Assessing the environmental factors affecting the natural regeneration of Cedrus libani A. Rich. in Jawbat Burghal, Syria

Remote Sensing (RS) and Geographic Information Systems (GIS) technologies are valuable tools for managing forest ecosystems today. This study employed a Binary Logistic Regression Model to analyze the environmental factors influencing the natural regeneration of Cedrus libani A. Rich. within its native habitat in the Jawbat Burghal forest of Syria. The effects of various environmental factors (spatial and forest structure, topography, and spectral indicators) were assessed both individually and collectively to understand their impact on the probability of C. libani seedling presence in Jawbat Burghal. The model’s accuracy significantly improved when considering the combined effects of these factors, reaching 94.3%, exceeding the accuracy of the other models evaluated (none of which surpassed 85%). Higher stone density, increased broadleaved tree cover, and favorable summer soil moisture were found to promote the natural regeneration of C. libani in Jawbat Burghal.