{"id":"https://openalex.org/W4285207472","doi":"https://doi.org/10.1109/tgrs.2022.3177935","title":"Spectral\u2013Spatial and Cascaded Multilayer Random Forests for Tree Species Classification in Airborne Hyperspectral Images","display_name":"Spectral\u2013Spatial and Cascaded Multilayer Random Forests for Tree Species Classification in Airborne Hyperspectral Images","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285207472","doi":"https://doi.org/10.1109/tgrs.2022.3177935"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3177935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3177935","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5077048862","display_name":"Fei Tong","orcid":"https://orcid.org/0000-0001-6056-9299"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fei Tong","raw_affiliation_strings":["Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB, Canada","Department of Geodesy and Geomatics Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada"],"raw_orcid":"https://orcid.org/0000-0001-6056-9299","affiliations":[{"raw_affiliation_string":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB, Canada","institution_ids":["https://openalex.org/I106938459"]},{"raw_affiliation_string":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100356784","display_name":"Yun Zhang","orcid":"https://orcid.org/0000-0001-9231-0142"},"institutions":[{"id":"https://openalex.org/I106938459","display_name":"University of New Brunswick","ror":"https://ror.org/05nkf0n29","country_code":"CA","type":"education","lineage":["https://openalex.org/I106938459"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yun Zhang","raw_affiliation_strings":["Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB, Canada","Department of Geodesy and Geomatics Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada"],"raw_orcid":"https://orcid.org/0000-0001-9231-0142","affiliations":[{"raw_affiliation_string":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB, Canada","institution_ids":["https://openalex.org/I106938459"]},{"raw_affiliation_string":"Department of Geodesy and Geomatics Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada","institution_ids":["https://openalex.org/I106938459"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I106938459"],"apc_list":null,"apc_paid":null,"fwci":4.9736,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95895421,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9987999796867371,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9407683610916138},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6951640844345093},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6476739645004272},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6372635960578918},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.636645495891571},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.607639491558075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5417786836624146},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.5417410135269165},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5381131768226624},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5112688541412354},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.48635798692703247},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4506908655166626},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42118096351623535},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20439836382865906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1993098258972168},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13809508085250854}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9407683610916138},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6951640844345093},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6476739645004272},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6372635960578918},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.636645495891571},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.607639491558075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5417786836624146},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.5417410135269165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5381131768226624},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5112688541412354},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.48635798692703247},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4506908655166626},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42118096351623535},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20439836382865906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1993098258972168},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13809508085250854},{"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/tgrs.2022.3177935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3177935","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.7599999904632568,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G3476830129","display_name":null,"funder_award_id":"19FANBA36","funder_id":"https://openalex.org/F4320334436","funder_display_name":"Canadian Space Agency"}],"funders":[{"id":"https://openalex.org/F4320334436","display_name":"Canadian Space Agency","ror":"https://ror.org/03a1gte98"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1950365613","https://openalex.org/W2001298023","https://openalex.org/W2004104348","https://openalex.org/W2056132907","https://openalex.org/W2059110141","https://openalex.org/W2085529604","https://openalex.org/W2097915756","https://openalex.org/W2101711129","https://openalex.org/W2103094532","https://openalex.org/W2135431554","https://openalex.org/W2136251662","https://openalex.org/W2159070926","https://openalex.org/W2162698522","https://openalex.org/W2164437025","https://openalex.org/W2166923144","https://openalex.org/W2405365025","https://openalex.org/W2500751094","https://openalex.org/W2515306179","https://openalex.org/W2572303978","https://openalex.org/W2585293115","https://openalex.org/W2604870469","https://openalex.org/W2745791577","https://openalex.org/W2808098982","https://openalex.org/W2808776742","https://openalex.org/W2902193101","https://openalex.org/W2919115771","https://openalex.org/W2962770389","https://openalex.org/W2987475181","https://openalex.org/W2994639710","https://openalex.org/W3005383134","https://openalex.org/W3036016333","https://openalex.org/W3098388691","https://openalex.org/W3105298104","https://openalex.org/W3105357426","https://openalex.org/W3151633797","https://openalex.org/W3200742127","https://openalex.org/W4232714830","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W2800956885","https://openalex.org/W2533019003","https://openalex.org/W2626158795","https://openalex.org/W2057283258","https://openalex.org/W1788560349","https://openalex.org/W2901421464","https://openalex.org/W2324845311","https://openalex.org/W2391021239"],"abstract_inverted_index":{"The":[0,79],"rapid":[1],"development":[2],"of":[3,100,109,120,128,141,149,167,190],"remote":[4],"sensing":[5],"sensors":[6],"has":[7],"made":[8],"it":[9,36],"possible":[10],"to":[11,28,40,68,85],"collect":[12],"airborne":[13,137],"hyperspectral":[14,77,138],"data":[15,23,139],"with":[16,135,145,153],"high":[17,74],"spectral":[18,45,115],"and":[19,47,59,94,113,193],"spatial":[20,49,75,89,101,147],"resolution.":[21],"Such":[22],"can":[24],"provide":[25],"valuable":[26],"information":[27,46,50,90,102],"identify":[29],"tree":[30,70],"species":[31,71],"in":[32,72,188],"the":[33,43,52,73,88,107,110,114,118,121,126,129,146,160,174,179,197],"forest.":[34],"However,":[35],"is":[37,66],"a":[38,57,142,164],"challenge":[39],"efficiently":[41],"utilize":[42],"abundant":[44],"complex":[48],"within":[51,91,169],"data.":[53],"In":[54,172],"this":[55],"article,":[56],"Spectral-Spatial":[58],"Cascaded":[60],"Multilayer":[61],"Random":[62],"Forests":[63],"(SSCMRF)":[64],"method":[65],"proposed":[67,130,161,180],"classify":[69],"resolution":[76,148],"image.":[78],"SSCMRF":[80,162,181],"adopts":[81],"two":[82],"classification":[83,112,165,186,198],"stages":[84],"fully":[86],"exploit":[87],"shape-adaptive":[92],"superpixels":[93],"shape-fixed":[95],"patches.":[96],"Two":[97],"different":[98],"kinds":[99],"are":[103,133],"integrated":[104],"by":[105],"concatenating":[106],"output":[108],"superpixel-based":[111],"features":[116],"as":[117],"input":[119],"patch-based":[122],"classification.":[123],"To":[124],"demonstrate":[125,177],"superiority":[127],"SSCMRF,":[131],"experiments":[132],"conducted":[134],"an":[136],"set":[140],"forest":[143],"area":[144],"1":[150],"m.":[151],"Training":[152],"2.5%":[154],"randomly":[155],"selected":[156],"ground":[157],"truth":[158],"samples,":[159],"achieves":[163],"accuracy":[166],"97.50%":[168],"6":[170],"minutes.":[171],"addition,":[173],"experiment":[175],"results":[176],"that":[178],"outperforms":[182],"some":[183],"state-of-art":[184],"spectral-spatial":[185],"models":[187],"terms":[189],"quantitative":[191],"metrics":[192],"visual":[194],"quality":[195],"on":[196],"map.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
