Düzlerçamı Kızılçam Ormanında (Antalya) Toprak Üstü Orman Biyokütlesinin Modellenmesi

Yıl 2017, Cilt: 26 Sayı: 2, 151 - 161, 26.12.2017

Doğukan Doğu Yavaşlı , M. Kirami Ölgen

Öz

Estimation of forest biomass is
needed 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 of
Calabrian pine forests of Düzlerçamı, Antalya, Turkey using Landsat and
ICESat/GLAS data. The field data has been collected in 2017 and plot-level
estimates were calculated using the allometric equations. GLAS parameters and
various Landsat vegetation indices were modeled using multiple regression
analysis to estimate above ground biomass. In the first model (ModelA) height
of median energy (HOME) and the ratio of HOME to maximum vegetation height
(%HOME) parameter of GLAS showed relation with field based estimates of above
ground biomass with a coefficient of determination (R2) of 0.87. Above ground
biomass derived from ModelA and the variables obtained from Landsat indices has
been used at the second model (ModelB) had a R2 of 0.52 meaning the GLAS data
is poorly correlated with Landsat at the study area. A better statistical
relationship has been found with Landsat data and AGB with a R2 of 0.91 in
ModelC that uses Landsat pixel values of each bands and pixel values of the
indices are used as independent variable to explain above ground biomass. The
results demonstrate a current potential for above ground biomass estimation
of forests using optical sensor data and satellite lidar where airborne
lidar data is not widely available.

Anahtar Kelimeler

Above ground biomass, forest, ICESat/GLAS, Landsat

MODELING ABOVE GROUND BIOMASS IN CALABRIAN PINE FORESTS OF DÜZLERÇAMI (ANTALYA)

Öz

Karbon stoklarındaki değişimlerin
izlenmesi ile birlikte çeşitli diğer amaçlar için orman biyokütlesinin
belirlenmesine ihtiyaç duyulmaktadır. Bu çalışma Düzlerçamı kızılçam ormanında
(Antalya) toprak üstü orman biyokütlesinin Landsat ve ICESat/GLAS verileri
kullanarak belirlenebilmesini test etmektedir. 2017 yılında arazi çalışmaları
ile örneklem alanlarından toplanan veriler ile allometrik eşitlikler
kullanılarak gerçek biyokütle verileri hesaplanmıştır. Toprak üstü orman
biyokütlesinin modellenmesinde çok değişkenli regresyon analizi ile GLAS
parametreleri ve çeşitli Landsat vejetasyon indekslerinden yararlanılmıştır.
Birinci modelde (ModelA) GLAS verisinden medyan enerjinin yüksekliği (HOME) ve
HOME’un maksimum yüksekliğe oranı parametrelerinin araziden toplanan biyokütle
verileri ile olan ilişkisinde determinasyon katsayısı (R2) 0.87 olarak tespit
edilmiştir. ModelA’dan elde edilen toprak üstü orman biyokütlesi ile çeşitli
Landsat indekslerinin kullanıldığı ikinci modelde (ModelB) 0.52 bulunan R2
değeri GLAS verisinin çalışma alanında Landsat veriler ile zayıf bir
korelasyonu bulunduğunu göstermiştir. Toprak üstü orman biyokütlesini açıklamak
için Landsat indeks değerlerinin bağımsız değişken olarak kullanıldığı ModelC’de
ise 0.91 R2 ile istatistiksel olarak daha anlamlı bir istatistiksel ilişki
belirlenmiştir. Sonuçlar toprak üstü orman biyokütlesinin belirlenmesinde hava
lidar verilerinin bulunmadığı durumlarda optik sensörlerin ve uydu tabanlı
lidar verilerin güncel potansiyelini göstermektedir.

Anahtar Kelimeler

Toprak üstü biyokütle, orman, ICESat/GLAS, Landsat

Kaynakça

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