{"id":"https://openalex.org/W3021334113","doi":"https://doi.org/10.1080/13658816.2020.1759806","title":"Efficient regionalization for spatially explicit neighborhood delineation","display_name":"Efficient regionalization for spatially explicit neighborhood delineation","publication_year":2020,"publication_date":"2020-05-05","ids":{"openalex":"https://openalex.org/W3021334113","doi":"https://doi.org/10.1080/13658816.2020.1759806","mag":"3021334113"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2020.1759806","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2020.1759806","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/A5011421770","display_name":"Ran Wei","orcid":"https://orcid.org/0000-0002-2737-1712"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ran Wei","raw_affiliation_strings":["Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004811779","display_name":"Sergio J. Rey","orcid":"https://orcid.org/0000-0001-5857-9762"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sergio Rey","raw_affiliation_strings":["Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072323207","display_name":"Elijah Knaap","orcid":"https://orcid.org/0000-0001-7520-2238"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elijah Knaap","raw_affiliation_strings":["Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA"],"affiliations":[{"raw_affiliation_string":"Center for Geospatial Sciences, School of Public Policy, University of California, Riverside, CA, USA","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004811779"],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":5.8955,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.95680346,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"35","issue":"1","first_page":"135","last_page":"151"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10298","display_name":"Urban Transport and Accessibility","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10298","display_name":"Urban Transport and Accessibility","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"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/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.7668119668960571},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6310399770736694},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5252392292022705},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5159576535224915},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48497438430786133},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4598219692707062},{"id":"https://openalex.org/keywords/efficient-algorithm","display_name":"Efficient algorithm","score":0.4104940891265869},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33148038387298584},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3068578243255615},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.28676652908325195},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2655846178531647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2187362015247345}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7668119668960571},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6310399770736694},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5252392292022705},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5159576535224915},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48497438430786133},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4598219692707062},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.4104940891265869},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33148038387298584},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3068578243255615},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.28676652908325195},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2655846178531647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2187362015247345},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/13658816.2020.1759806","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2020.1759806","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G1893344766","display_name":null,"funder_award_id":"SES-1733705","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3603997417","display_name":null,"funder_award_id":"SES-1831615","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W74935743","https://openalex.org/W172963486","https://openalex.org/W1533459960","https://openalex.org/W1547981617","https://openalex.org/W1843684519","https://openalex.org/W1851934214","https://openalex.org/W1892336054","https://openalex.org/W1952692938","https://openalex.org/W1967137980","https://openalex.org/W1983859220","https://openalex.org/W1984121786","https://openalex.org/W1987114813","https://openalex.org/W2035955308","https://openalex.org/W2058529928","https://openalex.org/W2067344376","https://openalex.org/W2090275183","https://openalex.org/W2092519803","https://openalex.org/W2104670598","https://openalex.org/W2117746342","https://openalex.org/W2117997410","https://openalex.org/W2118898434","https://openalex.org/W2121427128","https://openalex.org/W2139839146","https://openalex.org/W2158672897","https://openalex.org/W2178471055","https://openalex.org/W2254083598","https://openalex.org/W2260567607","https://openalex.org/W2300880524","https://openalex.org/W2486224434","https://openalex.org/W2499641349","https://openalex.org/W2512880873","https://openalex.org/W2546838348","https://openalex.org/W2736558540","https://openalex.org/W2997776631","https://openalex.org/W4246598646"],"related_works":["https://openalex.org/W2327204559","https://openalex.org/W3129254793","https://openalex.org/W2587671147","https://openalex.org/W2623240261","https://openalex.org/W2144844759","https://openalex.org/W2366567522","https://openalex.org/W2386767533","https://openalex.org/W2355215981","https://openalex.org/W2347219288","https://openalex.org/W2366221835"],"abstract_inverted_index":{"Neighborhood":[0],"delineation":[1,49,80],"is":[2,33,129],"increasingly":[3],"relied":[4],"upon":[5],"in":[6,131],"urban":[7],"social":[8],"science":[9],"research":[10],"to":[11,41,64,106],"identify":[12],"the":[13,23,30,74,83,108,114,132,152],"most":[14],"appropriate":[15],"spatial":[16],"unit.":[17],"In":[18,69,98],"problems":[19],"of":[20,26,55,76,92],"this":[21,70],"type,":[22],"true":[24],"number":[25],"neighborhoods":[27],"(typically":[28],"called":[29],"k":[31,43],"parameter)":[32],"unknown":[34],"and":[35,94,145,151,157],"analysts":[36],"often":[37],"require":[38,53],"algorithmic":[39],"approaches":[40,46],"determine":[42],"endogenously.":[44],"Existing":[45],"for":[47,78,122],"neighborhood":[48,79,124],"that":[50,82,117],"do":[51],"not":[52],"pre-specification":[54],"a":[56,90,102],"k-parameter,":[57],"however,":[58],"are":[59,149],"either":[60],"nonspatial":[61],"or":[62,66],"lead":[63],"noncontiguous":[65],"overlapping":[67],"regions.":[68],"paper,":[71],"we":[72,100],"propose":[73],"use":[75],"max-p-regions":[77,115],"so":[81,116],"geographic":[84],"space":[85],"can":[86,119],"be":[87,120],"partitioned":[88],"into":[89],"set":[91],"homogeneous":[93],"geographically":[95],"contiguous":[96],"neighborhoods.":[97],"addition,":[99],"developed":[101],"new":[103,127],"efficient":[104],"algorithm":[105,128],"address":[107],"computational":[109],"challenges":[110],"associated":[111],"with":[112],"solving":[113],"it":[118],"applied":[121],"large-scale":[123],"delineation.":[125],"This":[126],"implemented":[130],"open-source":[133],"Python":[134],"Spatial":[135],"Analysis":[136],"Library":[137],"(PySAL).":[138],"Computational":[139],"experiments":[140],"based":[141],"on":[142],"both":[143],"simulated":[144],"realistic":[146],"data":[147],"sets":[148],"performed":[150],"results":[153],"demonstrate":[154],"its":[155],"effectiveness":[156],"efficiency.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":5}],"updated_date":"2026-02-27T16:54:17.756197","created_date":"2025-10-10T00:00:00"}