Bayesian Spatio-temporal analysis of wildfires occurrence
Channel: CIMA UAdeC
Date: 2023-02-14

Conferencia "Bayesian Spatio-temporal analysis of wildfires occurrence" impartida por el Dr. Bartolo de Jesús Villar Hernández, profesor-investigador de la Universidad Autónoma de Chapingo, el día Jueves, 22 de septiembre de 2022, a las 18:00 horas (GMT-5).

Modalidad: Virtual

Resumen:
In this study we modelled and analyzed hotspots events recorded by MODIS satellite during the last nineteen years in the Mexican state of Oaxaca using a hierarchical Poisson Bayesian model. Our approach models the number of forest fires in space, in time and the interaction of both, as well as consider environmental variables. According to our results, some environmental variables can explain some of the observed spatio-temporal variations, such as temperature of the driest quarter, average wind speed, enhanced vegetation index values, and the occurrence of El Niño-Southern Oscillation. From the analysis two spatial clusters regions were identified: the first one cover the Sierra Juárez up to the Isthmus of Tehuantepec, the second one cover the Sierra del Sur. Additionally, the temporal term in our model suggest that the numbers of events have increased approximately 42.2% in the last two decades. As conclusion, our results prompt that the forest fires were increased not only spatially but also in temporarily. These findings are alarm signals because if the trend continues, in the next decades hundreds of new hectares of forest and its biodiversity be threatened, affecting too economical activities and people’s health living in rural and urban areas of Oaxaca.  This study can be a primary analysis in the design of more efficient fire management programs to mitigate the impacts of altered fire regimes in Oaxaca