Gis and fuzzy logic applied to modelling forest fire risk

Abstract

Fire risk mapping is a basic planning and protection element. This study presents the application of fuzzy logic in a geographic information system (GIS) as an alternative multi-criteria analysis for determining the areas of highest risk of forest fi re in natural forest remnants in the Brazil. In the decision-making process, a set of factors that are relevant to fi re safety were identifi ed in the study area. For each input variable chosen for the model, a pertinence function was defi ned that best described its infl uence on fi re risk. Subsequently, the variables were combined for the presentation of the fi nal fi re risk map. Concluded in the study that an increased risk of fi re occurs at the wildland -urban interface. A strong relationship was observed between the fi re ignition points and proximity to roads and urban areas. The proposed model was effi cient to integrate the variables and determine areas of greatest risk.

Fuzzy Logic Approach for Earthquake Risk Around Menanga Fault, Lampung

“…The output generated from the fuzzy overlay analysis is the degree of fuzzy membership which the value ranging from 0 to 1 [13]. The rank number which closer to 1 means the higher degree of risk, on the contrary the number which closer to 0 means the lower risk.…”

“…Fuzzy logic considers the promising approach for disaster risk modeling with its algorithm that could help to model the uncertainties and ambiguities. Previous research have applied the fuzzy logic model in different kind of hazards [12][13][14][15]. This research aims to applied Geographic Information System (GIS) with fuzzy logic overlay and Analytical Hierarchy Process (AHP) method to assess the disaster risk related to earthquake near Menanga Fault, Pesawaran area.…”

Avaliação espaço-temporal de focos de calor no sudoeste do estado de Goiás, Brasil

“…A classe AVE apesar de possuir comunidade de flora com várias espécies do cerrado brasileiro é menos susceptível a incêndios, a maior parte de suas áreas é formada por florestas nativas e florestas plantadas (eucalipto), ambas com sua base foliar em altitude maior (Juvanhol et al, 2021). Além disso, em comparação com o cerrado strictu sensu, que possui vasta ocupação por espécies de gramíneas com alta inflamabilidade, o cerradão em decorrência do sombreamento e do baixo espaçamento entre espécies não apresenta a mesma capacidade de combustão (Catry et al, 2010;Araújo et al, 2017).…”

A Multicriteria Geographic Information System Analysis of Wildfire Susceptibility in the Andean Region: A Case Study in Ibarra, Ecuador

“…However, they are costly and often inaccurate due to the human and economic resources required for their development [36]. The use of Geographic Information Systems (GISs) and remote sensing for the development of susceptibility mapping offers a more cost-effective solution than in situ methodologies and provides decision makers with precise information [11,28,37,38]. Consequently, this type of risk can be analyzed across large land areas using georeferenced information on the climatic, topographic, and biophysical variables involved in risk construction.…”

“…Given the vulnerability of forest ecosystems to fire, GIS-MCDA methods not only generate information adapted to user-specific needs but also produce data that decision makers can easily comprehend. Various examples of MCDA methods can be found in the literature, such as the analytic hierarchy process (AHP) [35,40,[42][43][44], the fuzzy AHP [45][46][47], the analytic network process [37,48], fuzzy logic [38], and artificial neural networks [39,49]. This study aims to address the existing knowledge gap concerning the threat that wildfires pose to Andean ecosystems.…”