{"id":"https://openalex.org/W2963998131","doi":"https://doi.org/10.3390/rs11141725","title":"Deep Fully Convolutional Networks for Cadastral Boundary Detection from UAV Images","display_name":"Deep Fully Convolutional Networks for Cadastral Boundary Detection from UAV Images","publication_year":2019,"publication_date":"2019-07-20","ids":{"openalex":"https://openalex.org/W2963998131","doi":"https://doi.org/10.3390/rs11141725","mag":"2963998131"},"language":"en","primary_location":{"id":"doi:10.3390/rs11141725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11141725","pdf_url":"https://www.mdpi.com/2072-4292/11/14/1725/pdf?version=1563618401","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/2072-4292/11/14/1725/pdf?version=1563618401","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055547394","display_name":"Xue Xia","orcid":"https://orcid.org/0000-0001-7942-4380"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Xue Xia","raw_affiliation_strings":["Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029035818","display_name":"Claudio Persello","orcid":"https://orcid.org/0000-0003-3742-5398"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Claudio Persello","raw_affiliation_strings":["Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001059507","display_name":"Mila Koeva","orcid":"https://orcid.org/0000-0001-7612-5270"},"institutions":[{"id":"https://openalex.org/I94624287","display_name":"University of Twente","ror":"https://ror.org/006hf6230","country_code":"NL","type":"education","lineage":["https://openalex.org/I94624287"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Mila Koeva","raw_affiliation_strings":["Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7522 NB Enschede, The Netherlands","institution_ids":["https://openalex.org/I94624287"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029035818"],"corresponding_institution_ids":["https://openalex.org/I94624287"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.9938,"has_fulltext":true,"cited_by_count":63,"citation_normalized_percentile":{"value":0.93652679,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"11","issue":"14","first_page":"1725","last_page":"1725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9993000030517578,"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":0.9993000030517578,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/cadastre","display_name":"Cadastre","score":0.980652928352356},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5835519433021545},{"id":"https://openalex.org/keywords/digitization","display_name":"Digitization","score":0.551987886428833},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5421584248542786},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5049946904182434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4752782881259918},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.4295501708984375},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.40465885400772095},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39031651616096497},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.27408772706985474},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10122981667518616}],"concepts":[{"id":"https://openalex.org/C134207755","wikidata":"https://www.wikidata.org/wiki/Q191072","display_name":"Cadastre","level":2,"score":0.980652928352356},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5835519433021545},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.551987886428833},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5421584248542786},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5049946904182434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4752782881259918},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.4295501708984375},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.40465885400772095},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39031651616096497},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.27408772706985474},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10122981667518616},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/rs11141725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11141725","pdf_url":"https://www.mdpi.com/2072-4292/11/14/1725/pdf?version=1563618401","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:ris.utwente.nl:openaire/a4e6a109-bd30-4b2a-8765-92c4e657bbbf","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/a4e6a109-bd30-4b2a-8765-92c4e657bbbf","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Xia, X, Persello, C & Koeva, M N 2019, 'Deep Fully Convolutional Networks for Cadastral Boundary Detection from UAV Images', Remote sensing, vol. 11, no. 14, 1725. https://doi.org/10.3390/rs11141725","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:f5b444032220401c84cea703caa35e49","is_oa":true,"landing_page_url":"https://doaj.org/article/f5b444032220401c84cea703caa35e49","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 14, p 1725 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/14/1725/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11141725","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; Volume 11; Issue 14; Pages: 1725","raw_type":"Text"},{"id":"pmh:oai:ris.utwente.nl:publications/a4e6a109-bd30-4b2a-8765-92c4e657bbbf","is_oa":true,"landing_page_url":"https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2019/isi/percello_dee.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Xia , X , Persello , C & Koeva , M N 2019 , ' Deep Fully Convolutional Networks for Cadastral Boundary Detection from UAV Images ' , Remote sensing , vol. 11 , no. 14 , 1725 . https://doi.org/10.3390/rs11141725","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs11141725","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11141725","pdf_url":"https://www.mdpi.com/2072-4292/11/14/1725/pdf?version=1563618401","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":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G2990640502","display_name":null,"funder_award_id":"687828","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8318064016","display_name":null,"funder_award_id":"Horizon","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963998131.pdf","grobid_xml":"https://content.openalex.org/works/W2963998131.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1966811077","https://openalex.org/W1972544340","https://openalex.org/W2095028777","https://openalex.org/W2110158442","https://openalex.org/W2119823327","https://openalex.org/W2330219538","https://openalex.org/W2395611524","https://openalex.org/W2414925235","https://openalex.org/W2512695020","https://openalex.org/W2548960422","https://openalex.org/W2583659076","https://openalex.org/W2735833004","https://openalex.org/W2736449982","https://openalex.org/W2746153425","https://openalex.org/W2751311838","https://openalex.org/W2764034829","https://openalex.org/W2765226977","https://openalex.org/W2782522152","https://openalex.org/W2919115771","https://openalex.org/W2942749051","https://openalex.org/W2947614256","https://openalex.org/W2951982261","https://openalex.org/W3125542698","https://openalex.org/W6637568146","https://openalex.org/W6716241776"],"related_works":["https://openalex.org/W2361566382","https://openalex.org/W2114233742","https://openalex.org/W1562347873","https://openalex.org/W4247263692","https://openalex.org/W1899898439","https://openalex.org/W2051591117","https://openalex.org/W2212678439","https://openalex.org/W2017709107","https://openalex.org/W1963842245","https://openalex.org/W125192551"],"abstract_inverted_index":{"There":[0],"is":[1,27],"a":[2,73,175],"growing":[3],"demand":[4],"for":[5,98],"cheap":[6],"and":[7,29,58,104,121,141,147,159,190,200],"fast":[8],"cadastral":[9,33,55,99,171,179,198],"mapping":[10,34,199],"methods":[11],"to":[12,48,88,168],"face":[13],"the":[14,49,53,63,66,90,109,196],"challenge":[15],"of":[16,68,92,111,124,152,178],"70%":[17],"global":[18],"unregistered":[19],"land":[20,44],"rights.":[21],"As":[22],"traditional":[23],"on-site":[24],"field":[25,192],"surveying":[26],"time-consuming":[28],"labor":[30],"intensive,":[31],"imagery-based":[32],"has":[35],"in":[36,62,102,127,132,143,154,157,161],"recent":[37],"years":[38],"been":[39],"advocated":[40],"by":[41,83],"fit-for-purpose":[42],"(FFP)":[43],"administration.":[45],"However,":[46],"owing":[47],"semantic":[50],"gap":[51],"between":[52],"high-level":[54],"boundary":[56,70,100],"concept":[57],"low-level":[59],"visual":[60],"cues":[61],"imagery,":[64],"improving":[65],"accuracy":[67,151],"automatic":[69],"delineation":[71],"remains":[72],"major":[74],"challenge.":[75],"In":[76,163],"this":[77],"research,":[78],"we":[79],"use":[80],"imageries":[81],"acquired":[82],"Unmanned":[84],"Aerial":[85],"Vehicles":[86],"(UAV)":[87],"explore":[89],"potential":[91],"deep":[93],"Fully":[94],"Convolutional":[95],"Networks":[96],"(FCNs)":[97],"detection":[101],"urban":[103],"semi-urban":[105],"areas.":[106],"We":[107],"test":[108],"performance":[110],"FCNs":[112,138,165],"against":[113],"other":[114],"state-of-the-art":[115],"techniques,":[116],"including":[117],"Multi-Resolution":[118],"Segmentation":[119],"(MRS)":[120],"Globalized":[122],"Probability":[123],"Boundary":[125],"(gPb)":[126],"two":[128],"case":[129],"study":[130,145],"sites":[131],"Rwanda.":[133],"Experimental":[134],"results":[135],"show":[136],"that":[137],"outperformed":[139],"MRS":[140],"gPb":[142],"both":[144],"areas":[146],"achieved":[148],"an":[149],"average":[150],"0.79":[153],"precision,":[155],"0.37":[156],"recall":[158],"0.50":[160],"F-score.":[162],"conclusion,":[164],"are":[166,181],"able":[167],"effectively":[169],"extract":[170],"boundaries,":[172],"especially":[173],"when":[174],"large":[176],"proportion":[177],"boundaries":[180],"visible.":[182],"This":[183],"automated":[184],"method":[185],"could":[186],"minimize":[187],"manual":[188],"digitization":[189],"reduce":[191],"work,":[193],"thus":[194],"facilitating":[195],"current":[197],"updating":[201],"practices.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2019-07-30T00:00:00"}