Determination of the critical threshold for the occurrence of fires in the Parque Nacional de Brasília (Brazil) through temporal analysis using spectral índices
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Keywords

Analysis
Biome
Google Earth Engine
Fire
Monitoring

How to Cite

SILVA, L. I. da; BAPTISTA, G. M. de M. Determination of the critical threshold for the occurrence of fires in the Parque Nacional de Brasília (Brazil) through temporal analysis using spectral índices. Sociedade & Natureza, [S. l.], v. 35, n. 1, 2023. DOI: 10.14393/SN-v35-2023-67446. Disponível em: https://seer.ufu.br/index.php/sociedadenatureza/article/view/67446. Acesso em: 31 aug. 2024.

Abstract

The Brazilian Savannah is one of the largest biomes in Brazil. Unfortunately, human pressure is aggravating the degradation processes of the biome and, together with the drought processes, fire events are a major concern. Monitoring tools must be designed, especially those involving the concepts of remote sensing, in anticipation of the fire phenomenon, mitigating the devastating effects. Therefore, the present research aims to determine the critical threshold for the occurrence of fires through the diagnosis of the conditions of greenness, humidity and senescence of the vegetation using the temporal analysis of Sentinel-2 images in the Parque Nacional de Brasília. Therefore, it is necessary to quantitatively determine each condition through the analysis of past events, determining the criticality threshold that conditions the region to present conditions that favor the onset of a fire, as well as the construction of an algorithm, in the Google Earth Engine. The study area is the Parque Nacional de Brasília, with the image data collection Harmonized Sentinel-2 MSI: MultiSpectral Instrument, Level-1C inside the Google Earth Engine. The algorithm aims to build a masking system to remove materials from the scenes, as well as the calculation of the NDVI, NDII, PSRI and dNBR indices, extracting the data through the mask of burned pixels. It was possible to identify six periods of fire occurrence, the data extraction allowed the statistical determination of the threshold, which was 0,580 for the NDVI, 0,015 for the NDII and 0,150 for the PSRI.

https://doi.org/10.14393/SN-v35-2023-67446
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References

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Copyright (c) 2022 Lucas Inácio Silva, Gustavo Macedo Mello Baptista

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