{"id":"https://openalex.org/W2988950246","doi":"https://doi.org/10.1109/igarss.2019.8898021","title":"Online Random Forests For Large-Scale Land-Use Classification From Polarimetric Sar Images","display_name":"Online Random Forests For Large-Scale Land-Use Classification From Polarimetric Sar Images","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2988950246","doi":"https://doi.org/10.1109/igarss.2019.8898021","mag":"2988950246"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8898021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 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/A5025073736","display_name":"Ronny H\u00e4nsch","orcid":"https://orcid.org/0000-0002-2936-6765"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ronny Hansch","raw_affiliation_strings":["Computer Vision & Remote Sensing, Technische Universit\u00e4t, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision & Remote Sensing, Technische Universit\u00e4t, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081055268","display_name":"Olaf Hellwich","orcid":"https://orcid.org/0000-0002-2871-9266"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Olaf Hellwich","raw_affiliation_strings":["Computer Vision & Remote Sensing, Technische Universit\u00e4t, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision & Remote Sensing, Technische Universit\u00e4t, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1812,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58179959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"20","issue":null,"first_page":"5808","last_page":"5811"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9954000115394592,"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":0.9954000115394592,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9911999702453613,"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"}},{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9775999784469604,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7718570828437805},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7359700202941895},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5510467290878296},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5502601861953735},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4865633547306061},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4801751673221588},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47754037380218506},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4726235866546631},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4693891406059265},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4491158723831177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42349690198898315},{"id":"https://openalex.org/keywords/data-processing","display_name":"Data processing","score":0.41282832622528076},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3967520594596863},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33746451139450073},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20946809649467468},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.18327122926712036},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08935734629631042},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07263913750648499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718570828437805},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7359700202941895},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5510467290878296},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5502601861953735},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4865633547306061},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4801751673221588},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47754037380218506},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4726235866546631},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4693891406059265},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4491158723831177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42349690198898315},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.41282832622528076},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3967520594596863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33746451139450073},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20946809649467468},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.18327122926712036},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08935734629631042},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07263913750648499},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2019.8898021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8898021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:131039","is_oa":false,"landing_page_url":"https://elib.dlr.de/131039/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W137456267","https://openalex.org/W1019189097","https://openalex.org/W1485877476","https://openalex.org/W1529840045","https://openalex.org/W1992047056","https://openalex.org/W2012786385","https://openalex.org/W2113242816","https://openalex.org/W2162152641","https://openalex.org/W2772082715","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4297664336"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372","https://openalex.org/W3022067003"],"abstract_inverted_index":{"The":[0,66,120],"deployment":[1],"of":[2,21,41,63,76,88,122,132],"numerous":[3],"air-":[4],"and":[5],"space-borne":[6],"remote":[7],"sensing":[8],"sensors":[9],"as":[10,12,27,50],"well":[11],"new":[13],"data":[14,43,59,79,114],"policies":[15],"led":[16],"to":[17,84,112],"a":[18,73,77],"tremendous":[19],"increase":[20],"available":[22],"data.":[23],"While":[24],"methods":[25,48],"such":[26,49],"neural":[28],"networks":[29],"are":[30,68,126],"trained":[31,71,104],"by":[32,105],"online":[33],"or":[34],"batch":[35,106],"processing,":[36,55],"i.e.":[37,56],"keeping":[38,57],"only":[39],"parts":[40],"the":[42,45,61,64,90,129],"in":[44,60,93],"memory,":[46],"other":[47],"Random":[51,100],"Forests":[52,101],"require":[53],"offline":[54],"all":[58,94],"memory":[62],"computer.":[65],"latter":[67],"therefore":[69],"often":[70],"on":[72],"small":[74],"subset":[75],"larger":[78],"set":[80],"that":[81,99],"is":[82],"hoped":[83],"be":[85,103],"representative":[86],"instead":[87],"exploiting":[89],"information":[91],"contained":[92],"samples.":[95],"This":[96],"paper":[97],"shows":[98],"can":[102],"processing":[107],"too":[108],"making":[109],"their":[110],"application":[111],"large":[113],"sets":[115],"feasible":[116],"without":[117],"further":[118],"constraints.":[119],"benefits":[121],"this":[123],"training":[124],"scheme":[125],"illustrated":[127],"for":[128],"use":[130],"case":[131],"land-use":[133],"classification":[134],"from":[135],"PolSAR":[136],"imagery.":[137]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}