{"id":"https://openalex.org/W4389137516","doi":"https://doi.org/10.1145/3615900.3628791","title":"Predicting urban tree cover from incomplete point labels and limited background information","display_name":"Predicting urban tree cover from incomplete point labels and limited background information","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4389137516","doi":"https://doi.org/10.1145/3615900.3628791"},"language":"en","primary_location":{"id":"doi:10.1145/3615900.3628791","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615900.3628791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI","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/A5101670240","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0002-0992-5830"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024785374","display_name":"Ankit Kariryaa","orcid":"https://orcid.org/0000-0001-9284-7847"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Ankit Kariryaa","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068614491","display_name":"Venkanna Babu Guthula","orcid":"https://orcid.org/0000-0001-5902-5905"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Venkanna Babu Guthula","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042628612","display_name":"Christian Igel","orcid":"https://orcid.org/0000-0003-2868-0856"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Christian Igel","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017031707","display_name":"Stefan Oehmcke","orcid":"https://orcid.org/0000-0002-0240-1559"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Stefan Oehmcke","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101670240"],"corresponding_institution_ids":["https://openalex.org/I124055696"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15051791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"52","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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":0.9958999752998352,"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/cover","display_name":"Cover (algebra)","score":0.7434629797935486},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.550806999206543},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5364431142807007},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4753451347351074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3583475947380066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1654321253299713},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1214032769203186},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08033180236816406}],"concepts":[{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.7434629797935486},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.550806999206543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5364431142807007},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4753451347351074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3583475947380066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1654321253299713},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1214032769203186},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08033180236816406},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3615900.3628791","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3615900.3628791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/0f911c7b-1529-4752-a36f-df61b4676430","is_oa":false,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/0f911c7b-1529-4752-a36f-df61b4676430","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhang , H , Kariryaa , A , Guthula , V B , Igel , C & Oehmcke , S 2023 , Predicting urban tree cover from incomplete point labels and limited background information . in O A Omitaomu , A Mostafavi & Y Liu (eds) , Urban-AI 2023 - Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI . Association for Computing Machinery, Inc. , pp. 52-60 , 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI, Urban-AI 2023 , Hamburg , Germany , 13/11/2023 . https://doi.org/10.1145/3615900.3628791","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G5394559786","display_name":null,"funder_award_id":"34306","funder_id":"https://openalex.org/F4320310490","funder_display_name":"Villum Fonden"},{"id":"https://openalex.org/G5764830279","display_name":null,"funder_award_id":"DeReEco","funder_id":"https://openalex.org/F4320310490","funder_display_name":"Villum Fonden"},{"id":"https://openalex.org/G7892086459","display_name":null,"funder_award_id":"NNF21OC0069116","funder_id":"https://openalex.org/F4320325957","funder_display_name":"Novo Nordisk Fonden"}],"funders":[{"id":"https://openalex.org/F4320310490","display_name":"Villum Fonden","ror":"https://ror.org/007ww2d15"},{"id":"https://openalex.org/F4320322436","display_name":"Novo Nordisk","ror":"https://ror.org/0435rc536"},{"id":"https://openalex.org/F4320325957","display_name":"Novo Nordisk Fonden","ror":"https://ror.org/04txyc737"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W611457968","https://openalex.org/W1495267108","https://openalex.org/W1561442812","https://openalex.org/W1901129140","https://openalex.org/W1989750313","https://openalex.org/W2029731618","https://openalex.org/W2055289854","https://openalex.org/W2114487471","https://openalex.org/W2120841153","https://openalex.org/W2169551590","https://openalex.org/W2549766072","https://openalex.org/W2565950292","https://openalex.org/W2769833683","https://openalex.org/W2799406003","https://openalex.org/W2991979976","https://openalex.org/W3036762856","https://openalex.org/W3091093964","https://openalex.org/W3092811956","https://openalex.org/W3163974261","https://openalex.org/W3192247133"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4232403550","https://openalex.org/W623607250","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"Trees":[0],"inside":[1],"cities":[2],"are":[3],"important":[4],"for":[5,41,60],"the":[6,12,18],"urban":[7,19,43],"microclimate,":[8],"contributing":[9],"positively":[10],"to":[11,80,97],"physical":[13],"and":[14,52,69,78,85,95],"mental":[15],"health":[16],"of":[17],"dwellers.":[20],"Despite":[21],"their":[22],"importance,":[23],"often":[24,83],"only":[25],"limited":[26,50],"information":[27],"about":[28],"city":[29],"trees":[30,44],"is":[31],"available.":[32],"Therefore":[33],"in":[34,45],"this":[35,61],"paper,":[36],"we":[37],"propose":[38],"a":[39],"method":[40],"mapping":[42],"high-resolution":[46],"aerial":[47],"imagery":[48],"using":[49],"datasets":[51,104],"deep":[53],"learning.":[54],"Deep":[55],"learning":[56],"has":[57],"become":[58],"best-practice":[59],"task,":[62],"however,":[63],"existing":[64],"approaches":[65],"rely":[66],"on":[67],"large":[68],"accurately":[70],"labelled":[71],"training":[72],"datasets,":[73],"which":[74],"can":[75,92],"be":[76,89,93],"difficult":[77,100],"expensive":[79],"obtain.":[81],"However,":[82],"noisy":[84],"incomplete":[86],"data":[87],"may":[88],"available":[90],"that":[91],"combined":[94],"utilized":[96],"solve":[98],"more":[99],"tasks":[101],"than":[102],"those":[103],"were":[105],"intended":[106],"for.":[107]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}