{"id":"https://openalex.org/W4391437548","doi":"https://doi.org/10.1080/13658816.2024.2305636","title":"A multi-glimpse deep learning architecture to estimate socioeconomic census metrics in the context of extreme scope variance","display_name":"A multi-glimpse deep learning architecture to estimate socioeconomic census metrics in the context of extreme scope variance","publication_year":2024,"publication_date":"2024-02-01","ids":{"openalex":"https://openalex.org/W4391437548","doi":"https://doi.org/10.1080/13658816.2024.2305636"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2024.2305636","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2024.2305636","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/A5063063620","display_name":"Daniel Miller Runfola","orcid":"https://orcid.org/0000-0001-5356-4676"},"institutions":[{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]},{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dan Runfola","raw_affiliation_strings":["Data Science Program, William & Mary, Williamsburg, VA, USA","Department of Applied Science, William & Mary, Williamsburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Department of Applied Science, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070909466","display_name":"Anthony Stefanidis","orcid":"https://orcid.org/0000-0002-8165-0667"},"institutions":[{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]},{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anthony Stefanidis","raw_affiliation_strings":["Data Science Program, William & Mary, Williamsburg, VA, USA","Department of Computer Science, William & Mary, Williamsburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Department of Computer Science, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083132239","display_name":"Zhonghui Lv","orcid":"https://orcid.org/0000-0001-5186-3699"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhonghui Lv","raw_affiliation_strings":["Department of Applied Science, William & Mary, Williamsburg, VA, USA","Virginia Institute of Marine Science, William & Mary, Gloucester, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Applied Science, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Virginia Institute of Marine Science, William & Mary, Gloucester, VA, USA","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027832545","display_name":"Joseph J. O\u2019Brien","orcid":"https://orcid.org/0000-0003-3446-6063"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph O\u2019Brien","raw_affiliation_strings":["Data Science Program, William & Mary, Williamsburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021900350","display_name":"Heather Baier","orcid":"https://orcid.org/0000-0002-2834-9082"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heather Baier","raw_affiliation_strings":["Data Science Program, William & Mary, Williamsburg, VA, USA","Department of Applied Science, William & Mary, Williamsburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Data Science Program, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Department of Applied Science, William & Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5063063620"],"corresponding_institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"],"apc_list":null,"apc_paid":null,"fwci":2.9894,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90592655,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"38","issue":"4","first_page":"726","last_page":"750"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11963","display_name":"Impact of Light on Environment and Health","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11963","display_name":"Impact of Light on Environment and Health","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9807000160217285,"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/satellite-imagery","display_name":"Satellite imagery","score":0.6724911332130432},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5802340507507324},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.5602173805236816},{"id":"https://openalex.org/keywords/socioeconomic-status","display_name":"Socioeconomic status","score":0.531862199306488},{"id":"https://openalex.org/keywords/census","display_name":"Census","score":0.526216983795166},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5257899761199951},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5255454778671265},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.524976909160614},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4901522099971771},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.4528064727783203},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45142120122909546},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.4305621087551117},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42432767152786255},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3505651354789734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32914382219314575},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32900339365005493},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.10644370317459106},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07374927401542664}],"concepts":[{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.6724911332130432},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5802340507507324},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5602173805236816},{"id":"https://openalex.org/C147077947","wikidata":"https://www.wikidata.org/wiki/Q1515895","display_name":"Socioeconomic status","level":3,"score":0.531862199306488},{"id":"https://openalex.org/C52130261","wikidata":"https://www.wikidata.org/wiki/Q39825","display_name":"Census","level":3,"score":0.526216983795166},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5257899761199951},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5255454778671265},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.524976909160614},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4901522099971771},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.4528064727783203},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45142120122909546},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.4305621087551117},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42432767152786255},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3505651354789734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32914382219314575},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32900339365005493},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.10644370317459106},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07374927401542664},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/13658816.2024.2305636","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2024.2305636","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":[],"awards":[{"id":"https://openalex.org/G933524813","display_name":null,"funder_award_id":"1-03-03","funder_id":"https://openalex.org/F4320337787","funder_display_name":"Homeland Defense and Security Information Analysis Center"}],"funders":[{"id":"https://openalex.org/F4320337787","display_name":"Homeland Defense and Security Information Analysis Center","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1584042284","https://openalex.org/W1686810756","https://openalex.org/W2081657528","https://openalex.org/W2086528839","https://openalex.org/W2086620533","https://openalex.org/W2109255472","https://openalex.org/W2117539524","https://openalex.org/W2277660392","https://openalex.org/W2342880667","https://openalex.org/W2513506629","https://openalex.org/W2515866431","https://openalex.org/W2556713226","https://openalex.org/W2593801968","https://openalex.org/W2600349926","https://openalex.org/W2603422184","https://openalex.org/W2618530766","https://openalex.org/W2725897987","https://openalex.org/W2732026016","https://openalex.org/W2737151197","https://openalex.org/W2769313216","https://openalex.org/W2780517933","https://openalex.org/W2789985449","https://openalex.org/W2792111852","https://openalex.org/W2884566448","https://openalex.org/W2890140875","https://openalex.org/W2899104089","https://openalex.org/W2900731800","https://openalex.org/W2912272178","https://openalex.org/W2919115771","https://openalex.org/W2940939359","https://openalex.org/W2951527505","https://openalex.org/W2963578416","https://openalex.org/W2964246847","https://openalex.org/W2983803269","https://openalex.org/W2991020922","https://openalex.org/W2995416681","https://openalex.org/W2997208123","https://openalex.org/W3000532270","https://openalex.org/W3004240810","https://openalex.org/W3016602916","https://openalex.org/W3018139790","https://openalex.org/W3027716283","https://openalex.org/W3043466072","https://openalex.org/W3043541567","https://openalex.org/W3105577662","https://openalex.org/W3106011052","https://openalex.org/W3115311933","https://openalex.org/W3118286860","https://openalex.org/W3132757466","https://openalex.org/W3133962347","https://openalex.org/W3169131408","https://openalex.org/W3174075674","https://openalex.org/W3182707437","https://openalex.org/W3204256842","https://openalex.org/W3212930866","https://openalex.org/W3217609647","https://openalex.org/W4205465039","https://openalex.org/W4220905292","https://openalex.org/W4230431864","https://openalex.org/W4252016870","https://openalex.org/W4283641761","https://openalex.org/W4288621246","https://openalex.org/W4299670613","https://openalex.org/W4313480389","https://openalex.org/W6600281192","https://openalex.org/W6682137061"],"related_works":["https://openalex.org/W2128472366","https://openalex.org/W621243299","https://openalex.org/W5594354","https://openalex.org/W4244351752","https://openalex.org/W2601163983","https://openalex.org/W2364090708","https://openalex.org/W2145323372","https://openalex.org/W1512152715","https://openalex.org/W2009948611","https://openalex.org/W2182026161"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"are":[4,32],"leveraged":[5],"for":[6,17,170,185],"a":[7,40,105,124,145],"wide":[8],"range":[9,55,106],"of":[10,69,80,97,107,119,135,144,152,173],"satellite":[11,88,114,174],"imagery":[12,115,175],"information":[13,24,86],"extraction":[14],"tasks.":[15],"However,":[16],"tasks":[18],"which":[19,54,75,130,186],"seek":[20,92],"to":[21,34,65,83,93,138,176],"estimate":[22,177],"aggregated":[23],"across":[25,50,140],"highly":[26],"variable":[27],"geographic":[28],"extents,":[29],"existing":[30],"techniques":[31],"subject":[33],"critical":[35],"limitations.":[36],"We":[37],"engage":[38],"with":[39,160],"specific":[41],"case":[42],"study":[43],"exploring":[44],"this":[45],"challenge:":[46],"estimating":[47,104],"census":[48,108],"variables":[49,109,155],"2358":[51],"Mexican":[52],"municipalities,":[53],"in":[56,129,180],"scope":[57],"from":[58,87],"2.21":[59],"km2":[60,67],"(\u02dc74,000":[61],"30":[62],"m":[63],"pixels)":[64],"72,417.9":[66],"(millions":[68],"pixels).":[70],"Building":[71],"on":[72,111],"recent":[73],"literature":[74],"has":[76],"illustrated":[77],"the":[78,153,171],"capability":[79],"deep":[81],"learning":[82],"extract":[84],"socioeconomic":[85,178],"imagery,":[89],"we":[90,122,131],"specifically":[91],"establish":[94],"baseline":[95],"metrics":[96],"error":[98],"that":[99,149],"might":[100],"be":[101,158],"expected":[102],"when":[103],"based":[110],"coarse-resolution":[112],"(Landsat)":[113],"alone.":[116],"For":[117],"each":[118,136],"52":[120],"variables,":[121],"implement":[123],"multi-glimpse":[125],"recurrent":[126],"attention":[127],"model,":[128],"parametrically":[132],"determine":[133],"subsets":[134],"municipality":[137],"sample":[139],"iterative":[141],"steps.":[142],"Results":[143,166],"five-fold":[146],"validation":[147],"indicate":[148],"nearly":[150],"half":[151],"tested":[154],"(22)":[156],"can":[157],"estimated":[159],"r2":[161],"values":[162],"greater":[163],"than":[164],"0.75.":[165],"suggest":[167],"considerable":[168],"promise":[169],"use":[172],"factors":[179],"both":[181],"historic":[182],"time":[183],"periods":[184],"surveys":[187],"were":[188],"not":[189],"conducted,":[190],"as":[191,193],"well":[192],"contemporary":[194],"inaccessible":[195],"regions.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}