Saf Kızılçam (Pinus brutia Ten.) Meşcerelerinde Aktif ve Pasif Uydu Görüntüleri Kullanılarak Topraküstü Biyokütlenin Tahmin Edilmesi (Anamur Orman İşletme Şefliği Örneği)

Bu çalışmanın amacı; saf kızılçam (Pinus brutia Ten.) meşcrelerinde aktif (Sentinel-1A) ve pasif (Landsat 8 OLI) uydu görüntüleri ile bazı topoğrafik veriler kullanılarak topraküstü biyokütlenin tahmin edilmesidir. Çalışmada toplam 404 adet örnek alan verisi kullanılmıştır. Bu örnek alan verilerinin 323 (%80) modellerin oluşturulmasında ve 81 (%20) ise modellerin test edilmesinde kullanılmıştır. Her bir örnek alana ilişkin topraküstü biyokütle değerleri allometrik denklem kullanılarak hesaplanmıştır. Ayrıca her bir örnek alana ilişkin Landsat 8 OLI uydu görüntüsünden bant reflektans, vejetasyon indis ve tekstür değerleri, Sentinel-1A uydu görüntüsünün her iki polarizasyonu (VV ve VH) için parlaklık ve geri yansıtım değerleri ile Alos-Palsar uydu görüntüsünden üretilen Sayısal Yükseklik Model (SYM) verisinden yükselti, eğim ve bakı değerleri hesaplanmıştır. Topraküstü biyokütle ile Landsat 8 OLI, Sentinel-1A ve SAM verisinden elde edilen değişkenler arasındaki ilişkiler regresyon analizi ile modellenmiştir. Toplam 22 farklı regresyon modeli geliştirilmiştir. Geliştirilen modeller arasında en iyi ilişki (R2= 0,509 ; Sy.x= 28,39), Landsat 8 OLI uydu görüntüsünün bant reflektans değerleri, vejetasyon indisleri, tekstür değerleri, Sentinel-1A uydu görüntüsünün iki polarizasyona ilişkin parlaklık değerleri ile yükselti ve bakının bağımsız değişkenler olarak yer aldığı modelle elde edilmiştir.

Anahtar Kelimeler:

Topraküstü biyomas, Sentinel 1A, Landsat 8 OLI, allometrik denklem, kızılçam

Estimating Aboveground Biomass Using Active and Passive Satel-lite Image in Pure Calabrian Pine (Pinus brutia Ten.) Stands (A Case Study in Anamur Forest Planning Unit)

The aim of this study is to estimate aboveground biomass in pure Calabrian pine (Pinus brutia Ten.) stands using active (Sentinel-1A) and passive (Landsat 8 OLI) satellite images and some topographic data. Sample plot data of a total of 404 sample areas were used in the study. Of these sample plot data, 323 (80%) were used to create models and 81 (20%) to test models. Aboveground biomass values for each sample plot were calculated using the allometric equation. In addition, band reflectance, vegetation indices and texture values from Landsat 8 OLI satellite image for each sample plot, brightness and backscattering values for both polarizations (VV and VH) of Sentinel-1A satellite image, and the elevation, slope and aspect values were calculated from the Digital Elevation Model (DEM) data produced from the Alos-Palsar satellite image. Relationships between aboveground biomass and variables obtained from Landsat 8 OLI, Sentinel-1A and SAM data were modelled regression analysis. A total of 22 different regression models were developed. The best success among the developed models was obtained with the model (R2= 0.509; Sy.x= 28.39) in which the band reflectance values, vegetation indices and texture values of the Landsat 8 OLI satellite image, the brightness values of the two polarizations of the Sentinel-1A satellite image, elevation and aspect are included as independent variables.

Keywords:

Abaveground biomass, Sentinel 1A, Landsat 8 OLI, allometric equation, calabrian pine,

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