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Estimating Some Stand Parameters Using Sentinel-1 and Sentinel-2 Satellite Images in Pure Black and Scots Pine Stands: A Case Study from Türkiye     
Yazarlar (2)
Arş. Gör. Döndü DEMİREL Arş. Gör. Döndü DEMİREL
Kastamonu Üniversitesi, Türkiye
Doç. Dr. Oytun Emre SAKICI Doç. Dr. Oytun Emre SAKICI
Kastamonu Üniversitesi, Türkiye
Devamını Göster
Özet
This study modeled various stand parameters (stand diameter, number of trees, basal area, volume, density) in pure Black and Scots pine stands in the Kastamonu Region of Türkiye using remote sensing data. A total of 146 Black pine and 96 Scots pine sample plots were analyzed. Stand parameters were calculated based on data obtained from field measurements. Data from Sentinel-1 (backscattering, polarization ratio, texture) and Sentinel-2 (reflectance, vegetation index, texture) were used, aggregated as the mean and sum of pixels for the sample plots. Correlation analysis identified relationships between stand parameters and remote sensing data, while stepwise regression analysis developed estimation models. In Black pine stands, the best models used the sum of Sentinel-2 pixels for stand diameter ((Formula presented.) = 0.170) and stand density ((Formula presented.) = 0.397), the sum of Sentinel-1 pixels for the number of trees ((Formula presented.) = 0.396) and the mean of Sentinel-2 pixels for stand volume ((Formula presented.) = 0.095). For Scots pine stands, the best models used the mean of Sentinel-2 pixels for stand diameter ((Formula presented.) = 0.314) and the sum of Sentinel-2 pixels for the number of trees ((Formula presented.) = 0.277), basal area ((Formula presented.) = 0.344), stand volume ((Formula presented.) = 0.123), and stand density ((Formula presented.) = 0.432). It achieved its best results in estimating stand density, showing the potential of remote sensing for forest inventory.
Anahtar Kelimeler
active sensor | forest inventory | Forestry | innovation and infrastructure | passive sensor | SDG 9: industry
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı Journal of Sustainable Forestry
Dergi ISSN 1054-9811 Wos Dergi Scopus Dergi
Dergi Grubu Q2
Makale Dili İngilizce
Basım Tarihi 01-2025
Sayı 1
Doi Numarası 10.1080/10549811.2025.2529390