Spatio-temporal modelling of the Brazilian wildfires: The influence of human and meteorological variables
Conference
64th ISI World Statistics Congress - Ottawa, Canada
Format: IPS Abstract
Keywords: environment, spatial-association, statistics-based-on-data-science, time-series
Session: IPS 421 - Data Science in Statistics: methodological and applied issues
Thursday 20 July 10 a.m. - noon (Canada/Eastern)
Abstract
Wildfires are one of the most common natural disasters in many world regions and actively impact life quality. These events have become frequent with the increasing effect of climate change and other local policies and human behavior. This study considers the historical data with the geographical locations of all the ``fire spots'' detected by the reference satellites that cover the whole Brazilian territory between January 2011 and December 2020, comprising more than 1.8 million fire spots. This data was modeled with a spatial econometric model using meteorological variables (precipitation, air temperature, humidity, and wind speed) and a human variable (land-use transition and occupation) as covariates. We find that the change in land use from forest and green areas to farming has a significant positive impact on the number of fire spots for all six Brazilian biomes. (Joint work with Jonatha Pimentel and Rodrigo Bulhões)