NHI aLGORITHM

The NHI (Normalized Hotspot Indices; Marchese et al., 2019) algorithm uses two normalized indices to identify thermal anomalies through Landsat-8 OLI and Sentinel-2 MSI data:

NHI_SWIR= (L_2.2-L_1.6)/(L_2.2+L_1.6)

NHI_SWNIR= (L_1.6-L_0.8)/(L_1.6+L_0.8)

where, L_2.2, L_1.6, and L_0.8 are the TOA radiaces [W⸱m^-2⸱sr^-1⸱m^-1] measured, for each pixel of the scene, at around 2.2 µm (SWIR2), 1.6 µm (SWIR1), and 0.8 µm (NIR). An initial test on SWIR2 radiance and a spectral filter, for multi-spectral misregistration issues of Sentinel-2 MSI imagery, are used before the computation of the two normalized indices to minimize false positives. Pixels having values of NHI_SWIR > 0 OR NHI_SWNIR > 0 are flagged as "hot" by the algorithm.