Matteo Merlo
Multitask segmentation from satellite imagery for burned area delineation and severity estimation.
Rel. Paolo Garza, Edoardo Arnaudo, Luca Barco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
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Abstract
In recent years, the frequency and intensity of natural disasters has significantly and dangerously increased in Europe and in the world due to factors such as climate change, population growth and aggressive urbanization of rural areas. Every year, hundreds of wildfires destroy millions of hectares of forest. Rapidly delineating burned areas from satellite has become a crucial task for first responders and decision makers, to enhance the preparedness, response and recover phases during such crises. The European Union and the European Space Agency are intensifying their efforts to accumulate information on natural disasters. Data about past catastrophic events are collected by Copernicus Emergency Management System (CEMS) and categorized according to the type of event.
Exploiting wildfire EMS activations, the first objective of this thesis was the generation of a large dataset focused mainly on the European soil, collecting satellite imagery from Sentinel-2
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