Analyzing forest fires in a brazilian savannah conservation unit using remote sensing and statistical methods: spatial patterns and interaction

IF 3.9 3区环境科学与生态学 Q1 ENGINEERING, CIVIL Stochastic Environmental Research and Risk Assessment Pub Date : 2024-03-22 DOI:10.1007/s00477-024-02708-0

Ronie Silva Juvanhol, Helbecy Cristino Paraná de Sousa, José Wellington Batista Lopes

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Abstract

The objective of the study was to analyze the occurrence of forest fires in a conservation unit (CU) of the Brazilian savannah using remote sensing techniques and statistical methods developed for spatial punctual processes. To conduct the spatial analysis of fires, fire polygons mapped using Landsat 8 satellite images were used. The fires were considered into size classes to better illustrate the spatial patterns. The analysis of the spatial distribution of fires utilized Ripley's K-function, in addition to the Kcross function to verify spatial interaction. The results show that the year 2015 had the highest number of fires and burned area. Smaller fires represent a greater number of occurrences, located mostly on CU boundaries. The spatial distribution of forest fires is not random and can cluster on a scale of approximately 6 km. There is a strong spatial interaction between forest fires and traditional communities, particularly with fires smaller than 100 hectares. However, these communities are not responsible for large fires. These results contribute to better-targeted forest fire prevention and combat policies, serving as management tools for the protected area.

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利用遥感和统计方法分析巴西热带稀树草原保护区的森林火灾：空间模式和相互作用

这项研究的目的是利用遥感技术和为空间定时过程开发的统计方法，分析巴西热带稀树草原一个保护单元（CU）的森林火灾发生情况。为了对火灾进行空间分析，使用了 Landsat 8 卫星图像绘制的火灾多边形。为了更好地说明空间模式，对火灾进行了大小分级。在分析火灾的空间分布时，除了使用 Kcross 函数验证空间交互作用外，还使用了 Ripley's K 函数。结果表明，2015 年的火灾数量和燃烧面积都是最高的。较小的火灾代表了较多的发生次数，主要位于中央大学边界。森林火灾的空间分布不是随机的，可以在大约 6 公里的范围内聚集。森林火灾与传统社区之间存在很强的空间互动关系，尤其是面积小于 100 公顷的火灾。不过，这些社区并不对大火负责。这些结果有助于制定更有针对性的森林火灾预防和扑救政策，作为保护区的管理工具。

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来源期刊

Stochastic Environmental Research and Risk Assessment 环境科学-工程：环境

CiteScore

7.10

自引率

9.50%

发文量

189

审稿时长

3.8 months

期刊介绍： Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.