Estimating Some Stand Parameters Using Sentinel-1 and Sentinel-2 Satellite Images in Pure Black and Scots Pine Stands: A Case Study from Turkiye

Abstract

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 T & uuml;rkiye 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 (R-d(2)= 0.170) and stand density (R-d(2)= 0.397), the sum of Sentinel-1 pixels for the number of trees (R-d(2)= 0.396) and the mean of Sentinel-2 pixels for stand volume (R-d(2)= 0.095). For Scots pine stands, the best models used the mean of Sentinel-2 pixels for stand diameter (R-d(2)= 0.314) and the sum of Sentinel-2 pixels for the number of trees (R-d(2)= 0.277), basal area (R-d(2)= 0.344), stand volume (R-d(2)= 0.123), and stand density (R-d(2)= 0.432). It achieved its best results in estimating stand density, showing the potential of remote sensing for forest inventory.