{"id":"https://openalex.org/W7225410667","doi":"https://doi.org/10.3832/ifor4798-019","title":"Estimating leaf area index in semi-Mediterranean oak forests using Sentinel-2 and machine learning algorithms: cross-comparison with global satellite products","display_name":"Estimating leaf area index in semi-Mediterranean oak forests using Sentinel-2 and machine learning algorithms: cross-comparison with global satellite products","publication_year":2026,"publication_date":"2026-11-06","ids":{"openalex":"https://openalex.org/W7225410667","doi":"https://doi.org/10.3832/ifor4798-019"},"language":"en","primary_location":{"id":"doi:10.3832/ifor4798-019","doi":"https://doi.org/10.3832/ifor4798-019","is_oa":true,"landing_page_url":"https://doi.org/10.3832/ifor4798-019","pdf_url":"https://iforest.sisef.org/pdf/?id=ifor4798-019","source":{"id":"https://openalex.org/S104841470","display_name":"iForest - Biogeosciences and Forestry","issn_l":"1971-7458","issn":["1971-7458"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","ddh","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310317615","host_organization_name":"Italian Society of Silviculture and Forest Ecology","host_organization_lineage":["https://openalex.org/P4310317615"],"host_organization_lineage_names":["Italian Society of Silviculture and Forest Ecology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"iForest - Biogeosciences and Forestry","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://iforest.sisef.org/pdf/?id=ifor4798-019","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5161123711","display_name":"N Miri","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N Miri","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161012238","display_name":"P Fatehi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P Fatehi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161133737","display_name":"M Pir Bavaghar","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M Pir Bavaghar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160990786","display_name":"L Homolov\u00e1","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L Homolov\u00e1","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"6","first_page":"388","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.875,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.875,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.12150000035762787,"subfield":{"id":"https://openalex.org/subfields/1107","display_name":"Forestry"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.0005000000237487257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"leaf area index","score":0.9739999771118164},{"id":"https://openalex.org/keywords/oak-forest","display_name":"oak forest","score":0.6919999718666077},{"id":"https://openalex.org/keywords/zagros-mountains","display_name":"Zagros Mountains","score":0.8659999966621399},{"id":"https://openalex.org/keywords/sentinel-2","display_name":"Sentinel-2","score":0.9940000176429749},{"id":"https://openalex.org/keywords/machine-learning-regression","display_name":"machine learning regression","score":0.7929999828338623},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9620000123977661},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.9440000057220459},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.9940000176429749},{"id":"https://openalex.org/keywords/digital-elevation-model","display_name":"digital elevation model","score":0.9190000295639038},{"id":"https://openalex.org/keywords/modis","display_name":"MODIS","score":0.9480000138282776},{"id":"https://openalex.org/keywords/proba-v","display_name":"PROBA-V","score":0.996999979019165},{"id":"https://openalex.org/keywords/canopy-structure","display_name":"canopy structure","score":0.6000000238418579},{"id":"https://openalex.org/keywords/lai-mapping","display_name":"LAI mapping","score":0.48500001430511475}],"concepts":[{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5943999886512756},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5781999826431274},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5235000252723694},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4242999851703644},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.4138000011444092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40049999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.375},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3741999864578247},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.3183000087738037},{"id":"https://openalex.org/C2986088632","wikidata":"https://www.wikidata.org/wiki/Q4259364","display_name":"Forest cover","level":2,"score":0.31450000405311584},{"id":"https://openalex.org/C548217200","wikidata":"https://www.wikidata.org/wiki/Q251","display_name":"Java","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2987528665","wikidata":"https://www.wikidata.org/wiki/Q854845","display_name":"Earth observation satellite","level":3,"score":0.27399998903274536},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C2778751583","wikidata":"https://www.wikidata.org/wiki/Q1182618","display_name":"Defense Meteorological Satellite Program","level":3,"score":0.25209999084472656},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3832/ifor4798-019","doi":"https://doi.org/10.3832/ifor4798-019","is_oa":true,"landing_page_url":"https://doi.org/10.3832/ifor4798-019","pdf_url":"https://iforest.sisef.org/pdf/?id=ifor4798-019","source":{"id":"https://openalex.org/S104841470","display_name":"iForest - Biogeosciences and Forestry","issn_l":"1971-7458","issn":["1971-7458"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","ddh","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310317615","host_organization_name":"Italian Society of Silviculture and Forest Ecology","host_organization_lineage":["https://openalex.org/P4310317615"],"host_organization_lineage_names":["Italian Society of Silviculture and Forest Ecology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"iForest - Biogeosciences and Forestry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:935cab92565a4a1292222f42d0913e29","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/935cab92565a4a1292222f42d0913e29","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"iForest - Biogeosciences and Forestry, Vol 19, Iss 1, Pp 388-395 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3832/ifor4798-019","doi":"https://doi.org/10.3832/ifor4798-019","is_oa":true,"landing_page_url":"https://doi.org/10.3832/ifor4798-019","pdf_url":"https://iforest.sisef.org/pdf/?id=ifor4798-019","source":{"id":"https://openalex.org/S104841470","display_name":"iForest - Biogeosciences and Forestry","issn_l":"1971-7458","issn":["1971-7458"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","ddh","doaj","dongbi-d","jufo-1","norway-1","oarl","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310317615","host_organization_name":"Italian Society of Silviculture and Forest Ecology","host_organization_lineage":["https://openalex.org/P4310317615"],"host_organization_lineage_names":["Italian Society of Silviculture and Forest Ecology"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"iForest - Biogeosciences and Forestry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life on land","score":1.0},{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4399999976158142}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322482","display_name":"Akademie V\u011bd \u010cesk\u00e9 Republiky","ror":"https://ror.org/053avzc18"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225410667.pdf","grobid_xml":"https://content.openalex.org/works/W7225410667.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W221493477","https://openalex.org/W1967248741","https://openalex.org/W2016602147","https://openalex.org/W2032305420","https://openalex.org/W2038617433","https://openalex.org/W2058214432","https://openalex.org/W2151647593","https://openalex.org/W2155722785","https://openalex.org/W2164936431","https://openalex.org/W2339345728","https://openalex.org/W2531213996","https://openalex.org/W2600798029","https://openalex.org/W2611080000","https://openalex.org/W2890271011","https://openalex.org/W2911964244","https://openalex.org/W2924772986","https://openalex.org/W2938239749","https://openalex.org/W2945958600","https://openalex.org/W2963446368","https://openalex.org/W2976696463","https://openalex.org/W2990165672","https://openalex.org/W3038890942","https://openalex.org/W3039309897","https://openalex.org/W3041165813","https://openalex.org/W3043213732","https://openalex.org/W3093660509","https://openalex.org/W3115746930","https://openalex.org/W3158405682","https://openalex.org/W4205917575","https://openalex.org/W4206781954","https://openalex.org/W4213454111","https://openalex.org/W4221070098","https://openalex.org/W4292843641","https://openalex.org/W4295414707"],"related_works":["https://openalex.org/W2005212695","https://openalex.org/W7035899735","https://openalex.org/W3153313607","https://openalex.org/W7000308632","https://openalex.org/W2329333366","https://openalex.org/W6959959338","https://openalex.org/W2906852213","https://openalex.org/W324522846","https://openalex.org/W7205833741","https://openalex.org/W3128915553"],"abstract_inverted_index":{"Leaf":[0],"area":[1],"index":[2],"(LAI)":[3],"provides":[4,194],"crucial":[5],"insights":[6],"into":[7],"forest":[8,228],"canopy":[9],"structure,":[10],"vegetation":[11],"density,":[12],"and":[13,38,80,98,104,140,159,192,197,218],"overall":[14],"ecosystem":[15],"functioning.":[16],"In":[17],"the":[18,47,62,106,126,147,165,219],"Zagros":[19,63],"Mountains":[20],"of":[21,49,167,179,214,221],"northwestern":[22],"Iran,":[23],"traditional":[24],"silvopastoral":[25],"practices":[26],"rely":[27],"on":[28],"tree":[29],"foliage":[30],"as":[31],"animal":[32],"fodder":[33],"for":[34,52,200,226],"local":[35],"communities.":[36],"Understanding":[37],"estimating":[39],"LAI":[40,60,111,149,154,169,202,208],"in":[41,61,67,109,115,203],"these":[42,227],"forests":[43],"can":[44],"therefore":[45],"support":[46],"adoption":[48],"appropriate":[50],"strategies":[51],"sustainable":[53],"management.":[54],"This":[55],"study":[56,184],"aims":[57],"to":[58,174],"map":[59,150],"semi-Mediterranean":[64],"Forests":[65],"(ZMFs)":[66],"Iran":[68],"using":[69],"Machine":[70],"Learning":[71],"Regression":[72,93],"Algorithms":[73],"(MLRAs)":[74],"combined":[75],"with":[76,131,151,190],"Sentinel-2":[77,156],"(S-2)":[78],"data":[79,112,189],"a":[81],"Digital":[82],"Elevation":[83],"Model":[84],"(DEM).":[85],"We":[86,144],"employed":[87],"three":[88,152],"MLRAs,":[89],"i.e.,":[90],"Support":[91],"Vector":[92],"(SVR),":[94],"K-Nearest":[95],"Neighbors":[96],"(KNN),":[97],"Random":[99],"Forest":[100],"(RF).":[101],"To":[102],"train":[103],"evaluate":[105],"algorithms\u2019":[107],"performance,":[108],"situ":[110],"were":[113],"collected":[114],"60":[116],"field":[117],"plots":[118],"measuring":[119],"20\u00d720":[120],"m.":[121],"The":[122,161,183],"results":[123,162],"revealed":[124],"that":[125,164,178,186],"RF":[127],"algorithm":[128],"performed":[129],"best,":[130],"R2":[132],"=":[133,136,142],"0.82,":[134],"RMSE":[135],"0.16":[137],"m2":[138],"m-2,":[139],"rRMSE":[141],"16.84.":[143],"further":[145],"cross-compared":[146],"generated":[148],"satellite-derived":[153],"products:":[155],"SNAP,":[157],"MODIS,":[158],"PROBA-V.":[160],"indicated":[163],"uncertainty":[166,212],"global":[168,207],"products":[170,209],"varies":[171],"from":[172],"30%":[173],"55%":[175],"higher":[176,211],"than":[177],"our":[180],"applied":[181],"approach.":[182],"concludes":[185],"integrating":[187],"S-2":[188],"DEM":[191],"MLRAs":[193],"an":[195],"accurate":[196],"reliable":[198],"method":[199],"mapping":[201],"open-canopy":[204],"ZMFs.":[205],"However,":[206],"show":[210],"because":[213],"lower":[215],"spatial":[216],"resolution":[217],"lack":[220],"suitable":[222],"empirical":[223],"transfer":[224],"functions":[225],"types.":[229]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-11-07T00:00:00"}
