Estimating aboveground biomass using landsat TM imagery: A case study of Anatolian Crimean pine forests in Turkey

MakaleAçık Erişim
  • SDG 13 · İklim Eylemi
  • SDG 15 · Karasal Yaşam

Özet

Forests play an important role in carbon circulation, and the productivity of forest ecosystems can be evaluated by evaluating its biomass. Evaluation of biomass aids the determination and understanding of changes in forest ecosystems. Because of the limitations of ground measurements of biomass, in recent times, satellite images have been broadly applied to estimate aboveground biomass (AGB). The objective of this study is to examine the relationships between AGB and individual band reflectance values and ten Vegetation Indices (VIs) obtained from a Landsat TM satellite image for a Anatolian pine forests in northwestern Turkey. Multiple regression analysis is utilized to predict the AGB. The AGB model using TM 1 and TM 2 had an adjusted R2of 0.465. Another AGB model using Enhanced Vegetation Index (EVI) and Normalized Difference 57 (ND57) had an adjusted R2 of 0.606. Our results reveal that VIs present better estimation of AGB in Anatolian pine forests as compared to individual band reflectance values.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/15455Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.15287/afr.2014.278Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorGünlü, A.
dc.contributor.authorErcanli, İ.
dc.contributor.authorBaşkent, E.Z.
dc.contributor.authorÇakır, G.
dc.date.accessioned2026-10-22T10:24:02.462573572Z
dc.date.available2026-10-22T10:24:02.462573572Z
dc.date.issued2014
dc.description.abstractForests play an important role in carbon circulation, and the productivity of forest ecosystems can be evaluated by evaluating its biomass. Evaluation of biomass aids the determination and understanding of changes in forest ecosystems. Because of the limitations of ground measurements of biomass, in recent times, satellite images have been broadly applied to estimate aboveground biomass (AGB). The objective of this study is to examine the relationships between AGB and individual band reflectance values and ten Vegetation Indices (VIs) obtained from a Landsat TM satellite image for a Anatolian pine forests in northwestern Turkey. Multiple regression analysis is utilized to predict the AGB. The AGB model using TM 1 and TM 2 had an adjusted R2of 0.465. Another AGB model using Enhanced Vegetation Index (EVI) and Normalized Difference 57 (ND57) had an adjusted R2 of 0.606. Our results reveal that VIs present better estimation of AGB in Anatolian pine forests as compared to individual band reflectance values.
dc.description.sponsorshipHead of Forest Management and Planning Department, General Directorate of Forestry, Republic of Turkey
dc.identifier.doi10.15287/afr.2014.278
dc.identifier.eissn2065-2445
dc.identifier.endpage298
dc.identifier.issn1844-8135
dc.identifier.issue2
dc.identifier.scopus2-s2.0-84920093317
dc.identifier.startpage289
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/15455
dc.identifier.volume57
dc.identifier.wosWOS:000349133100010
dc.language.isoen
dc.publisherEditura Silvica
dc.relation.ispartofAnnals of Forest Research
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAboveground biomass
dc.subjectLandsat TM satellite data
dc.subjectModelling
dc.subject.classificationForestry
dc.subject.otherLEAF-AREA INDEX
dc.subject.otherSATELLITE DATA
dc.subject.otherTREE BIOMASS
dc.subject.otherSITE INDEX
dc.subject.otherBASAL AREA
dc.subject.otherETM+ DATA
dc.subject.otherINVENTORY
dc.subject.otherCARBON
dc.subject.otherLIDAR
dc.subject.otherVEGETATION
dc.titleEstimating aboveground biomass using landsat TM imagery: A case study of Anatolian Crimean pine forests in Turkey
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex62
rdl.citation.scopus56
rdl.citation.wos48
rdl.oa.statusgold
rdl.oa.statusclosed
rdl.oa.urlhttps://doi.org/10.15287/afr.2014.278
rdl.sdgSDG15
rdl.sdgSDG13
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)