Derived 500 m Grid Dataset for Post-fire Vegetation Recovery Analysis of the 2022 Uljin Wildfire, South Korea

This dataset provides the derived 500 m grid-based variables used for post-fire vegetation recovery analysis of the 2022 Uljin wildfire, South Korea. It includes annual Landsat-derived dNBR values for 2022–2025, time-lagged seasonal meteorological variables, topographic variables, and forest-structure dummy variables for 1,793 analytical grid cells. The dataset supports reproducibility of the associated manuscript on driver-specific temporal shifts in post-fire vegetation recovery.本数据集包含用于韩国2022年蔚珍山火灾后植被恢复分析的衍生500米格网变量。其中涵盖2022至2025年由陆地卫星（Landsat）反演得到的差分归一化燃烧指数（dNBR）年度值、时滞季节气象变量、地形变量，以及覆盖1793个分析格网的森林结构虚拟变量。本数据集可支撑相关研究论文中关于灾后植被恢复驱动因子特异性时间变化的研究成果的可重复性。