(untitled) (Research, Society and Development, 2022)
In order to generate a kernel density map and relate these with the CHIRPS precipitation data, in order to understand the space-time dynamics of hotspots and their relationship with precipitation in the municipality of Santarém in the state of Pará, Brazil. This work used data from BDQueimadas to spatialize fire outbreaks in the city of Santarém, in the state of Pará, in the year 2020, generating a kernel density map and relating it to the CHIRPS precipitation data, in order to understand the spatiotemporal dynamics of hotspots and their relationship with precipitation. For the visualization and management of the data, the QGIS 3.10 software was used, in which the data from BDQueimadas, the Belterra Automatic Station and CHIRPS were imported, the latter being exported via Google Earth Engine and inserted as an image with information on the amount of precipitation. and also tabulated numerical data about the image information. A possible relationship between fire outbreaks and precipitation volume in the municipality of Santarém for the year 2020 was demonstrated. Noting that the eastern portion of the municipality is the most affected with low rainfall and is the one with the most fire outbreaks.