{"id":"https://openalex.org/W2612469777","doi":"https://doi.org/10.1109/jurse.2017.7924590","title":"Evaluating the relationship between spatial and spectral features derived from high spatial resolution satellite data and urban poverty in Colombo, Sri Lanka","display_name":"Evaluating the relationship between spatial and spectral features derived from high spatial resolution satellite data and urban poverty in Colombo, Sri Lanka","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2612469777","doi":"https://doi.org/10.1109/jurse.2017.7924590","mag":"2612469777"},"language":"en","primary_location":{"id":"doi:10.1109/jurse.2017.7924590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jurse.2017.7924590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Joint Urban Remote Sensing Event (JURSE)","raw_type":"proceedings-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/A5045808718","display_name":"Ryan Engstrom","orcid":"https://orcid.org/0000-0002-3063-0551"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ryan Engstrom","raw_affiliation_strings":["Department of Geography, The George Washington University, District of Columbia, Washington"],"affiliations":[{"raw_affiliation_string":"Department of Geography, The George Washington University, District of Columbia, Washington","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089159541","display_name":"David Newhouse","orcid":"https://orcid.org/0000-0003-4051-8130"},"institutions":[{"id":"https://openalex.org/I55633929","display_name":"World Bank Group","ror":"https://ror.org/02md09461","country_code":"US","type":"other","lineage":["https://openalex.org/I55633929"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Newhouse","raw_affiliation_strings":["Poverty Global Practice Group, The World Bank, District of Columbia, Washington"],"affiliations":[{"raw_affiliation_string":"Poverty Global Practice Group, The World Bank, District of Columbia, Washington","institution_ids":["https://openalex.org/I55633929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040529149","display_name":"Vishwesh Haldavanekar","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishwesh Haldavanekar","raw_affiliation_strings":["Data Science Program, The George Washington University, District of Columbia, Washington"],"affiliations":[{"raw_affiliation_string":"Data Science Program, The George Washington University, District of Columbia, Washington","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085214517","display_name":"Andrew Copenhaver","orcid":null},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Copenhaver","raw_affiliation_strings":["Department of Geography, The George Washington University, District of Columbia, Washington"],"affiliations":[{"raw_affiliation_string":"Department of Geography, The George Washington University, District of Columbia, Washington","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009433206","display_name":"Jonathan Hersh","orcid":"https://orcid.org/0000-0001-6786-5162"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Hersh","raw_affiliation_strings":["Department of Economics, Boston University, Boston, Massachusetts"],"affiliations":[{"raw_affiliation_string":"Department of Economics, Boston University, Boston, Massachusetts","institution_ids":["https://openalex.org/I111088046"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045808718"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":4.2376,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.94762735,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962999820709229,"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":0.9962999820709229,"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9952999949455261,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.9940000176429749,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.5740900039672852},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5532448291778564},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.5481158494949341},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.5033180117607117},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5027480125427246},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.49819421768188477},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4829111099243164},{"id":"https://openalex.org/keywords/percentile","display_name":"Percentile","score":0.46628403663635254},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4623371958732605},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.45530977845191956},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4262889325618744},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42299920320510864},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.41387826204299927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.22385936975479126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17075103521347046},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15502426028251648},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1306629478931427}],"concepts":[{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5740900039672852},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5532448291778564},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.5481158494949341},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.5033180117607117},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5027480125427246},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.49819421768188477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4829111099243164},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.46628403663635254},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4623371958732605},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.45530977845191956},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4262889325618744},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42299920320510864},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.41387826204299927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.22385936975479126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17075103521347046},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15502426028251648},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1306629478931427},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jurse.2017.7924590","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jurse.2017.7924590","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Joint Urban Remote Sensing Event (JURSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1500265423","https://openalex.org/W1515135833","https://openalex.org/W1530281873","https://openalex.org/W1677409904","https://openalex.org/W1969981696","https://openalex.org/W2014351994","https://openalex.org/W2017619079","https://openalex.org/W2063623478","https://openalex.org/W2070512596","https://openalex.org/W2073981548","https://openalex.org/W2083061291","https://openalex.org/W2088972316","https://openalex.org/W2093791422","https://openalex.org/W2094056275","https://openalex.org/W2102372511","https://openalex.org/W2106543613","https://openalex.org/W2131438174","https://openalex.org/W2150262608","https://openalex.org/W2152640741","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W2286788505","https://openalex.org/W2340841368","https://openalex.org/W2345272913","https://openalex.org/W2346062110","https://openalex.org/W2404611670","https://openalex.org/W2513506629","https://openalex.org/W2516854745","https://openalex.org/W2546726174"],"related_works":["https://openalex.org/W1979381110","https://openalex.org/W1992707155","https://openalex.org/W40582406","https://openalex.org/W2396658448","https://openalex.org/W3196810513","https://openalex.org/W2114530358","https://openalex.org/W2073099965","https://openalex.org/W3142310456","https://openalex.org/W2082199675","https://openalex.org/W2169211939"],"abstract_inverted_index":{"In":[0],"this":[1,26],"study":[2,27],"we":[3,28],"seek":[4],"to":[5,181,198,201],"map":[6],"urban":[7,69],"poverty":[8,207],"in":[9,51,206],"Colombo,":[10,72],"Sri":[11,73,178],"Lanka":[12],"using":[13,173,209],"spectral":[14,31,114,194],"and":[15,32,41,66,112,140,193],"spatial":[16,21,33,192],"features":[17,34,76,146,195],"estimated":[18],"from":[19,46,175],"high":[20],"resolution":[22],"satellite":[23],"imagery.":[24],"For":[25,125,149],"calculated":[29,77,172],"165":[30,145],"at":[35],"a":[36,42,210],"block":[37],"size":[38,131],"of":[39,44,64,71,90,105,107,132,143,159,163,166,185,203],"16m":[40],"range":[43],"scales,":[45],"three":[47],"Quickbird":[48],"scenes,":[49],"collected":[50],"2010":[52],"which":[53],"cover":[54],"316":[55],"Grama":[56],"Niladhari":[57],"(GN)":[58],"census":[59,128],"units":[60],"within":[61],"the":[62,68,103,108,119,136,153,160,176,190,204],"District":[63],"Colombo":[65],"includes":[67],"area":[70],"Lanka.":[74],"The":[75],"include":[78],"linear":[79,83,215],"support":[80],"regions":[81],"(LSR),":[82],"binary":[84],"pattern":[85],"moments":[86],"(LBPM),":[87],"PanTex,":[88],"Histogram":[89],"Oriented":[91],"Gradients":[92],"(HoG),":[93],"Speeded":[94],"Up":[95],"Robust":[96],"Features":[97],"(SURF),":[98],"Fourier":[99],"Transform":[100],"(FT),":[101],"Gabor,":[102],"mean":[104],"each":[106,126,150],"blue,":[109],"green,":[110],"red,":[111],"near-infrared":[113],"bands,":[115],"as":[116,118],"well":[117],"Normalized":[120],"Difference":[121],"Vegetation":[122],"Index":[123],"(NDVI).":[124],"GN":[127,151],"unit":[129],"(avg.":[130],"2.17":[133],"sq.":[134],"km),":[135],"zonal":[137],"sum,":[138],"mean,":[139],"standard":[141],"deviation":[142],"all":[144],"were":[147,171,196],"calculated.":[148],"unit,":[152],"10/20/30/40":[154],"<sup":[155],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[156],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">th</sup>":[157],"percentiles":[158],"national":[161],"distribution":[162],"household":[164],"estimates":[165],"predicted":[167],"per":[168],"capita":[169],"consumption":[170],"data":[174],"2011":[177],"Lankan":[179],"Census":[180],"provide":[182],"an":[183],"estimate":[184],"poverty.":[186],"Results":[187],"indicate":[188],"that":[189],"combined":[191],"able":[197],"explain":[199],"up":[200],"54%":[202],"variation":[205],"when":[208],"simple,":[211],"ordinary":[212],"least":[213],"squares":[214],"regression":[216],"model.":[217]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}