Estimation of Aboveground Carbon Using Active and Passive Satellite Image in Pure Crimean Pine Stands

Erdal Şahan; Alkan Gunlu

Makale detayları

Estimation of Aboveground Carbon Using Active and Passive Satellite Image in Pure Crimean Pine Stands

Yazarlar:

Erdal Şahan | Alkan Gunlu

Yayıncı:

Bartin University

Ana Başlıklar:

Orman Biyometrisi

Dergi:

Bartın Orman Fakültesi Dergisi Vol.26 Issue 4, pp.377-391

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001333086

pISSN:

1302-0943

Anahtar kelimeler:

Özet:

 This study was conducted in pure Crimean stands located within the boundaries of Sinop Regional Directorate of Forestry, Boyabat Forest Enterprise, Elekçamı Forest Planning Unit. A total of 247 sample plot inventory data were utilized. Using inventory data, aboveground carbon values were calculated for each sample plot. Then, for each sample plot, band brightness and vegetation indice obtained from the Landsat 5 TM satellite image, polarization HH and HV brightness and backscattering obtained from the ALOS-PALSAR satellite image, as well as slope, aspect, and elevation values, were calculated. The relationships between aboveground carbon values and the variables mentioned above were modeled using multiple regression analysis. A total of 14 models were developed. When examining the success of the developed models, the highest model accuracy R_adj20.655;Sy.x0.18147 was achieved in the model that included vegetation indices from the Landsat 5 TM satellite image, brightness and backscattering values from the ALOS-PALSAR satellite image, along with slope, aspect, and elevation as independent variables.

 This study was conducted in pure Crimean stands located within the boundaries of Sinop Regional Directorate of Forestry, Boyabat Forest Enterprise, Elekçamı Forest Planning Unit. A total of 247 sample plot inventory data were utilized. Using inventory data, aboveground carbon values were calculated for each sample plot. Then, for each sample plot, band brightness and vegetation indice obtained from the Landsat 5 TM satellite image, polarization HH and HV brightness and backscattering obtained from the ALOS-PALSAR satellite image, as well as slope, aspect, and elevation values, were calculated. The relationships between aboveground carbon values and the variables mentioned above were modeled using multiple regression analysis. A total of 14 models were developed. When examining the success of the developed models, the highest model accuracy R_adj20.655;Sy.x0.18147 was achieved in the model that included vegetation indices from the Landsat 5 TM satellite image, brightness and backscattering values from the ALOS-PALSAR satellite image, along with slope, aspect, and elevation as independent variables.

 This study was conducted in pure Crimean stands located within the boundaries of Sinop Regional Directorate of Forestry, Boyabat Forest Enterprise, Elekçamı Forest Planning Unit. A total of 247 sample plot inventory data were utilized. Using inventory data, aboveground carbon values were calculated for each sample plot. Then, for each sample plot, band brightness and vegetation indice obtained from the Landsat 5 TM satellite image, polarization HH and HV brightness and backscattering obtained from the ALOS-PALSAR satellite image, as well as slope, aspect, and elevation values, were calculated. The relationships between aboveground carbon values and the variables mentioned above were modeled using multiple regression analysis. A total of 14 models were developed. When examining the success of the developed models, the highest model accuracy R_adj20.655;Sy.x0.18147 was achieved in the model that included vegetation indices from the Landsat 5 TM satellite image, brightness and backscattering values from the ALOS-PALSAR satellite image, along with slope, aspect, and elevation as independent variables.

 Bu çalışma, Sinop Orman Bölge Müdürlüğü, Boyabat Orman İşletme Müdürlüğü, Elekçamı Orman İşletme Şefliği sınırları içerisinde yayılış gösteren saf karaçam meşcerelerinde gerçekleştirilmiştir. Çalışma kapsamında toplam 247 adet örnek alan verisi kullanılmıştır. Envanter verilerinden yararlanılarak her bir örnek alan için topraküstü karbon TÜK değerleri hesaplanmıştır. Her bir örnek alan için Landsat 5 TM bant yansıma ve vejetasyon indis, ALOS-PALSAR uydu görüntüsüne ait HH ve HV polarizasyonlarından parlaklık ve geri yansıtım ile örnek alanlara ilişkin eğim, bakı ve yükselti değerleri hesaplanmıştır. TÜK değerleri ile yukarıda açıklanan değişkenler arasındaki ilişkiler çoğul regresyon analizi ile modellenmiştir. Toplam 14 adet model geliştirilmiştir. Geliştirilen model başarıları incelendiğinde, Landsat 5 TM vejetasyon indis, ALOS-PALSAR parlaklık ve geri yansıtım değişkenleri ile eğim, bakı ve yükselti değerlerinin bağımsız değişkenler olarak yer aldığı modelde belirtme katsayısı R_düz20.655; Sy.x0.18147 elde edilmiştir.

Makale detayları

Estimation of Aboveground Carbon Using Active and Passive Satellite Image in Pure Crimean Pine Stands

Yazarlar:

Erdal Şahan | Alkan Gunlu

Yayıncı:

Bartin University

Ana Başlıklar:

Orman Biyometrisi

Dergi:

Bartın Orman Fakültesi Dergisi Vol.26 Issue 4, pp.377-391

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001333086

pISSN:

1302-0943

Landsat 5 TM

ALOS-PALSAR

multiple regression analysisLandsat 5 TM

ALOS-PALSAR

çoğul regresyon analizi

Sayı

Makale detayları

Estimation of Aboveground Carbon Using Active and Passive Satellite Image in Pure Crimean Pine Stands

Yazarlar: Erdal Şahan | Alkan Gunlu

Yayıncı: Bartin University

Ana Başlıklar: Orman Biyometrisi

Dergi: Bartın Orman Fakültesi Dergisi Vol.26 Issue 4, pp.377-391

Belge Tipi: Makale

Yayın Tarihi: 12/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001333086

pISSN: 1302-0943

Landsat 5 TM

ALOS-PALSAR

multiple regression analysisLandsat 5 TM

ALOS-PALSAR

çoğul regresyon analizi

Sayı

Yazarlar:

Erdal Şahan | Alkan Gunlu

Yayıncı:

Bartin University

Ana Başlıklar:

Orman Biyometrisi

Dergi:

Bartın Orman Fakültesi Dergisi Vol.26 Issue 4, pp.377-391

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001333086

pISSN:

1302-0943