{"id":"https://openalex.org/W4387801985","doi":"https://doi.org/10.1109/igarss52108.2023.10282639","title":"Forest Height Estimation Using Multi-Frequency Sar and a Stacking Regression","display_name":"Forest Height Estimation Using Multi-Frequency Sar and a Stacking Regression","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387801985","doi":"https://doi.org/10.1109/igarss52108.2023.10282639"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10282639","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 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/A5085251040","display_name":"Jo\u00e3o E. Pereira-Pires","orcid":"https://orcid.org/0000-0003-2957-6372"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]},{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["GB","PT"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o E. Pereira-Pires","raw_affiliation_strings":["NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516","Surrey Space Centre, University of Surrey, Guildford, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I83558840"]},{"raw_affiliation_string":"Surrey Space Centre, University of Surrey, Guildford, UK","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028471241","display_name":"Jo\u00e3o M. N. Silva","orcid":"https://orcid.org/0000-0001-5201-9836"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jo\u00e3o M. N. Silva","raw_affiliation_strings":["University of Lisbon,Forest Research Centre and Associate Laboratory TERRA, School of Agriculture,Lisbon,Portugal,1349-017"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Lisbon,Forest Research Centre and Associate Laboratory TERRA, School of Agriculture,Lisbon,Portugal,1349-017","institution_ids":["https://openalex.org/I141596103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010179430","display_name":"Jos\u00e9 Fonseca","orcid":"https://orcid.org/0000-0001-7173-7374"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 M. Fonseca","raw_affiliation_strings":["NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I83558840"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051554638","display_name":"Andr\u00e9 Mora","orcid":"https://orcid.org/0000-0003-1354-4739"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I83558840","display_name":"Universidade Nova de Lisboa","ror":"https://ror.org/02xankh89","country_code":"PT","type":"education","lineage":["https://openalex.org/I83558840"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Andr\u00e9 Mora","raw_affiliation_strings":["NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NOVA University of Lisbon,Centre of Technology and Systems/UNINOVA, School of Science and Technology,Caparica,Portugal,2829-516","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I83558840"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072917995","display_name":"Raffaella Guida","orcid":"https://orcid.org/0000-0002-9041-4244"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Raffaella Guida","raw_affiliation_strings":["University of Surrey,Surrey Space Centre,Guildford,UK,GU2 7XH"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey,Surrey Space Centre,Guildford,UK,GU2 7XH","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2483,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77220406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"1353","last_page":"1356"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10535","display_name":"Landslides and related hazards","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9969000220298767,"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.7963473796844482},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.628291130065918},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.570315420627594},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5617093443870544},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.5353942513465881},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5245285630226135},{"id":"https://openalex.org/keywords/interferometric-synthetic-aperture-radar","display_name":"Interferometric synthetic aperture radar","score":0.5183766484260559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5115207433700562},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.447884738445282},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.42503225803375244},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.42397361993789673},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.41091302037239075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27670449018478394},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21816059947013855},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18987923860549927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18687114119529724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17387741804122925},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.0893695056438446}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.7963473796844482},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.628291130065918},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.570315420627594},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5617093443870544},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.5353942513465881},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5245285630226135},{"id":"https://openalex.org/C22286887","wikidata":"https://www.wikidata.org/wiki/Q1666056","display_name":"Interferometric synthetic aperture radar","level":3,"score":0.5183766484260559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5115207433700562},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.447884738445282},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.42503225803375244},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.42397361993789673},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.41091302037239075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27670449018478394},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21816059947013855},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18987923860549927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18687114119529724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17387741804122925},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0893695056438446},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10282639","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10282639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321979","display_name":"University of Surrey","ror":"https://ror.org/00ks66431"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2807472028","https://openalex.org/W2972457889","https://openalex.org/W2980591256","https://openalex.org/W2999320693","https://openalex.org/W3108705003","https://openalex.org/W3117603577","https://openalex.org/W3132992476","https://openalex.org/W3133225133","https://openalex.org/W3156622514","https://openalex.org/W3176152844","https://openalex.org/W3198237269","https://openalex.org/W3210146873","https://openalex.org/W6767720669","https://openalex.org/W6791612052","https://openalex.org/W6794141760"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W4376641153","https://openalex.org/W2070875936","https://openalex.org/W4250391473","https://openalex.org/W3045075405","https://openalex.org/W4302292679","https://openalex.org/W4241625287","https://openalex.org/W2050788868","https://openalex.org/W3206958763","https://openalex.org/W2159160885"],"abstract_inverted_index":{"The":[0,44],"knowledge":[1],"of":[2,22,84,100,111,118,127],"the":[3,11,27,36,41,50,82,109,116,138],"Forest":[4],"Height":[5],"(FH)":[6],"is":[7,31,52,121],"important":[8,33],"for":[9,34],"monitoring":[10],"forests,":[12],"and":[13,39,64,103,132,144],"it":[14,78],"can":[15],"be":[16,75],"used":[17],"as":[18,26],"a":[19,92,104,119,125,141,145],"proxy":[20],"variable":[21],"other":[23],"forest":[24],"parameters":[25],"aboveground":[28],"biomass.":[29],"It":[30],"also":[32],"understanding":[35],"climate":[37],"change":[38],"prepare":[40],"wildfire":[42],"seasons.":[43],"most":[45],"effective":[46],"way":[47],"to":[48,114],"map":[49,115],"FH":[51,117],"through":[53],"field":[54],"campaigns":[55],"or":[56],"airborne":[57],"laser":[58],"scanning,":[59],"but":[60],"both":[61],"are":[62],"expensive":[63],"not":[65],"scalable.":[66],"Alternatively,":[67],"spaceborne":[68],"Synthetic":[69],"Aperture":[70],"Radar":[71],"(SAR)":[72],"data":[73,102,112],"may":[74],"used.":[76],"However,":[77],"often":[79],"relies":[80],"on":[81,124],"acquisition":[83],"large":[85],"ground":[86],"truth":[87],"datasets.":[88],"In":[89],"this":[90],"paper,":[91],"new":[93],"Regression":[94],"Methodology":[95],"(RM)":[96],"that":[97,107],"makes":[98],"use":[99],"SAR":[101],"Stacking":[105],"Regressor":[106],"minimises":[108],"amount":[110],"needed":[113],"region":[120],"presented.":[122],"Tested":[123],"total":[126],"16":[128],"regions":[129],"between":[130,147],"Portugal":[131],"Spain,":[133],"plus":[134],"one":[135],"in":[136],"California,":[137],"RM":[139],"achieved":[140],"R2between":[142],"42.12%-62.62%,":[143],"RMSE":[146],"0.96m-4.49m.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}