Modeling Above Ground Biomass in Calabrian Pine Forests of Düzlerçamı (Antalya)
Yazarlar (2)
Doç. Dr. Doğukan Doğu YAVAŞLI Kırşehir Ahi Evran Üniversitesi, Türkiye
Prof. Dr. Muhibullah Kirami Ölgen Ege Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(Diğer hakemli ulusal dergilerde yayınlanan tam makale)
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| Dergi Adı | Ege Coğrafya Dergisi | ||
| Dergi ISSN | 2636-8056 | ||
| Dergi Tarandığı Indeksler | Index Copernicus | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2017 |
| Cilt / Sayı / Sayfa | 26 / 2 / 151–161 | DOI | – |
| UAK Araştırma Alanları |
Uzaktan Algılama
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| Özet |
| Estimation of forest biomass isneeded for monitoring the changes in carbon stocks as well as other purposes.This study reports on a test of the ability to estimate above ground biomass ofCalabrian pine forests of Düzlerçamı, Antalya, Turkey using Landsat andICESat/GLAS data. The field data has been collected in 2017 and plot-levelestimates were calculated using the allometric equations. GLAS parameters andvarious Landsat vegetation indices were modeled using multiple regressionanalysis to estimate above ground biomass. In the first model (ModelA) heightof median energy (HOME) and the ratio of HOME to maximum vegetation height(%HOME) parameter of GLAS showed relation with field based estimates of aboveground biomass with a coefficient of determination (R2) of 0.87. Above groundbiomass derived from ModelA and the variables obtained from Landsat indices hasbeen used at the second model (ModelB) had a R2 of 0.52 meaning the GLAS datais poorly correlated with Landsat at the study area. A better statisticalrelationship has been found with Landsat data and AGB with a R2 of 0.91 inModelC that uses Landsat pixel values of each bands and pixel values of theindices are used as independent variable to explain above ground biomass. Theresults demonstrate a current potential for above ground biomass estimationofforests using optical sensor data and satellite lidar where airbornelidar data is not widely available. |
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