Abstract

The study aimed to analyze the spatial distribution of heat sources inside and outside the Chapada dos Guimarães National Park (PNCG) in the State of Mato Grosso. The analyzes were performed through the estimate of kernel density (KDE) and Ripley's K function from 2005 to 2014. The data related to the number of hot spots were obtained from the National Institute for Space Research (INPE) from 2005 to 2014, and the vector files were acquired from the cartographic base of the Brazilian Institute of Geography and Statistics (IBGE). In the 10 years of analysis, 579 hot spots were detected in the PNCG, where it was found that the months of August and September had the highest incidence of hot spots in the park. The kernel maps demonstrated that most hotspots were observed in the years 2007, 2010 and 2012. The years 2005 and 2013 presented average densities and the years 2006, 2008, 2009, 2011 and 2014 indicated low density of the hot spots. Ripley's K function, calculated to observe the spatial distribution of the hot spots, rejected the hypothesis of complete spatial randomness (CSR), indicating that they showed a tendency to cluster during the study time series at the PNCG.

Highlights

  • Every year forest fires cause damage to the economy and biodiversity in several regions of Brazil and the world, constituting one of the greatest threats to the preservation of biodiversity on the planet

  • A study carried out in the Chapada dos Veadeiros National Park, in Goiás, showed a lower occurrence of hot spots compared to the present study, with 184 spots inside the unit, through images from the NOAA-12 satellite, in the period from 1992 to 2003, leading to the finding of a higher incidence of hot spots in relation to the number of occurrences of fires recorded in the park during the analyzed period (FIEDLER; MERLO; MEDEIROS, 2006)

  • The detection of hot spots by remote sensing was evaluated in the Itatiaia National Park using the AQUA satellite, observing the occurrence of 26 spots, concluding that the satellite presented the best results, both in terms of the number of detections and in the proximity of the spots in relation to the affected area (TOMZHINSKI; COURA; FERNANDES, 2011)

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Summary

Introduction

Every year forest fires cause damage to the economy and biodiversity in several regions of Brazil and the world, constituting one of the greatest threats to the preservation of biodiversity on the planet. In addition to their direct impacts on fauna and flora, they contribute indirectly to environmental degradation, making the soil more susceptible to erosive processes and releasing into the atmosphere a large amount of greenhouse gases (WHITE et al, 2013).

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