Fuzzy Inference System For Mapping Forest Fire Susceptibility In Northern Rondônia, Brazil

Q2 Agricultural and Biological Sciences Geography, Environment, Sustainability Pub Date : 2024-04-03 DOI:10.24057/2071-9388-2023-2910
Miqueias Lima Duarte, Tatiana Acácio da Silva, Jocy Ana Paixão de Sousa, Amazonino Lemos de Castro, R. W. Lourenço
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Abstract

Forest fires are global phenomena that pose an accelerating threat to ecosystems, affect the population life quality and contribute to climate change. The mapping of fire susceptibility provides proper direction for mitigating measures for these events. However, predicting their occurrence and scope is complicated since many of their causes are related to human practices and climatological variations.  To predict fire occurrences, this study applies a fuzzy inference system methodology implemented in R software and using triangular and trapezoidal functions that comprise four input parameters (temperature, rainfall, distance from highways, and land use and occupation) obtained from remote sensing data and processed through GIS environment. The fuzzy system classified 63.27% of the study area as having high and very high fire susceptibility. The high density of fire occurrences in these classes shows the high precision of the proposed model, which was confirmed by the area under the curve (AUC) value of 0.879. The application of the fuzzy system using two extreme climate events (rainy summer and dry summer) showed that the model is highly responsive to temperature and rainfall variations, which was verified by the sensitivity analysis. The results obtained with the system can assist in decision-making for appropriate firefighting actions in the region.
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模糊推理系统用于绘制巴西朗多尼亚北部的森林火灾易感性地图
森林火灾是一种全球性现象,对生态系统构成日益严重的威胁,影响人们的生活质量,并导致气候变化。绘制火灾易发区地图可为采取缓解措施提供正确方向。然而,预测火灾的发生和范围非常复杂,因为许多原因都与人类活动和气候变异有关。 为了预测火灾发生率,本研究采用了一种模糊推理系统方法,该方法由 R 软件实现,使用三角函数和梯形函数,包含四个输入参数(温度、降雨量、与高速公路的距离、土地利用和占用),这些参数从遥感数据中获取,并通过地理信息系统环境进行处理。模糊系统将 63.27% 的研究区域划分为高火灾易发区和极高火灾易发区。这些类别中火灾发生的高密度显示了所建议模型的高精确度,曲线下面积(AUC)值 0.879 证实了这一点。利用两个极端气候事件(夏季多雨和夏季干燥)对模糊系统进行的应用表明,该模型对温度和降雨量的变化反应灵敏,这一点在灵敏度分析中得到了验证。该系统得出的结果有助于该地区采取适当的消防行动。
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来源期刊
Geography, Environment, Sustainability
Geography, Environment, Sustainability Social Sciences-Geography, Planning and Development
CiteScore
2.50
自引率
0.00%
发文量
37
审稿时长
12 weeks
期刊介绍: Journal “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” is founded by the Faculty of Geography of Lomonosov Moscow State University, The Russian Geographical Society and by the Institute of Geography of RAS. It is the official journal of Russian Geographical Society, and a fully open access journal. Journal “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” publishes original, innovative, interdisciplinary and timely research letter articles and concise reviews on studies of the Earth and its environment scientific field. This goal covers a broad spectrum of scientific research areas (physical-, social-, economic-, cultural geography, environmental sciences and sustainable development) and also considers contemporary and widely used research methods, such as geoinformatics, cartography, remote sensing (including from space), geophysics, geochemistry, etc. “GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY” is the only original English-language journal in the field of geography and environmental sciences published in Russia. It is supposed to be an outlet from the Russian-speaking countries to Europe and an inlet from Europe to the Russian-speaking countries regarding environmental and Earth sciences, geography and sustainability. The main sections of the journal are the theory of geography and ecology, the theory of sustainable development, use of natural resources, natural resources assessment, global and regional changes of environment and climate, social-economical geography, ecological regional planning, sustainable regional development, applied aspects of geography and ecology, geoinformatics and ecological cartography, ecological problems of oil and gas sector, nature conservations, health and environment, and education for sustainable development. Articles are freely available to both subscribers and the wider public with permitted reuse.
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