Rapid Mapping: an Approach to the Main Variables in Flood Disasters and Conceptual Modeling of Situational Awareness

Abstract

Brazil is one of the main countries in the world regarding impacts caused by floods. Thus, managing this type of disaster is of paramount importance so that impacts, such as loss of life and socioeconomic damage, can be mitigated. The present work aims, therefore, to present an approach for extracting the main variables concerning flood disasters and also to present the UML (Unified Modeling Language) conceptual modeling of situational awareness in order to direct cartographic production, speeding up its supply, and thus assisting, in the timely action of the teams in dealing with these disasters. For this, a questionnaire was conducted and applied to civil defense technicians in the states of Rio de Janeiro and Santa Catarina. Forty-six variables were listed, extracted from exploratory interviews with technicians from the aforementioned public agencies, from academic literature, through scientific articles, and from reports of Brazilian Army training operations. The Likert scale was then adopted for the questionnaire and, based on the results obtained, a parametric analysis was performed using Student's T distribution. Based on this analysis, it was possible to separate the 19 most important variables among the 46. Then, the variables were separated into the levels of situational awareness and subsequent conceptual modeling, so that geoinformation producers can act in a better directed way in support to face flood disasters, in order to support decision makers with timely cartographic supply.