## 5 Results
### Study Site 2  
UAV NDVI Burned Area Mapping  
Future applications of the methodology will be conducted reducing the high resolution used in the present study (2-cm ground resolution) by adopting a greater flight altitude (adapted depending on the morphology of the study area), to favor the number of landmarks in the scene present. This would allow a more efficient image composition for the creation of the orthophoto, reducing the peripheral data absence, and also affecting the reported case study when compared to a portion of the ground mapped fire perimeter. As witnessed by local fire fighters, the fire path was not regular nor linear, since the spreading of the flames was operated by \"scattered\" sparks. The most affected parcels, located in the center of the burned area, showed evidence of high combustion temperatures as witnessed by the melting of what was supposed to be metal tin. Similarly, in the same parcel and from there uphill, the soil underwent a partial charring, highlighting medium  
Figure 15: PRISMA scene spectral differences between high-severity areas and unburned parcels. The aim of the image is to represent the difference in extreme scenarios. Spectral signatures vary within the same observed categories.  
fire severity. From the center of the area, going towards the crest of the hill, the vegetation and soil were heavily affected. Figure 16a, representing the fire-affected vegetation via the NDVI index, reports different and variable index values, reflecting the uneven fire burning path combined with post-fire revegetation and unburned parcels. The first reason for an increased index value could be addressed to the sprouting of ferns, _Robinia_, heather, and generally grass. Secondly, the uneven fire burning path could be a consequence of the firefighter's effort, aerial water, and flame-retardant throws resulting in an irregular fire-burning path. Even if the regrowth of grass and low bushes did not cover the evidence of fire, they affected the vegetation index, covering the otherwise barren soil and increasing the image noise. From this problem arises the necessity to perform the data sampling as soon as possible after the fire. Figure 16b displays the polygon created by the fire fighters through GPS perimeter mapping, and the polygon deriving from the NDVI index discrimination drawing. Excluding the parcel that was not mapped by the drone flight, the area crafted by the VdF (fire fighters brigade) has a surface extension of 33,328 m\({}^{2}\), while the one mapped following the false-color representation of the index accounts an area of 36,744 m\({}^{2}\). Morphologically, the perimeter of the two areas was somehow similar. The greatest difference was the detail level that the NDVI index allows.  
The processing of the orthophoto resulting in a point cloud creating a 3D representation of the NDVI index (Figure 17a,b) highlighted that trees in different locations of the area have suffered different flame heights. This evidence comes from the neat division of the plant NDVI index. As an example, the 3D visualization of scorched vegetation delineated a clear difference in the index value, the lower portion of a tree that suffered the fire heat had an index amenable to dead vegetation, while the upper part of it had a healthy vegetation index value (Figure 18a).  
Figure 16: (**a**) Computed NDVI index on the area orthophoto. (**b**) Comparison of the burned area mapped via the field GPS by VdF personnel (yellow polygon), and area mapped by the drone-acquired data (blue polygon).  
Figure 17: Photoscan 3D mesh of the area with computed NDVI index. (**a**) S view; (**b**) S-W view.