Geotechnologies as decision support strategies for the identification of fire-susceptible areas in Rio de Janeiro State

Forest fires have global, regional, and local socioeconomic and environmental consequences, with negative effects on ecosystem services, air quality, population health, and other relevant aspects, emphasizing their significance in the context of the United Nations Sustainable Development Goals. The...

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Published in:Environmental monitoring and assessment Vol. 194; no. 8; p. 557
Main Authors: de Souza Camargo, Leandro, Silva, Corbiniano, Pimentel, Luiz Claudio Gomes, da Silva, Rodrigo Werner, Sobrinho, Marco Antonio Basques, Landau, Luiz
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01-08-2022
Springer Nature B.V
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Summary:Forest fires have global, regional, and local socioeconomic and environmental consequences, with negative effects on ecosystem services, air quality, population health, and other relevant aspects, emphasizing their significance in the context of the United Nations Sustainable Development Goals. The study identified areas in the Rio de Janeiro State (RJS) with varying degrees of susceptibility to fire focis using remote sensing data derived from topographic, anthropogenic, meteorological, and hydrological factors based on seasonality and integrated into geographic information systems. The analytical hierarchy process was used as a method of integration and normalized hierarchy of variables, generating susceptibility maps in the annual, summer, and winter periods in the RJS’s hydrographic regions (HR), with the application of the associated chi-square test to records of fire focis from the AQUA satellite, period 2003 to 2017, without methodological variation for data acquisition, whose susceptibility was classified as very low to very high. The results show that the years with the most fire foci in the adopted time series are 2007 and 2014, with a peak in September and a fall from October onwards. According to the susceptibility map, 9% of the RJS is highly susceptible during the annual period, with HR-IX being especially vulnerable. In the summer, 0.2% of RJS is extremely vulnerable, while 32% is highly vulnerable in the winter, with 6402 km 2 of HR-IX areas being extremely vulnerable. A statistical correlation was discovered between the chi-square test and susceptible areas. This work contributes as a decision-making tool in fire planning and emergency response, with the potential to assist control bodies (city halls, civil defense, environmental protection bodies, health systems) in the local and regional context in the assessment, analysis, and management of these phenomena.
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ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-022-10227-0