Determination of forest fire risk with fuzzy analytic hierarchy process and its mapping with the application of GIS: The case of Turkey/Çakırlar

Author(s):  
Cumhur Güngöroğlu
2018 ◽  
Vol 13 (3) ◽  
pp. 307-316 ◽  
Author(s):  
DIVYA MEHTA ◽  
PARMINDER KAUR BAWEJA ◽  
R K AGGARWAL

Forest fires in the mid hills of Himachal Pradesh are mostly related to human activities. More than 90% of fires are originated from either deliberate or involuntary causes. The purpose of study is linked to identification of forest fire risk factors in 19 villages under Nauni and Oachhghat Panchayats. The methodology paradigm applied here is based on knowledge and fuzzy analytic hierarchy process (FAHP) techniques. Knowledge-based criteria involve socio-economic and biophysical themes for risk assessment. The risk factors are identified according to past occurrence of fire. Fuel type scores highest weight (0.3109) followed by aspect (0.2487), agricultural workers (0.1865), nutritional density (0.1244), population density (0.0622), elevation (0.0311), literacy rate (0.0207) and distance from road (0.0155) in descending order. In the study area applying FAHP, 24.96% of total area was classified under high-risk prone area, 21.69% area classified under high-risk, 34.63% area under moderate risk, while 18.61% area under low risk. The results were in accordance with actual fire occurrences in the past years.


2016 ◽  
Vol 36 (85) ◽  
pp. 41 ◽  
Author(s):  
Larissa Alves Secundo White ◽  
Benjamin Leonardo Alves White ◽  
Genésio Tâmara Ribeiro

A modelagem do risco espacial de incêndios florestais tem o objetivo de determinar as regiões mais susceptíveis ao fogo, baseando-se em variáveis que representam a facilidade de ignição e de propagação do fogo. Nesse contexto, utilizando-se das variáveis: sistema viário, densidade demográfica, uso e ocupação do solo, malha hidrográfica, inclinação e orientação das encostas, foram elaborados mapas de riscos preliminares, que, posteriormente à ponderações das mesmas pelo método AHP, foram integradas por meio da calculadora Raster em um mapa final de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil. Com base no modelo utilizado, 75,46% da área de estudo apresenta-se classificada como de maior risco, representado pelas classes “alto”, “muito alto” e “extremo”. Ao comparar o mapa final do risco de incêndio florestal para a área de estudo com o histórico de áreas queimadas, verificou-se que 94,83% dos registros de incêndios florestais estão alocados nas áreas de maior risco.Spatial modeling of forest fire risk for the Municipality of Inhambupe, Bahia State, BrazilSpatial modeling of forest fire risk has the aim to determine areas most susceptible to fire based on variables that represent facility of ignition and propagation. This work developed a forest fire risk map for the Municipality of Inhambupe, Bahia State, Brazil, by elaborating thematic maps of the following variables: road system, population density, land occupation and use, watershed network, slope and aspect. These were evaluated by the analytic hierarchy process and integrated with map algebra. Based on the developed model, 75.46% of the studied area was classified as “high”, “very high” and “extreme high” fire risk. When comparing the forest fire risk map with historical data of burned areas, 95% of the fires were in these areas.Index terms: Forest protection; Fire susceptibility; Risk map


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