An Emotion Detection GIS-Based Framework for Evaluating Exposure to Heatwave Scenarios in Urban Settlements During a Pandemic - Barbara Cardone; Ferdinando Di Martino; Cristiano Mauriello; Vittorio Miraglia (Applied Sciences)
The study of impacts on and risks to citizens generated by climatic or environmental phenomena in urban settlements is made complex by the coexistence of events that can affect the risk assessment. In this work, a model for the assessment of impacts on and risks to the population generated by heatwaves in urban settlements in the presence of pandemic periods is proposed. The presence of epidemics is treated as a stressor that contributes to altering exposure. To assess the prevalence of this stressor, a fuzzy-based emotion detection method is utilized, which uses the FREDoC framework to categorize the subzones that comprise the urban study area according to the relevance of the pleasant and unpleasant emotions of the citizens, identified based on the examination of posts that have been published on social networks. The proposed model was tested on the urban area of study of the city of Naples in Italy, taking into consideration a heatwave scenario that occurred in the summer of 2021 during the COVID-19 pandemic and analyzing the variation in exposure in the thirty districts into which the city is partitioned. The findings demonstrate that the model can accurately represent the range of impacts and hazards associated with the heatwave brought on by the COVID-19 pandemic.