## 5 Discussion
### Operational Services  
This research study deals with the use of S2 optical satellite data to map burned areas with no a priori knowledge about wildfire occurrence or burned area spatial distribution. The proposed methodology explores the entire multitemporal series, discovering wildfire fingerprints on vegetation cover by means of an abrupt change detection procedure. Such a novel procedure is founded on a threshold-based classification that relies on empirical observations of spectral indices time series, describing wildfire disturbance. To provide updated, detailed, and reliable information on wildfires, there is a need to integrate existing operational services (i.e., Copernicus EMS and EFFIS) with new procedures for national level mapping, exploiting the large amount of new Copernicus Sentinel data and possibly using no ancillary data but available near-real-time information. The presented methodology, based on an automatic detection procedure, should stimulate the development of operational services for mapping burned areas at the national level in support of decision support systems. There are success stories about national services delivering fire-related products and services produced from satellite data. For example, the Greek National Observatory of Forest Fires (NOFFi) makes use of S2 data to routinely provide three main products: (i) fuel type mapping, (ii) semi-automatic burned area mapping service, and (iii) a fire danger index providing mid-term predictions [64]. Concerning the Italian territory, a geographic database of burned areas in Italian National Parks for the 2001-2005 period was built using ASTER and SPOT images, processed with photo-interpretation, multiple thresholds of spectral indices (NBR and BAI), and maximum likelihood [65]. Despite the success of this pilot project, promoted by the Ministry for Environment Land and Sea Protection of Italy, the mapping activity was not taken up. Since the Italian territory is plagued by arsonists, precise knowledge about wildfire-affected regions plays a key role for the identification of areas that need to be recovered. Moreover, Italy is the European Union country facing the highest landslide hazard. In recent years, the combination of droughs, wildfires, and heavy rainfall, as a result of climate change, significantly strengthens soil erosion. In fact, deposition of fire hash and altered soil permeability could cause intense surface water flow during heavy rainfall and, together with the reduction of vegetated surface, may strengthen landslide activation. This research study used the presented procedure to successfully map wildfire events in Italy during the year 2017, comparing the performances of three different fire-related spectral indices. The procedure could also be adapted to deal with near-real-time burned area identification, since it does not use any information after the post-fire image acquisition. Further investigations are needed in order to improve the developed procedure by addressing the following issues:  
comparison of the performance using other spectral indices used for burned area identification; integration of spectral indices in order to increase the robustness of the detection;  
perform the tuning of the threshold values for the required parameters;  
identify further strategies to reduce the commission error, especially for arable lands. Besides the identification of burned areas, dense multitemporal series of optical satellite observations can be used to extract much more wildfire-related information that can rarely be measured after a wildfire takes place, information regarding, for example, the active fires and the pre-fire land cover type affected by the wildfires. Such thematic data play a major role in supporting knowledge about wildfires since they can be exploited to derive information related to fire fuel load [66] and therefore used to estimate other components of the fire regime and the amount of smoke emitted, and consequently the wildfire impact on air quality.