Integrating remote sensing and site-specific data in forest planning: A multicriteria approach to prioritize forest restoration in Central Europe

Recent severe droughts and storms has led to severe disturbances in Central European forests, highlighting the urgent need for adaptive forest management strategies and restoration. Using a multi-criteria decision analysis (MCDA) approach, this study prioritizes forest restoration areas across ownership boundaries by integrating remote sensing data, climate projections, and site-specific characteristics. Key indicators of forest resilience—drought stress risk, stand-level tree species diversity, and landscape-level rarity—were assessed, revealing that approximately 18.5 % of the study area in Lüchow-Dannenberg, Germany, requires urgent restoration due to high drought stress risk, as well as low diversity and rarity. European beech and Norway spruce stands exhibit the highest projected drought stress risk, whereas Scots pine and oak stands show comparatively low drought stress risk. Pine-dominated stands exhibit the lowest diversity and landscape rarity, while beech and oak contribute significantly to biodiversity. Sensitivity analyses reveal that weighting different indicators affects restoration prioritization, emphasizing the need for context-specific adaptive management strategies that take into account site conditions (e.g., soil moisture, climate exposure) and forest type (e.g., converting pure pine stands into more diverse, mixed stands to increase resilience.