Skip to main content

Advertisement

Log in

Assessing the impacts of catastrophic 2020 wildfires in the Brazilian Pantanal using MODIS data and Google Earth Engine: A case study in the world’s largest sanctuary for Jaguars

  • Research
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

The Encontro das Águas State Park (EASP), renowned as the world’s largest refuge for Jaguars (Panthera onca), is located within the Brazilian portion of the Pantanal biome, and it covers a vast area of approximately 1,080 square kilometers. This ecologically rich region suffered significant devastation from extensive fires in 2020. Given that the ongoing monitoring of wildfires is a crucial task for the preservation of fauna and flora in legally protected environments such as the Pantanal biome, this paper investigates the catastrophic 2020 fire incidents in the EASP reserve through a fully automated methodology capable of detecting and characterizing fire-devastated areas. By taking updated and accurate data from the Google Earth Engine platform, our approach integrates a comprehensive collection of MODIS sensor images, spectral indices, and filtering processes to generate a spatial map of fire-affected areas in a given period of analysis. Specifically, given a surface reflectance and atmospheric corrected MODIS (MOD09Q/A1) image series, the NBR index is computed from each image and then processed through Savitzky-Golay filtering to remove noisy and missing data. Next, the \(\Delta \)NBR index is calculated for each consecutive pair of images so as to produce a frequency map of burned areas. In order to quantify and analyze the recent changes due to these successive wildfires that took place in this Pantanal portion, we focused on the devastating fire events that occurred in the EASP park from July to September 2020. The fire mappings were assessed and statistically validated using the kappa coefficient and significance tests computed through reference samples collected from official databases and visual inspection. The findings revealed that, tragically, 84% of the study area experienced at least one instance of fire during the three-month investigation period. The high temporal resolution of MODIS sensors proves to be extremely valuable in promptly and effectively detecting changes in land use.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Code Availability

The code of the proposed framework is freely available at https://github.com/rogerionegri/firemap.

References

Download references

Funding

This research was funded by the São Paulo Research Foundation (FAPESP), grants 2016/24185-8, 2021/01305-6 and 2021/03328-3, and National Council for Scientific and Technological Development (CNPq), grants 316228/2021-4 and 305220/2022-5.

Author information

Authors and Affiliations

Authors

Contributions

Larissa M. P. Parra, Fabrícia C. Santos, Rogeério G. Negri, Adriano Bressane and Wallace Casaca wrote the main manuscript text; Rogério G. Negri implemented the codes; Larissa M. P. Parra, Fabrícia C. Santos, Rogério G. Negri, Adriano Bressane, Marilaine Colnago, Maurício A. Dias and Wallace Casaca analyzed the results. All authors reviewed the manuscript.

Corresponding author

Correspondence to Rogério G. Negri.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Additional information

Communicated by: H. Babaie.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Parra, L.M.P., Santos, F.C., Negri, R.G. et al. Assessing the impacts of catastrophic 2020 wildfires in the Brazilian Pantanal using MODIS data and Google Earth Engine: A case study in the world’s largest sanctuary for Jaguars. Earth Sci Inform 16, 3257–3267 (2023). https://doi.org/10.1007/s12145-023-01080-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-023-01080-x

Keywords

Navigation