Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest

DİNDAROĞLU T., Babur E., YAKUPOĞLU T., Rodrigo-Comino J., Cerda A.

Fire Safety Journal, vol.122, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 122
  • Publication Date: 2021
  • Doi Number: 10.1016/j.firesaf.2021.103318
  • Journal Name: Fire Safety Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Computer & Applied Sciences, Environment Index, ICONDA Bibliographic, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Assessment, Morphometry, Sentinel MSI, Soil, Wildfire
  • Yozgat Bozok University Affiliated: Yes


© 2021 Elsevier LtdUnderstanding 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.