{"id":"https://openalex.org/W4285120326","doi":"https://doi.org/10.1109/jstars.2022.3179027","title":"Generative Feature Extraction From Sentinel 1 and 2 Data for Prediction of Forest Aboveground Biomass in the Italian Alps","display_name":"Generative Feature Extraction From Sentinel 1 and 2 Data for Prediction of Forest Aboveground Biomass in the Italian Alps","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285120326","doi":"https://doi.org/10.1109/jstars.2022.3179027"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3179027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3179027","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09785720.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09785720.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086420288","display_name":"Parth Naik","orcid":"https://orcid.org/0000-0001-9399-1103"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Parth Naik","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Information Engineering and Computer Science, University of Trento, 19034 Trento, Trento, India, 38123"],"raw_orcid":"https://orcid.org/0000-0001-9399-1103","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Information Engineering and Computer Science, University of Trento, 19034 Trento, Trento, India, 38123","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055675691","display_name":"Michele Dalponte","orcid":"https://orcid.org/0000-0001-9850-8985"},"institutions":[{"id":"https://openalex.org/I103225651","display_name":"Fondazione Edmund Mach","ror":"https://ror.org/0381bab64","country_code":"IT","type":"other","lineage":["https://openalex.org/I103225651"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Michele Dalponte","raw_affiliation_strings":["Research and Innovation Center, Fondazione Edmund Mach, San Michele all'Adige, Italy","Sustainable Agro-ecosystems and Bioresources Department, Research and Innovation Centre, Fondazione E. Mach, San Michele all'Adige, Trento, Italy, 38050"],"raw_orcid":"https://orcid.org/0000-0001-9850-8985","affiliations":[{"raw_affiliation_string":"Research and Innovation Center, Fondazione Edmund Mach, San Michele all'Adige, Italy","institution_ids":["https://openalex.org/I103225651"]},{"raw_affiliation_string":"Sustainable Agro-ecosystems and Bioresources Department, Research and Innovation Centre, Fondazione E. Mach, San Michele all'Adige, Trento, Italy, 38050","institution_ids":["https://openalex.org/I103225651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Dept. of Information Engineering and Computer Science, University of Trento, Trento, Trento, Italy, I-38050"],"raw_orcid":"https://orcid.org/0000-0002-6036-459X","affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Dept. of Information Engineering and Computer Science, University of Trento, Trento, Trento, Italy, I-38050","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":1.0881,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.72597602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"15","issue":null,"first_page":"4755","last_page":"4771"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9987000226974487,"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":0.9847000241279602,"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/overfitting","display_name":"Overfitting","score":0.7474296689033508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6876606941223145},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.514665424823761},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5011041164398193},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.50065016746521},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.4695492386817932},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4584822356700897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4369317293167114},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4358797073364258},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39084362983703613},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.23933526873588562},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09779444336891174}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7474296689033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6876606941223145},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.514665424823761},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5011041164398193},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.50065016746521},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.4695492386817932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4584822356700897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4369317293167114},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4358797073364258},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39084362983703613},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.23933526873588562},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09779444336891174}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/jstars.2022.3179027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3179027","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09785720.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/400176","is_oa":true,"landing_page_url":"https://hdl.handle.net/11572/400176","pdf_url":"https://iris.unitn.it/bitstream/11572/400176/2/Generative_Feature_Extraction_From_Sentinel_1_and_2_Data_for_Prediction_of_Forest_Aboveground_Biomass_in_the_Italian_Alps.pdf","source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:openpub.fmach.it:10449/75695","is_oa":true,"landing_page_url":"http://hdl.handle.net/10449/75695","pdf_url":"https://openpub.fmach.it/bitstream/10449/75695/1/2022_JSTARS.pdf","source":{"id":"https://openalex.org/S4377196413","display_name":"CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I103225651","host_organization_name":"Fondazione Edmund Mach","host_organization_lineage":["https://openalex.org/I103225651"],"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":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:184ae11324ff40898582d51408bb9d6f","is_oa":true,"landing_page_url":"https://doaj.org/article/184ae11324ff40898582d51408bb9d6f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 4755-4771 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3179027","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3179027","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/09785720.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G3521318513","display_name":null,"funder_award_id":"INEA/CEF/ICT/A2018/1815462","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8334187609","display_name":null,"funder_award_id":"INEA/CEF/ICT/A2018/1815462","funder_id":"https://openalex.org/F4320335813","funder_display_name":"Innovation and Networks Executive Agency"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320335813","display_name":"Innovation and Networks Executive Agency","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285120326.pdf","grobid_xml":"https://content.openalex.org/works/W4285120326.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W200771331","https://openalex.org/W1498436455","https://openalex.org/W2008374411","https://openalex.org/W2050269337","https://openalex.org/W2055052573","https://openalex.org/W2060297838","https://openalex.org/W2117026615","https://openalex.org/W2118921056","https://openalex.org/W2120641882","https://openalex.org/W2122798004","https://openalex.org/W2160192633","https://openalex.org/W2172174689","https://openalex.org/W2179290474","https://openalex.org/W2254881217","https://openalex.org/W2315994349","https://openalex.org/W2484828460","https://openalex.org/W2488702363","https://openalex.org/W2503727202","https://openalex.org/W2517185326","https://openalex.org/W2548211349","https://openalex.org/W2617056706","https://openalex.org/W2625186681","https://openalex.org/W2751694392","https://openalex.org/W2756157229","https://openalex.org/W2764034829","https://openalex.org/W2775704776","https://openalex.org/W2782522152","https://openalex.org/W2789665835","https://openalex.org/W2791006446","https://openalex.org/W2800294424","https://openalex.org/W2801684017","https://openalex.org/W2883824776","https://openalex.org/W2904779670","https://openalex.org/W2909302730","https://openalex.org/W2913079708","https://openalex.org/W2940726923","https://openalex.org/W2950240247","https://openalex.org/W2950674916","https://openalex.org/W2950859539","https://openalex.org/W2950969444","https://openalex.org/W2959046283","https://openalex.org/W2963010714","https://openalex.org/W2963695810","https://openalex.org/W2963749793","https://openalex.org/W2964218010","https://openalex.org/W2969739369","https://openalex.org/W2973184731","https://openalex.org/W2974510043","https://openalex.org/W2981537605","https://openalex.org/W2990923659","https://openalex.org/W3011821767","https://openalex.org/W3035803741","https://openalex.org/W3041608560","https://openalex.org/W3081051646","https://openalex.org/W3087122056","https://openalex.org/W3089333173","https://openalex.org/W3097169367","https://openalex.org/W3104341624","https://openalex.org/W3107126542","https://openalex.org/W3109802736","https://openalex.org/W3112661396","https://openalex.org/W3127284993","https://openalex.org/W3131337884","https://openalex.org/W3136435360","https://openalex.org/W3140411515","https://openalex.org/W3153168759","https://openalex.org/W3153743275","https://openalex.org/W3205462867","https://openalex.org/W3207667596","https://openalex.org/W3214587837","https://openalex.org/W4205617034","https://openalex.org/W4210994734","https://openalex.org/W4213420789","https://openalex.org/W6734641875","https://openalex.org/W6735132182","https://openalex.org/W6754249846","https://openalex.org/W6764340487","https://openalex.org/W6784391721"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W3015304056","https://openalex.org/W3042518613"],"abstract_inverted_index":{"Aboveground":[0],"biomass":[1],"(AGB)":[2],"is":[3],"an":[4,56],"important":[5],"forest":[6,12,74,87],"attribute":[7],"directly":[8],"linked":[9],"to":[10,29,42,47,85,94,139],"the":[11,95,103,140,156,164,169,177,185,190],"carbon":[13],"pool.":[14],"The":[15,100,123,148],"use":[16],"of":[17,102,131,155,163,199],"satellite":[18,77,203],"remote":[19],"sensing":[20],"(RS)":[21],"data":[22,205],"has":[23],"increased":[24],"for":[25,72,144,196,206],"AGB":[26,75],"prediction":[27,49],"due":[28,41],"their":[30],"large":[31],"footprint":[32],"and":[33,58,89,98,118,135],"low-cost":[34],"availability.":[35],"However,":[36],"they":[37],"have":[38],"been":[39],"limited":[40],"saturation":[43],"effect":[44],"that":[45,66,176],"leads":[46],"low":[48],"precision.":[50],"In":[51],"this":[52],"study,":[53],"we":[54],"propose":[55],"innovative":[57],"dynamic":[59],"architecture":[60],"based":[61],"on":[62],"generative":[63,70,157,179],"neural":[64],"network":[65],"extracts":[67],"target":[68,170],"oriented":[69],"features":[71,81,97,105,158,180,201],"predicting":[73,207],"using":[76,111],"RS":[78,204],"data.":[79],"These":[80],"are":[82],"more":[83,182],"resilient":[84],"mixed":[86],"types":[88],"geographical":[90],"conditions":[91],"as":[92,137],"compared":[93,138],"traditional":[96],"models.":[99],"effectiveness":[101],"proposed":[104,124],"was":[106],"assessed":[107],"by":[108],"experiments":[109],"performed":[110],"multispectral":[112],"(MS),":[113],"Synthetic":[114],"aperture":[115],"Radar":[116],"(SAR)":[117],"combined":[119],"dual-source":[120],"(DS)":[121],"datasets.":[122,147],"model":[125,133,191],"achieved":[126],"best":[127],"performance":[128],"in":[129],"terms":[130],"precision,":[132],"agreement":[134],"overfitting":[136],"other":[141],"conventional":[142,186],"models":[143],"all":[145],"analyzed":[146],"t-distributed":[149],"stochastic":[150],"neighbor":[151],"embedding":[152],"(t-SNE)":[153],"scatterplots":[154],"clearly":[159],"show":[160],"one":[161],"dimension":[162],"feature":[165],"space":[166],"associated":[167],"with":[168],"AGB.":[171,208],"Feature":[172],"importance":[173],"analysis":[174],"indicated":[175],"produced":[178],"were":[181],"significant":[183],"than":[184],"analytical":[187],"features.":[188],"Also,":[189],"provided":[192],"a":[193],"robust":[194],"framework":[195],"homogeneous":[197],"fusion":[198],"multi-sensor":[200],"from":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}