Understanding spatiotemporal geomorphological and pedological changes as a consequence of wildfires can allow stakeholders, land planners, and policymakers to design efficient fire safety-based afforestation and restoration programs of forest lands. The use of remote sensing techniques is a key tool to achieve this goal. The suitable combination of Sentinel-2 MSI data for mapping of different spectral indices related to burn severity and their relationship with other morphometric and soil properties can contribute to a better understanding of the impact of fire, and this is relevant in regions where is still scarce fire-related research such as Turkey. In this investigation, the use of NDVI (Normalized Difference Vegetation Index), dNDVI (Difference Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), NBR (Normalized Burn Ratio), dNBR (Difference Normalized Burn Ratio), RBR (Relativized Burn Ratio), SBI (Soil Bare Index), As (Upslope area), CTI (Compound Topographic Index), TCI (Terrain Characterization Index), SPI (Stream Power Index) and Curvature (Standard Curvature) were combined. As a study case, 47.43 ha in a burned area of Çınarpınar forest unit, Andırın, Kahramanmaraş in Turkey was selected. The results showed that dNDVI, dNBR, RBR, SBI contribute to relevant information about the effect of the wildfire. According to the dNBR fire severity classification, 75% of the total area has been exposed to high-severity fire. The relationship of Sentinel MSI satellite images with some soil and morphometric features have been found meaningful to understand the impact of forest fire in Mediterranean ecosystems. The information collected in the Turkish forest areas affected by wildfires should be relevant for planning and represent a key contribution to the selection of restoration programs and afforestation techniques for a future fire-safe forest.

了解野火造成的时空地貌和生态变化，可以使利益相关者，土地规划人员和政策制定者设计出有效的基于火灾安全的林地造林和恢复计划。遥感技术的使用是实现这一目标的关键工具。Sentinel-2 MSI数据的适当组合可用于绘制与燃烧严重性相关的不同光谱指数以及它们与其他形态计量学和土壤特性的关系，这可以有助于更好地了解火的影响，这在仍然稀缺的地区很重要与火有关的研究，例如土耳其。在这项调查中，使用NDVI（归一化植被指数），dNDVI（归一化植被指数），NDWI（归一化水分指数），NBR（归一化燃烧比），dNBR（差异归一化燃烧比），RBR（相对燃烧比），SBI（土壤裸露指数），As（上坡面积），CTI（复合形貌指数），TCI（地形特征指数），SPI （流功率指数）和曲率（标准曲率）组合在一起。作为研究案例，选择了土耳其Kahramanmaraş的Cınarpınar森林单位Andırın的烧毁面积47.43公顷。结果表明，dNDVI，dNBR，RBR，SBI有助于了解有关野火影响的相关信息。根据dNBR火灾严重性分类，总面积的75％已暴露于高强度火灾。已发现Sentinel MSI卫星图像与某些土壤和形态特征之间的关系对于理解森林火灾对地中海生态系统的影响是有意义的。