Estimating aboveground carbon stock using landsat 8 oli satellite image in pure scots pine (Pinus sylvestris L.) stands (a case study of Aladağ Planning Unit)
2024
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Danışman: Doç. Dr. Oytun Emre Sakıcı
Özet (EN)
In this study, modeling the amount of aboveground carbon in pure Scots pine stands distributed in Aladağ Forest Planning Unit using remote sensing data was aimed. The aboveground carbon amounts of the sample plots were calculated using field measurements made in sample plot taken from pure Scots pine stands of different development ages and canopy classes in the study area. The remote sensing data (band reflectance values and vegetation indices) used in the study were obtained from the Landsat 8 OLI satellite image. The relationships between aboveground carbon amounts and remote sensing data were examined with Correlation Analysis, and aboveground carbon amount estimation models were developed with Stepwise Regression Analysis. Depending on the independent variables included in the model, successful results were obtained for four different model structures in which only band reflectance values, band reflectance values and topographic data, only vegetation indices, and band reflectance values and vegetation indices were used as independent variables. Adjusted Coefficient of Determination (R_d^2), Root Mean Squared Error (RMSE) and Akaike Information Criterion (AIC) were used to reveal the model performances. The most successful models were M3 (R_d^2=0,593) for the model structure including only band reflectance values are used, M6 (R_d^2=0,581) for the model structure including band reflectance values and topographic data together, M12 (R_d^2=0,632) for the model structure including only vegetation indices. and M13 (R_d^2=0,576) for the model structure including band reflectance values and vegetation indices together.
Yazar
Sedat Işık
Bu Yayına Nasıl Atıf Yapılır
Sedat Işık (Master Thesis). Estimating aboveground carbon stock using landsat 8 oli satellite image in pure scots pine (Pinus sylvestris L.) stands (a case study of Aladağ Planning Unit), 2024, Kastamonu University.
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