Research article

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

A. Günlü , I. Ercanli, E.Z. Başkent, G. Çakır

A. Günlü
Çankırı Karatekin University, Faculty of Forestry, 18200, Çankırı, Turkey. Email: alkangunlu@karatekin.edu.tr
I. Ercanli
Çankırı Karatekin University, Faculty of Forestry, 18200, Çankırı, Turkey
E.Z. Başkent
Karadeniz Technical University, Faculty of Forestry, 61080, Trabzon, Turkey
G. Çakır
Gümüşhane University, Graduate School of Natural and Applied Sciences, Department of Forestry and Environmental Science, 29000, Gümüşhane, Turkey

Online First: November 27, 2014
Günlü, A., Ercanli, I., Başkent, E., Çakır, G. 2014. Estimating aboveground biomass using Landsat TM imagery: A case study of Anatolian Crimean pine forests in Turkey. Annals of Forest Research DOI:10.15287/afr.2014.278


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 an 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 R2 of 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.


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  • A. Günlü
  • I. Ercanli
  • E.Z. Başkent
  • G. Çakır
  • A. Günlü
  • I. Ercanli
  • E.Z. Başkent
  • G. Çakır