{"id":"https://openalex.org/W4401856308","doi":"https://doi.org/10.3390/rs16163056","title":"Utilizing Multi-Source Geospatial Big Data to Examine How Environmental Factors Attract Outdoor Jogging Activities","display_name":"Utilizing Multi-Source Geospatial Big Data to Examine How Environmental Factors Attract Outdoor Jogging Activities","publication_year":2024,"publication_date":"2024-08-20","ids":{"openalex":"https://openalex.org/W4401856308","doi":"https://doi.org/10.3390/rs16163056"},"language":"en","primary_location":{"id":"doi:10.3390/rs16163056","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16163056","pdf_url":"https://www.mdpi.com/2072-4292/16/16/3056/pdf?version=1724144024","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/16/3056/pdf?version=1724144024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108973969","display_name":"Tingyan Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tingyan Shi","raw_affiliation_strings":["College of Art and Science, New York University, New York, NY 11201, USA"],"affiliations":[{"raw_affiliation_string":"College of Art and Science, New York University, New York, NY 11201, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021117983","display_name":"Feng Gao","orcid":"https://orcid.org/0000-0003-0398-4255"},"institutions":[{"id":"https://openalex.org/I4210126705","display_name":"Guangzhou Urban Planning Survey & Design Institute","ror":"https://ror.org/02crg7060","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210126705"]},{"id":"https://openalex.org/I4210155564","display_name":"Guangzhou Science, Technology and Innovation Commission","ror":"https://ror.org/05t4nb462","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210155564"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feng Gao","raw_affiliation_strings":["Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China","Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China","Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Enterprise Key Laboratory for Urban Sensing, Monitoring and Early Warning, Guangzhou 510060, China","institution_ids":[]},{"raw_affiliation_string":"Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China","institution_ids":["https://openalex.org/I4210155564"]},{"raw_affiliation_string":"Guangzhou Urban Planning & Design Survey Research Institute Co., Ltd., Guangzhou 510060, China","institution_ids":["https://openalex.org/I4210126705"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021117983"],"corresponding_institution_ids":["https://openalex.org/I4210126705","https://openalex.org/I4210155564"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":12.2104,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.98708669,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"16","issue":"16","first_page":"3056","last_page":"3056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10298","display_name":"Urban Transport and Accessibility","score":0.9997000098228455,"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":0.9997000098228455,"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/T10692","display_name":"Urban Green Space and Health","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11793","display_name":"Recreation, Leisure, Wilderness Management","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.7770754098892212},{"id":"https://openalex.org/keywords/built-environment","display_name":"Built environment","score":0.5444011688232422},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4924110174179077},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.47240346670150757},{"id":"https://openalex.org/keywords/geographically-weighted-regression","display_name":"Geographically Weighted Regression","score":0.44253793358802795},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4063074588775635},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3744761347770691},{"id":"https://openalex.org/keywords/environmental-resource-management","display_name":"Environmental resource management","score":0.3465484380722046},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3279457092285156},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.28045853972435},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.251065194606781},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15182387828826904},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14517265558242798},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.136849045753479},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12160259485244751},{"id":"https://openalex.org/keywords/civil-engineering","display_name":"Civil engineering","score":0.10406234860420227},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08566495776176453}],"concepts":[{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.7770754098892212},{"id":"https://openalex.org/C148803439","wikidata":"https://www.wikidata.org/wiki/Q4986688","display_name":"Built environment","level":2,"score":0.5444011688232422},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4924110174179077},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.47240346670150757},{"id":"https://openalex.org/C2910321205","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geographically Weighted Regression","level":2,"score":0.44253793358802795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4063074588775635},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3744761347770691},{"id":"https://openalex.org/C107826830","wikidata":"https://www.wikidata.org/wiki/Q929380","display_name":"Environmental resource management","level":1,"score":0.3465484380722046},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3279457092285156},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.28045853972435},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.251065194606781},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15182387828826904},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14517265558242798},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.136849045753479},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12160259485244751},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.10406234860420227},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08566495776176453},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs16163056","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16163056","pdf_url":"https://www.mdpi.com/2072-4292/16/16/3056/pdf?version=1724144024","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a9e8ae960e5146eb9f626bdda7e62134","is_oa":true,"landing_page_url":"https://doaj.org/article/a9e8ae960e5146eb9f626bdda7e62134","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 16, p 3056 (2024)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/16/16/3056/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs16163056","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs16163056","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16163056","pdf_url":"https://www.mdpi.com/2072-4292/16/16/3056/pdf?version=1724144024","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7699999809265137}],"awards":[{"id":"https://openalex.org/G1175592645","display_name":null,"funder_award_id":"2022YFC3800704-2","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401856308.pdf","grobid_xml":"https://content.openalex.org/works/W4401856308.grobid-xml"},"referenced_works_count":75,"referenced_works":["https://openalex.org/W987751915","https://openalex.org/W1958782862","https://openalex.org/W1966888350","https://openalex.org/W1977556410","https://openalex.org/W1987233492","https://openalex.org/W2001050716","https://openalex.org/W2006767569","https://openalex.org/W2062108920","https://openalex.org/W2070638955","https://openalex.org/W2113842135","https://openalex.org/W2144512297","https://openalex.org/W2163283323","https://openalex.org/W2169368100","https://openalex.org/W2169813901","https://openalex.org/W2216903345","https://openalex.org/W2276093141","https://openalex.org/W2339252961","https://openalex.org/W2478090196","https://openalex.org/W2560023338","https://openalex.org/W2793486875","https://openalex.org/W2890231632","https://openalex.org/W2899128325","https://openalex.org/W2916829009","https://openalex.org/W2962764844","https://openalex.org/W2999339909","https://openalex.org/W2999819528","https://openalex.org/W3000665717","https://openalex.org/W3010184311","https://openalex.org/W3024110832","https://openalex.org/W3090335068","https://openalex.org/W3092250696","https://openalex.org/W3093292596","https://openalex.org/W3118378166","https://openalex.org/W3118777781","https://openalex.org/W3120447743","https://openalex.org/W3137817591","https://openalex.org/W3147335260","https://openalex.org/W3148541183","https://openalex.org/W3164049546","https://openalex.org/W3166458872","https://openalex.org/W3166836859","https://openalex.org/W3168809040","https://openalex.org/W3170621952","https://openalex.org/W3186651210","https://openalex.org/W3192577330","https://openalex.org/W4200560510","https://openalex.org/W4206673664","https://openalex.org/W4207062688","https://openalex.org/W4225095656","https://openalex.org/W4280632598","https://openalex.org/W4284675861","https://openalex.org/W4297015111","https://openalex.org/W4297539071","https://openalex.org/W4310725244","https://openalex.org/W4313593989","https://openalex.org/W4317622048","https://openalex.org/W4362451528","https://openalex.org/W4362475835","https://openalex.org/W4375945112","https://openalex.org/W4376155524","https://openalex.org/W4383497944","https://openalex.org/W4386435973","https://openalex.org/W4386579416","https://openalex.org/W4387520943","https://openalex.org/W4388084092","https://openalex.org/W4388108748","https://openalex.org/W4389113894","https://openalex.org/W4389321524","https://openalex.org/W4391517495","https://openalex.org/W4391731565","https://openalex.org/W4392858280","https://openalex.org/W4393238350","https://openalex.org/W4398773964","https://openalex.org/W4401078112","https://openalex.org/W6857233133"],"related_works":["https://openalex.org/W4367313141","https://openalex.org/W4283374591","https://openalex.org/W2004086023","https://openalex.org/W2733999579","https://openalex.org/W2110217573","https://openalex.org/W2910751785","https://openalex.org/W4390100400","https://openalex.org/W4366547507","https://openalex.org/W4362512700","https://openalex.org/W4390608645"],"abstract_inverted_index":{"In":[0],"the":[1,16,27,30,62,68,99,102,113,136,165,169,173,177,181,188,191,209,215,230,246,260,286,291],"post-pandemic":[2],"era,":[3],"outdoor":[4,34,71,77],"jogging":[5,35,72,78,223,243,266,283,308],"has":[6],"become":[7],"an":[8,145],"increasingly":[9],"popular":[10],"form":[11],"of":[12,33,70,101,176,190,232,249,262],"exercise":[13],"due":[14],"to":[15,24,38,60,160,194,214,323],"growing":[17],"emphasis":[18],"on":[19,94,187,265],"health.":[20],"It":[21],"is":[22],"essential":[23],"comprehensively":[25],"analyze":[26],"factors":[28,90,241],"influencing":[29,89,242],"spatial":[31,174,201,270],"distribution":[32],"activities":[36,73,267],"and":[37,50,67,87,107,122,150,171,203,218,234,254,276,307,320],"propose":[39,195],"planning":[40,197,312],"strategies":[41,198],"with":[42,199,282],"practical":[43,204],"guidance.":[44],"Using":[45],"multi-source":[46,95],"geospatial":[47],"big":[48,96],"data":[49,80,97],"multiple":[51],"models,":[52],"this":[53],"study":[54,182,292],"constructs":[55],"a":[56,84,132,141,151],"comprehensive":[57],"analytical":[58],"framework":[59,137],"examine":[61],"association":[63],"between":[64,305],"environmental":[65,117],"variables":[66,306],"frequency":[69,224,284],"in":[74,285],"Guangzhou.":[75],"Firstly,":[76],"trajectory":[79],"were":[81,91,129,237,279],"collected":[82],"from":[83,98,131],"fitness":[85],"app,":[86],"potential":[88],"selected":[92],"based":[93,186],"perspectives":[100],"built":[103,216],"environment,":[104],"street":[105,219],"perception,":[106,253,256],"natural":[108],"environment.":[109],"For":[110,272],"example,":[111],"using":[112],"street-view":[114],"imagery,":[115],"objective":[116,252],"elements":[118,124],"such":[119,125],"as":[120,126,239],"greenery":[121,277],"subjective":[123,255],"safety":[127,235],"perception":[128,220,236],"extracted":[130],"human-centric":[133],"perspective.":[134],"Secondly,":[135],"included":[138],"three":[139,247],"models:":[140],"backward":[142],"stepwise":[143],"regression,":[144],"optimal":[146],"parameters-based":[147],"geographical":[148],"detector,":[149],"geographically":[152],"weighted":[153],"regression":[154],"(GWR)":[155],"model.":[156],"These":[157],"models":[158],"served,":[159],"screen":[161],"significant":[162,269,315],"variables,":[163,170],"identify":[164],"synergistic":[166],"effects":[167],"among":[168],"quantify":[172],"heterogeneity":[175],"effects,":[178],"respectively.":[179,257],"Finally,":[180],"area":[183,293],"was":[184,294],"clustered":[185],"results":[189,207],"GWR":[192],"model":[193],"urban":[196,318],"clear":[200],"positions":[202],"significance.":[205],"The":[206,310],"indicated":[208],"following:":[210],"(1)":[211],"Factors":[212],"related":[213],"environment":[217],"significantly":[221],"influence":[222,261],"distribution.":[225],"(2)":[226],"Public":[227],"sports":[228,274],"facilities,":[229,251],"level":[231,278],"greenery,":[233],"identified":[238],"key":[240],"activities,":[244],"representing":[245,300],"aspects":[248],"service":[250],"(3)":[258],"Specifically,":[259],"each":[263,299],"factor":[264],"displayed":[268],"variation.":[271],"instance,":[273],"facilities":[275],"positively":[280],"correlated":[281],"city":[287],"center.":[288],"(4)":[289],"Lastly,":[290],"divided":[295],"into":[296],"four":[297],"clusters,":[298],"different":[301],"local":[302],"associative":[303],"characteristics":[304],"activities.":[309],"zonal":[311],"recommendations":[313],"have":[314],"implications":[316],"for":[317],"planners":[319],"policymakers":[321],"aiming":[322],"create":[324],"jogging-friendly":[325],"environments.":[326]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}
