Many cities have unplanned areas with irregular occupation, mainly by the poorest parts of the population, who are pushed to live in high-risk areas without public services and subject to the impacts of extreme events. In this paper, emergency calls, reflecting exposed human population behavior, accessibility, and public awareness, are used, along with machine learning, to indicate the seriousness of the situation and the need for abatement measures by the municipal administration.