Wildfire detection and mapping by satellite with an enhanced configuration of the Normalized Hotspot Indices: results from Sentinel-2 and Landsat 8/9 data integration

The Operational Land Imager (OLI) and the Multispectral Instrument (MSI), respectively, aboard Landsat-8/9 (L8/9) and Sentinel-2 (S2) satellites, by providing data in near infrared (NIR) and short-wave infrared (SWIR) bands, with a mid-high spatial resolution (20/30 m), enable the identification, mapping, and characterization of high-temperature features. Here, we exploit this potential by presenting and testing the normalized hotspot indices algorithm tailored to fire mapping (NHI-F). Results were achieved by investigating the devastating fire events occurring in California and Hawaii islands (USA), Yellowknife (Canada), Tenerife islands (Spain), North Attica (Greece), and Northern Territory (Australia), during the intense fire seasons of 2023, show the high performance of the NHI-F in detecting and mapping wildfires, despite multispectral misregistration and striping effects affecting S2-MSI imagery. These effects may be directly minimized from the used indices, as demonstrated in this work. By investigating the wildfires of Yellowknife and California by means of L8/9 OLI/OLI2 data, we found that the NHI-F flagged up to 99% of fire pixels detected by the operational Landsat Fire and Thermal Anomaly (LFTA) product. Moreover, the additional fire pixels from NHI-F (up to 70% in night-time conditions) better detailed the fire fronts and provided unique information also about some small-fire outbreaks. The analysis of fire dynamics, performed integrating L8/9 (nighttime/daytime) and S2 (daytime) observations, demonstrates that the NHI-F configuration may highly support the fire monitoring activities at different spatial scales, complementing information from systems using satellite data at high-temporal/low spatial resolution.