{"id":"https://openalex.org/W4313185778","doi":"https://doi.org/10.1109/igarss46834.2022.9883740","title":"Deep Learning Models in Forest Mapping Using Multitemporal SAR and Optical Satellite Data","display_name":"Deep Learning Models in Forest Mapping Using Multitemporal SAR and Optical Satellite Data","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4313185778","doi":"https://doi.org/10.1109/igarss46834.2022.9883740"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883740","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078817021","display_name":"Shaojia Ge","orcid":"https://orcid.org/0000-0002-9655-1207"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaojia Ge","raw_affiliation_strings":["Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101434406","display_name":"Hong Gu","orcid":"https://orcid.org/0000-0002-8224-146X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Gu","raw_affiliation_strings":["Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101831645","display_name":"Weimin Su","orcid":"https://orcid.org/0000-0001-5752-7936"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weimin Su","raw_affiliation_strings":["Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, School of Electronic and Optical Engineering,Department of Electronic Engineering,Nanjing,China,210094","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069103777","display_name":"Jaan Praks","orcid":"https://orcid.org/0000-0001-7466-3569"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jaan Praks","raw_affiliation_strings":["Aalto University, School of Electrical Engineering,Aalto,Finland,FI-02044"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalto University, School of Electrical Engineering,Aalto,Finland,FI-02044","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075299738","display_name":"Anne L\u00f6nnqvist","orcid":null},"institutions":[{"id":"https://openalex.org/I87653560","display_name":"VTT Technical Research Centre of Finland","ror":"https://ror.org/04b181w54","country_code":"FI","type":"nonprofit","lineage":["https://openalex.org/I4210089493","https://openalex.org/I87653560"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Anne Lonnqvist","raw_affiliation_strings":["VTT Technical Research Centre of Finland,Finland,FI-02044 VTT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VTT Technical Research Centre of Finland,Finland,FI-02044 VTT","institution_ids":["https://openalex.org/I87653560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037773899","display_name":"Oleg Antropov","orcid":"https://orcid.org/0000-0001-8576-404X"},"institutions":[{"id":"https://openalex.org/I87653560","display_name":"VTT Technical Research Centre of Finland","ror":"https://ror.org/04b181w54","country_code":"FI","type":"nonprofit","lineage":["https://openalex.org/I4210089493","https://openalex.org/I87653560"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Oleg Antropov","raw_affiliation_strings":["VTT Technical Research Centre of Finland,Finland,FI-02044 VTT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"VTT Technical Research Centre of Finland,Finland,FI-02044 VTT","institution_ids":["https://openalex.org/I87653560"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"5688","last_page":"5691"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":1.0,"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":1.0,"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":0.9997000098228455,"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/T10555","display_name":"Fire effects on ecosystems","score":0.9958000183105469,"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/remote-sensing","display_name":"Remote sensing","score":0.6445047855377197},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.604823887348175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6015848517417908},{"id":"https://openalex.org/keywords/taiga","display_name":"Taiga","score":0.5302355289459229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5189461708068848},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4992563724517822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4917657673358917},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4824810326099396},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4664207398891449},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.44045940041542053},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4150261878967285},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.41152700781822205},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.2477818727493286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2220490574836731},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15111929178237915},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15053752064704895},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15016725659370422},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10002130270004272}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6445047855377197},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.604823887348175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6015848517417908},{"id":"https://openalex.org/C87621631","wikidata":"https://www.wikidata.org/wiki/Q69564","display_name":"Taiga","level":2,"score":0.5302355289459229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5189461708068848},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4992563724517822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4917657673358917},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4824810326099396},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4664207398891449},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.44045940041542053},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4150261878967285},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.41152700781822205},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.2477818727493286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2220490574836731},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15111929178237915},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15053752064704895},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15016725659370422},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10002130270004272},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883740","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G2035592251","display_name":null,"funder_award_id":"2020M681604","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8928186136","display_name":null,"funder_award_id":"61801221,62001229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W837234218","https://openalex.org/W1901129140","https://openalex.org/W1997732436","https://openalex.org/W2001470990","https://openalex.org/W2057327074","https://openalex.org/W2756157229","https://openalex.org/W2756863509","https://openalex.org/W2903542913","https://openalex.org/W2968347155","https://openalex.org/W2969890686","https://openalex.org/W3124539583","https://openalex.org/W3173833413","https://openalex.org/W3197211007","https://openalex.org/W3204157259","https://openalex.org/W6800763789"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W1924178503","https://openalex.org/W4308716060","https://openalex.org/W4280648719","https://openalex.org/W4386937079","https://openalex.org/W2901774584"],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3],"evaluate":[4],"the":[5],"potential":[6],"of":[7,28,92,97,110,119],"deep":[8,30],"learning":[9,31,40,105],"models":[10,32,81,106],"in":[11,16,51,86],"predicting":[12,87],"forest":[13,18,88],"tree":[14,89],"height":[15],"boreal":[17,58],"zone":[19],"using":[20,65],"ESA":[21],"Sentinel-1":[22],"and":[23,53,68,103,114,124],"Sentinel-2":[24],"images.":[25],"The":[26,42],"performance":[27],"studied":[29,73],"is":[33,45],"compared":[34,99],"to":[35,100],"several":[36],"popular":[37],"conventional":[38],"machine":[39,104],"approaches.":[41],"study":[43],"area":[44],"located":[46],"near":[47],"Hyytiala":[48],"forestry":[49],"station":[50],"Finland,":[52],"represents":[54],"a":[55],"conifer-dominated":[56],"mixed":[57],"forestland.":[59],"Improved":[60],"predictions":[61],"were":[62],"obtained":[63],"when":[64,121],"combined":[66],"optical":[67,123],"SAR":[69],"data":[70,126],"for":[71],"all":[72],"models.":[74],"Our":[75],"results":[76],"indicate":[77],"that":[78],"UNet":[79],"based":[80],"can":[82],"achieve":[83],"better":[84],"accuracy":[85],"heights":[90],"(RMSE":[91],"<tex":[93,111,115],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[94,112,116],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$1.90m,\\":[95],"\\mathrm{R}^{2}$</tex>":[96],"0.69),":[98],"traditional":[101],"parametric":[102],"with":[107],"RMSE":[108],"range":[109,118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$2.27-2.41m$</tex>":[113],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathrm{R}^{2}$</tex>":[117],"0.50-0.56":[120],"satellite":[122],"radar":[125],"are":[127],"combined.":[128]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
