{"id":"https://openalex.org/W2898901454","doi":"https://doi.org/10.1109/igarss.2018.8517333","title":"Fusion of Lidar, Hyperspectral and RGB Data for Urban Land Use and Land Cover Classification","display_name":"Fusion of Lidar, Hyperspectral and RGB Data for Urban Land Use and Land Cover Classification","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2898901454","doi":"https://doi.org/10.1109/igarss.2018.8517333","mag":"2898901454"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517333","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5004452945","display_name":"Sergey Sukhanov","orcid":"https://orcid.org/0000-0003-3173-4616"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergey Sukhanov","raw_affiliation_strings":["AGT International, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGT International, Darmstadt, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070613017","display_name":"Dmitrii Budylskii","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dmitrii Budylskii","raw_affiliation_strings":["AGT International, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGT International, Darmstadt, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072141116","display_name":"Ivan Tankoyeu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ivan Tankoyeu","raw_affiliation_strings":["AGT International, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGT International, Darmstadt, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059519968","display_name":"Roel Heremans","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roel Heremans","raw_affiliation_strings":["AGT International, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGT International, Darmstadt, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023275599","display_name":"Christian Debes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christian Debes","raw_affiliation_strings":["AGT International, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGT International, Darmstadt, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9406,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.73734781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3864","last_page":"3867"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9957000017166138,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8242145776748657},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7406879663467407},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6689951419830322},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6382231116294861},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.6031694412231445},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5252520442008972},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5060727000236511},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.44204768538475037},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42450425028800964},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4220081567764282},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3975370526313782},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3529358506202698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26477307081222534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10166352987289429},{"id":"https://openalex.org/keywords/civil-engineering","display_name":"Civil engineering","score":0.05597895383834839}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8242145776748657},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7406879663467407},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6689951419830322},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6382231116294861},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.6031694412231445},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5252520442008972},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5060727000236511},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.44204768538475037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42450425028800964},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4220081567764282},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3975370526313782},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3529358506202698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26477307081222534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10166352987289429},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.05597895383834839},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517333","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517333","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309549","display_name":"University of Houston","ror":"https://ror.org/040vwpm13"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1105031944","https://openalex.org/W1678356000","https://openalex.org/W1836465849","https://openalex.org/W1965309615","https://openalex.org/W2095705004","https://openalex.org/W2103164346","https://openalex.org/W2531409750","https://openalex.org/W2606520626","https://openalex.org/W2773261480","https://openalex.org/W2798886737","https://openalex.org/W6638667902","https://openalex.org/W6674330103"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2072166414","https://openalex.org/W2956374172","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W4281783339","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"an":[5],"ensemble-based":[6],"classification":[7,16],"approach":[8,29],"for":[9,38],"urban":[10],"land":[11,14],"use":[12],"and":[13,22,53,71,79],"cover":[15],"based":[17],"on":[18,33],"multispectral":[19],"LiDAR,":[20],"hyperspectral":[21],"very":[23],"high":[24,60],"resolution":[25],"RGB":[26],"data.":[27],"The":[28],"has":[30,54],"been":[31,55],"evaluated":[32],"the":[34,39,48],"data":[35],"set":[36],"provided":[37],"IEEE":[40],"GRSS":[41,49],"2018":[42],"Data":[43],"Fusion":[44],"Contest":[45],"organized":[46],"by":[47],"IADF":[50],"technical":[51],"committee":[52],"proven":[56],"to":[57,65],"have":[58],"a":[59],"operational":[61],"performance,":[62],"being":[63],"able":[64],"distinguish":[66],"between":[67],"different":[68],"grass-,":[69],"building-":[70],"street-types":[72],"among":[73],"other":[74,85],"classes":[75,87],"like":[76,88],"water,":[77],"railways":[78],"parking":[80],"lots":[81],"as":[82,84],"well":[83],"non-typical":[86],"cars,":[89],"trains,":[90],"stadium":[91],"seats,":[92],"etc.":[93]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
