Modeling windthrow through remote sensing and analysis of environmental factors: Case of Bolu, Türkiye

Climate change may lead to increased or decreased future forest productivity. However, more frequent storms are expected in Europe and are increasingly considered an important abiotic damage factor for forests, leading to windthrows that result in both economic and ecological losses. Remote sensing data helps in detecting past windthrow and assessing both ecological and economic losses. In this study, carried out in Bolu Regional Forest Directorate (RFD), the windthrow areas between 2017 and 2019 were detected by using the Normalized Difference Fraction Index (NDFI) from the Sentinel-2A satellite image of Google Earth Engine Platform (GEE). The MaxEnt method was used to ascertain the relationship between windthrow damage and environmental variables. Wind speed, stand type (pure/mixed), precipitation, texture, distance to road, elevation, root types, slope (degree), and site index were used as environmental variables in the modeling. The value of the area under the curve (AUC) of the model was determined to be 0.821. According to the modeling results, the environmental variables that have the greatest impact on windthrow damage are site index and wind speed. In areas with a site index of '1' and wind speeds between 35-42 km/h and 53-65 km/h, it has been determined that there is an increased risk of windthrow. This study will enable forest managers to make ecological assessments to reduce the occurrence of windthrow. As a result of ecological assessments, it is anticipated that improvements in forest management planning will lead to a reduction in disturbances caused by windthrow.