based":[117],"on":[118],"SMHD;":[120],"(2)":[121],"2:":[123],"only":[126,162],"threshold;":[129],"(3)":[130],"3:":[132],"aCS":[139],"thresholds;":[140],"(4)":[142],"4:":[144],"SMHD,":[148],"aCS,":[150],"relationships.":[153],"These":[154],"experiments":[155],"suggest":[156,194],"2,":[159],"which":[160,174],"considers":[161],"distance,":[163],"does":[164],"not":[165],"provide":[166],"stable":[167,181],"results,":[168],"while":[169],"Models":[170],"3":[171],"4,":[173],"consider":[175],"direction":[176],"relationships,":[179],"produce":[180],"results":[182,193],"levels":[184],"accuracy":[186],"around":[187],"90%":[188],"95%,":[190],"respectively.":[191],"proposed":[197],"yet":[201],"robust":[202],"matching.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}