Point Process applied to fire outbreaks in São Paulo - Vinicius Crispim Tavares Monteiro; Manoel Alves de Oliveira; Ricardo Alves de Olinda; Lucas Cardoso Pereira (Socioeconomic Analytics)
This study applied spatial analysis techniques for point processes to investigate the distribution of fire outbreaks in the state of São Paulo during the months of June to September 2024. Descriptive and inferential analyses were conducted, including Ripley's K Function and the Kolmogorov-Smirnov Test, to test the hypothesis of Complete Spatial Randomness (CSR). The results indicated a spatial clustering pattern at short distances, rejecting the randomness hypothesis. Predictive models based on Poisson processes were fitted, highlighting the most vulnerable areas, particularly in the Atlantic Forest and Cerrado biomes.