{"id":"https://openalex.org/W7127427249","doi":"https://doi.org/10.1109/access.2026.3660738","title":"High-Precision Canopy Height Estimation Using Autoencoders With Multisource RGB Satellite Imagery and LiDAR Fusion","display_name":"High-Precision Canopy Height Estimation Using Autoencoders With Multisource RGB Satellite Imagery and LiDAR Fusion","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7127427249","doi":"https://doi.org/10.1109/access.2026.3660738"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3660738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660738","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3660738","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Leena Thomas","orcid":"https://orcid.org/0009-0001-5016-6303"},"institutions":[{"id":"https://openalex.org/I96797292","display_name":"Noorul Islam University","ror":"https://ror.org/01y2gf490","country_code":"IN","type":"education","lineage":["https://openalex.org/I96797292"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Leena Thomas","raw_affiliation_strings":["Noorul Islam Centre for Higher Education, Kumaracoil, India"],"raw_orcid":"https://orcid.org/0009-0001-5016-6303","affiliations":[{"raw_affiliation_string":"Noorul Islam Centre for Higher Education, Kumaracoil, India","institution_ids":["https://openalex.org/I96797292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124941224","display_name":"M Mary Synthuja Jain Preetha","orcid":null},"institutions":[{"id":"https://openalex.org/I96797292","display_name":"Noorul Islam University","ror":"https://ror.org/01y2gf490","country_code":"IN","type":"education","lineage":["https://openalex.org/I96797292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Mary Synthuja Jain Preetha","raw_affiliation_strings":["Noorul Islam Centre for Higher Education, Kumaracoil, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noorul Islam Centre for Higher Education, Kumaracoil, India","institution_ids":["https://openalex.org/I96797292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112953149","display_name":"K. S. Vijula Grace","orcid":null},"institutions":[{"id":"https://openalex.org/I96797292","display_name":"Noorul Islam University","ror":"https://ror.org/01y2gf490","country_code":"IN","type":"education","lineage":["https://openalex.org/I96797292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. S. Vijula Grace","raw_affiliation_strings":["Noorul Islam Centre for Higher Education, Kumaracoil, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Noorul Islam Centre for Higher Education, Kumaracoil, India","institution_ids":["https://openalex.org/I96797292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96797292"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20806569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"23894","last_page":"23906"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.8281000256538391,"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":0.8281000256538391,"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":0.12110000103712082,"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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.00559999980032444,"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/canopy","display_name":"Canopy","score":0.73580002784729},{"id":"https://openalex.org/keywords/deciduous","display_name":"Deciduous","score":0.6635000109672546},{"id":"https://openalex.org/keywords/tree-canopy","display_name":"Tree canopy","score":0.4738999903202057},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.4641999900341034},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.44339999556541443},{"id":"https://openalex.org/keywords/deforestation","display_name":"Deforestation (computer science)","score":0.4417000114917755},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4059000015258789},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4034999907016754},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.40130001306533813}],"concepts":[{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.73580002784729},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6765999794006348},{"id":"https://openalex.org/C33283694","wikidata":"https://www.wikidata.org/wiki/Q1131316","display_name":"Deciduous","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5415999889373779},{"id":"https://openalex.org/C39807119","wikidata":"https://www.wikidata.org/wiki/Q1134228","display_name":"Tree canopy","level":3,"score":0.4738999903202057},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C2777399953","wikidata":"https://www.wikidata.org/wiki/Q2155658","display_name":"Deforestation (computer science)","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.40130001306533813},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.37059998512268066},{"id":"https://openalex.org/C108216600","wikidata":"https://www.wikidata.org/wiki/Q511668","display_name":"Tropical and subtropical dry broadleaf forests","level":2,"score":0.36550000309944153},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C2778405918","wikidata":"https://www.wikidata.org/wiki/Q1082970","display_name":"Reducing emissions from deforestation and forest degradation","level":4,"score":0.3091000020503998},{"id":"https://openalex.org/C139669111","wikidata":"https://www.wikidata.org/wiki/Q422666","display_name":"Understory","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C555313981","wikidata":"https://www.wikidata.org/wiki/Q199403","display_name":"Tropical rainforest","level":3,"score":0.29989999532699585},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C2776285232","wikidata":"https://www.wikidata.org/wiki/Q1048194","display_name":"Tropical forest","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.28540000319480896},{"id":"https://openalex.org/C73935091","wikidata":"https://www.wikidata.org/wiki/Q2249329","display_name":"Forest ecology","level":3,"score":0.2793999910354614},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C2619416","wikidata":"https://www.wikidata.org/wiki/Q9444","display_name":"Rainforest","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3660738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660738","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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 Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3660738","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3660738","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.692441999912262,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1745334888","https://openalex.org/W1965050236","https://openalex.org/W1965555277","https://openalex.org/W2114845814","https://openalex.org/W2279566557","https://openalex.org/W2411484482","https://openalex.org/W2725897987","https://openalex.org/W2786055572","https://openalex.org/W2798405286","https://openalex.org/W2900448217","https://openalex.org/W2914261052","https://openalex.org/W2963163009","https://openalex.org/W2968347155","https://openalex.org/W3021060199","https://openalex.org/W3094643344","https://openalex.org/W3109802736","https://openalex.org/W3182972367","https://openalex.org/W3186917005","https://openalex.org/W3206706034","https://openalex.org/W4205698403","https://openalex.org/W4214588794","https://openalex.org/W4280562927","https://openalex.org/W4283205801","https://openalex.org/W4311415873","https://openalex.org/W4387141420","https://openalex.org/W4388448546"],"related_works":[],"abstract_inverted_index":{"Deforestation":[0],"poses":[1],"a":[2,43,128,191,204],"significant":[3,129],"threat":[4],"to":[5,20,84,106],"humanity.":[6],"Accurate":[7],"measurement":[8],"of":[9,24,39,51,91,110,134,143,151,158,177,184,193,198,206],"canopy":[10,36,88,111,135],"height":[11,37,76,89,112,136,192],"and":[12,75,103,168],"land":[13,212],"cover":[14],"in":[15,46,119,131,146,161,187],"protected":[16,44],"areas":[17],"is":[18],"essential":[19],"understand":[21],"the":[22,40,57,79,108,120,132,144,147,159,185],"extent":[23],"deforestation.":[25],"In":[26],"this":[27],"study,":[28],"we":[29],"introduce":[30],"three":[31,95],"novel":[32],"methods":[33],"for":[34,56],"creating":[35],"maps":[38,90],"Western":[41,121,148],"Ghats,":[42],"area":[45],"India,":[47],"with":[48,156],"an":[49],"accuracy":[50,109,133],"1":[52],"meter":[53],"per":[54],"pixel":[55],"year":[58],"2024.":[59],"We":[60],"develop":[61],"multiple":[62],"Machine":[63],"Learning":[64],"models":[65,96,126],"that":[66,141],"integrate":[67],"RGB":[68],"images":[69],"from":[70,78,99],"Planet":[71],"Labs,":[72],"Sentinel":[73],"data,":[74],"information":[77],"Global":[80],"Ecosystem":[81],"Dynamics":[82],"Investigation":[83],"produce":[85],"high":[86],"quality":[87],"theWestern":[92,178],"Ghats.":[93,179],"These":[94],"draw":[97],"inspiration":[98],"Convolutional":[100],"Autoencoder":[101],"architecture":[102],"are":[104],"designed":[105],"enhance":[107],"prediction":[113],"across":[114],"various":[115],"tropical":[116,152,199],"forest":[117,145,174],"types":[118],"Ghats":[122,149],"region.":[123],"The":[124],"proposed":[125],"offer":[127],"improvement":[130],"estimation.":[137],"Our":[138],"study":[139],"found":[140],"51%":[142],"consists":[150],"moist":[153],"deciduous":[154,173,201],"forests,":[155],"17%":[157],"trees":[160,186],"these":[162,188],"forests":[163,189,202],"having":[164],"heights":[165],"between":[166],"20":[167],"24":[169],"meters.":[170,195],"Tropical":[171],"dry":[172,200],"covers":[175],"41%":[176],"Furthermore,":[180],"only":[181],"2.":[182],"8%":[183],"exceed":[190],"40":[194],"This":[196],"expansion":[197],"signifies":[203],"stage":[205],"natural":[207],"succession,":[208],"influenced":[209],"by":[210],"past":[211],"use":[213],"practices":[214],"or":[215],"disturbances.":[216]},"counts_by_year":[],"updated_date":"2026-02-19T06:27:42.648592","created_date":"2026-02-04T00:00:00"}