Beyond dNBR: Exploring Alternative Satellite Indices for Post-Fire Damage Assessment in Turkish Forests

Abstract

Difference Normalised Burn Ratio (dNBR) is used as a reliable reference index since it has accepted thresholds for determining fire severity. However, the use of the dNBR index is limited if pre-fire data cannot be obtained due to weather and other conditions. This situation necessitates the development of alternative indices that are calculated only with post-fire satellite imagery. This study was conducted on forest fires in Mersin, Izmir and Mugla provinces of Turkey while aiming to evaluate the effectiveness of alternative indices to the dNBR index, which is widely used in determining ecosystem damage and fire severity after forest fires. Using Sentinel-2 satellite data operated by the European Space Agency (ESA), the study analysed the performance of the NDVI, NDMI, NBR, MSAVI, EVI and BAIS2 indices calculated using only post-fire data against the dNBR index calculated from pre- and post-fire imagery. The main methods used in this study include data processing and analyses performed on the Google Earth Engine (GEE) platform and comparisons made on the QGIS platform. In this study, the extent to which these alternative indices can be effective in accurately and reliably assessing post-fire ecosystem damage was investigated. The results of the analyses showed that the NBR and BAIS2 indices have the highest accuracy in detecting post-fire ecosystem damage. While both indices produced results close to the dNBR index, MSAVI and EVI were found to be effective in monitoring vegetation changes but insufficient in determining fire severity. In conclusion, BAIS2 and NBR provide strong alternatives to dNBR in analyses based on post-fire data, while the other indices used in the study are considered as complementary tools.

Keywords

• Forest Fire
• Burn Severity
• Sentinel-2
• Google Earth Engine
• dNBR

Supporting Institution

This study was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) ARDEB 2549 (NCBR) Grant No: 122N254. The authors declare the utilization of AI-assisted technologies to enhance the readability and linguistic quality of the manuscript.

Project Number

122N254

Ethical Statement

The authors declare no conflict of interest.

Thanks

This study was supported by the Scientific and Technological Research Council of Turkey (TUBITAK) ARDEB 2549 (NCBR) Grant No: 122N254. The authors declare the utilization of AI-assisted technologies to enhance the readability and linguistic quality of the manuscript.

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