{"id":"https://openalex.org/W4304775464","doi":"https://doi.org/10.3390/rs14205088","title":"Tree Species Classification Based on Fusion Images by GF-5 and Sentinel-2A","display_name":"Tree Species Classification Based on Fusion Images by GF-5 and Sentinel-2A","publication_year":2022,"publication_date":"2022-10-12","ids":{"openalex":"https://openalex.org/W4304775464","doi":"https://doi.org/10.3390/rs14205088"},"language":"en","primary_location":{"id":"doi:10.3390/rs14205088","doi":"https://doi.org/10.3390/rs14205088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205088","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5088/pdf?version=1665569398","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/14/20/5088/pdf?version=1665569398","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088150785","display_name":"Weihua Chen","orcid":"https://orcid.org/0000-0002-1400-5721","observed_orcids":["https://orcid.org/0000-0002-1400-5721"]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Chen","raw_affiliation_strings":["Forest Resources and Environment Faculty, Nanjing Forestry University, Nanjing 210037, China"],"raw_orcid":"https://orcid.org/0000-0002-1400-5721","affiliations":[{"raw_affiliation_string":"Forest Resources and Environment Faculty, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101794894","display_name":"Jie Pan","orcid":"https://orcid.org/0000-0003-2056-4113","observed_orcids":["https://orcid.org/0000-0003-2056-4113"]},"institutions":[{"id":"https://openalex.org/I167027274","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165","country_code":"CN","type":"education","lineage":["https://openalex.org/I167027274"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Pan","raw_affiliation_strings":["Forest Resources and Environment Faculty, Nanjing Forestry University, Nanjing 210037, China"],"raw_orcid":"https://orcid.org/0000-0003-2056-4113","affiliations":[{"raw_affiliation_string":"Forest Resources and Environment Faculty, Nanjing Forestry University, Nanjing 210037, China","institution_ids":["https://openalex.org/I167027274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113299886","display_name":"Yulin Sun","orcid":"https://orcid.org/0000-0003-0749-5221","observed_orcids":["https://orcid.org/0000-0003-0749-5221","https://orcid.org/0000-0001-5821-0535"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yulin Sun","raw_affiliation_strings":["Wuxi Spectrum Vision Technology Co., Ltd., Wuxi 214028, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuxi Spectrum Vision Technology Co., Ltd., Wuxi 214028, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101794894"],"corresponding_institution_ids":["https://openalex.org/I167027274"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2618},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2618},"fwci":0.4854,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.5556757,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"14","issue":"20","first_page":"5088","last_page":"5088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.7836999893188477,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.7836999893188477,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.17759999632835388,"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":0.016300000250339508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/tree-species-classification","display_name":"tree species classification","score":0.9990000128746033},{"id":"https://openalex.org/keywords/image-fusion","display_name":"image fusion","score":0.8040000200271606},{"id":"https://openalex.org/keywords/gf-5","display_name":"GF-5","score":0.8610000014305115},{"id":"https://openalex.org/keywords/sentinel-2a","display_name":"Sentinel-2A","score":0.9940000176429749},{"id":"https://openalex.org/keywords/hyperspectral-imagery","display_name":"hyperspectral imagery","score":0.8299999833106995},{"id":"https://openalex.org/keywords/random-forest-feature-selection","display_name":"random forest feature selection","score":0.7490000128746033},{"id":"https://openalex.org/keywords/spectral-and-textural-features","display_name":"spectral and textural features","score":0.8610000014305115},{"id":"https://openalex.org/keywords/topographic-features","display_name":"topographic features","score":0.875}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7798417806625366},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6183896064758301},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6128548979759216},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.45868420600891113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4577937722206116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44918593764305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4164403975009918},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.4112307131290436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31429386138916016},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18495535850524902},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17252594232559204},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs14205088","doi":"https://doi.org/10.3390/rs14205088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205088","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5088/pdf?version=1665569398","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2a7cb55335f844e593e22140a035110e","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/2a7cb55335f844e593e22140a035110e","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,"listed_in":[],"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":"Remote Sensing, Vol 14, Iss 20, p 5088 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs14205088","doi":"https://doi.org/10.3390/rs14205088","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14205088","pdf_url":"https://www.mdpi.com/2072-4292/14/20/5088/pdf?version=1665569398","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life on land","score":0.7605999708175659,"id":"https://metadata.un.org/sdg/15"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1096466914","display_name":null,"funder_award_id":"11KJB220001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G459077913","display_name":null,"funder_award_id":"LYKJ [2021]14","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6944626170","display_name":"\u57fa\u4e8e\u8fd1\u5730\u9762\u9ad8\u5149\u8c31\u5f71\u50cf\u7279\u5f81\u4e0e\u7269\u8054\u7f51\u67b6\u6784\u7684\u677e\u6750\u7ebf\u866b\u75c5\u65e9\u671f\u667a\u80fd\u76d1\u6d4b\u7814\u7a76","funder_award_id":"31470579","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7040241351","display_name":null,"funder_award_id":"163010049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7708113347","display_name":null,"funder_award_id":"163010049","funder_id":"https://openalex.org/F4320312290","funder_display_name":"Nanjing Forestry University"}],"funders":[{"id":"https://openalex.org/F4320312290","display_name":"Nanjing Forestry University","ror":"https://ror.org/03m96p165"},{"id":"https://openalex.org/F4320318240","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4304775464.pdf","grobid_xml":"https://content.openalex.org/works/W4304775464.grobid-xml"},"referenced_works_count":71,"referenced_works":["https://openalex.org/W1894641570","https://openalex.org/W1967621805","https://openalex.org/W1967789481","https://openalex.org/W1979210946","https://openalex.org/W1990901078","https://openalex.org/W1996031526","https://openalex.org/W1996041299","https://openalex.org/W1996061706","https://openalex.org/W2013597166","https://openalex.org/W2020326148","https://openalex.org/W2021384698","https://openalex.org/W2022792380","https://openalex.org/W2057641906","https://openalex.org/W2059432853","https://openalex.org/W2060042860","https://openalex.org/W2065191898","https://openalex.org/W2076088305","https://openalex.org/W2081543911","https://openalex.org/W2090624115","https://openalex.org/W2109191549","https://openalex.org/W2119412805","https://openalex.org/W2134844255","https://openalex.org/W2151978020","https://openalex.org/W2156854396","https://openalex.org/W2160566385","https://openalex.org/W2164720626","https://openalex.org/W2206762869","https://openalex.org/W2261059368","https://openalex.org/W2332208325","https://openalex.org/W2411469696","https://openalex.org/W2515306179","https://openalex.org/W2544506565","https://openalex.org/W2548196722","https://openalex.org/W2556502614","https://openalex.org/W2615436872","https://openalex.org/W2767216801","https://openalex.org/W2799954862","https://openalex.org/W2806865914","https://openalex.org/W2808092904","https://openalex.org/W2891711602","https://openalex.org/W2898152330","https://openalex.org/W2909977981","https://openalex.org/W2910829991","https://openalex.org/W2921108718","https://openalex.org/W2921401402","https://openalex.org/W2921445307","https://openalex.org/W2945897702","https://openalex.org/W2949679648","https://openalex.org/W2974254117","https://openalex.org/W2979849666","https://openalex.org/W2995818283","https://openalex.org/W3004403641","https://openalex.org/W3005698624","https://openalex.org/W3007365842","https://openalex.org/W3010650493","https://openalex.org/W3011052870","https://openalex.org/W3038203156","https://openalex.org/W3081363466","https://openalex.org/W3088522164","https://openalex.org/W3097971370","https://openalex.org/W3128398964","https://openalex.org/W3130936732","https://openalex.org/W3132506628","https://openalex.org/W3174389373","https://openalex.org/W3185840992","https://openalex.org/W3186328757","https://openalex.org/W4200523756","https://openalex.org/W6648133709","https://openalex.org/W6653942448","https://openalex.org/W6668114399","https://openalex.org/W6782329917"],"related_works":["https://openalex.org/W4200101275","https://openalex.org/W4383820150","https://openalex.org/W2117432835","https://openalex.org/W3118328374","https://openalex.org/W1968590658","https://openalex.org/W2767216801","https://openalex.org/W3005769536","https://openalex.org/W3185270142","https://openalex.org/W4313640472","https://openalex.org/W4417440128"],"abstract_inverted_index":{"Forest":[0,103],"ecosystem":[1],"detection":[2],"and":[3,30,79,98,119,126,144,149,175,196,222,255,282],"assessment":[4],"usually":[5],"requires":[6],"accurate":[7],"spatial":[8,62,194],"distribution":[9],"information":[10,111,171],"of":[11,37,69,83,95,122,178,193,225,237,257,278,280,296],"forest":[12,110,137,154,201],"tree":[13,27,46,70,158,215,286],"species.":[14],"Remote":[15],"sensing":[16],"technology":[17],"has":[18,55],"been":[19],"confirmed":[20],"as":[21,170],"the":[22,35,50,66,81,84,101,113,117,123,152,179,182,219,226,258,276],"most":[23],"important":[24,213],"method":[25,91,260],"for":[26,45,92,214,250,285,294],"species":[28,47,71,159,216,287],"acquisition,":[29],"space-borne":[31],"hyperspectral":[32,53,298],"imagery,":[33],"with":[34],"advantages":[36],"high":[38],"spectral":[39,118,197],"resolution,":[40],"provides":[41,291],"a":[42,190],"better":[43],"possibility":[44],"classification.":[48,72,160,217],"However,":[49],"present":[51],"in-orbit":[52,297],"imager":[54],"proved":[56],"to":[57,64,108,135,156,188,235,248],"be":[58],"too":[59],"low":[60],"in":[61],"resolution":[63],"meet":[65],"accuracy":[67,221,244,256],"needs":[68],"In":[73],"this":[74],"study,":[75],"we":[76],"firstly":[77],"explored":[78],"evaluated":[80],"effectiveness":[82],"Gram-Schmidt":[85],"(GS)":[86],"Harmonic":[87],"analysis":[88],"fusion":[89,94,184,279],"(HAF)":[90],"image":[93,185],"GaoFen-5":[96],"(GF-5)":[97],"Sentinel-2A.":[99],"Then,":[100],"Integrated":[102],"Z-Score":[104],"(IFZ)":[105],"was":[106,186],"used":[107],"extract":[109],"from":[112,130,246],"fused":[114,124,180,227],"image.":[115],"Next,":[116],"textural":[120],"features":[121,128],"image,":[125],"topographic":[127],"extracted":[129],"DEM":[131],"were":[132,211,229],"selected":[133,259],"according":[134],"random":[136,153,200],"importance":[138,202],"ranking":[139,203],"(Mean":[140],"Decreasing":[141,146],"Gini":[142],"(MDG)":[143],"Mean":[145],"Accuracy":[147],"(MDA)),":[148],"imported":[150],"into":[151],"classifier":[155],"complete":[157],"The":[161,199,241],"results":[162,266],"showed":[163,204],"that:":[164],"comparing":[165],"some":[166],"evaluation":[167],"factors":[168],"such":[169],"entropy,":[172],"average":[173],"gradient":[174],"standard":[176],"deviation":[177],"images,":[181],"GS":[183],"proven":[187],"have":[189],"higher":[191,265],"degree":[192],"integration":[195],"fidelity.":[198],"that":[205],"WBI,":[206],"Aspect,":[207],"NDNI,":[208],"ARI2,":[209],"FRI":[210],"more":[212],"Both":[218],"classification":[220,243],"kappa":[223],"coefficients":[224],"images":[228,284],"significantly":[230],"greatly":[231],"improved":[232],"when":[233],"compared":[234],"those":[236],"original":[238],"GF-5":[239,281],"images.":[240,299],"overall":[242],"ranged":[245],"61.17%":[247],"86.93%":[249],"different":[251],"feature":[252],"combination":[253],"scenarios,":[254],"based":[261],"on":[262],"MDA":[263],"achieved":[264],"(OA":[267],"=":[268,271],"86.93%,":[269],"Kappa":[270],"0.85).":[272],"This":[273],"study":[274],"demonstrated":[275],"feasibility":[277],"Sentinel-2A":[283],"classification,":[288],"which":[289],"further":[290],"good":[292],"reference":[293],"application":[295]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2022-10-13T00:00:00"}
