scholarly journals Modelagem espacial de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil

2016 ◽  
Vol 36 (85) ◽  
pp. 41 ◽  
Author(s):  
Larissa Alves Secundo White ◽  
Benjamin Leonardo Alves White ◽  
Genésio Tâmara Ribeiro
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Risk Map ◽  
Map Algebra ◽  
Analytic Hierarchy ◽  
Land Occupation ◽  
Forest Protection ◽  
Burned Areas ◽  
Hierarchy Process ◽  
Forest Fire Risk

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

scholarly journals Forest Fire Risk Assessment using Fuzzy Analytic Hierarchy Process

2018 ◽  
Vol 13 (3) ◽  
pp. 307-316 ◽  
Author(s):  
DIVYA MEHTA ◽  
PARMINDER KAUR BAWEJA ◽  
R K AGGARWAL
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
High Risk ◽  
Analytic Hierarchy Process ◽  
Forest Fire ◽  
Fire Risk ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Forest Fire Risk

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.

scholarly journals A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role

2019 ◽  
Vol 11 (24) ◽  
pp. 7166 ◽  
Author(s):  
Gianluigi Busico ◽  
Elisabetta Giuditta ◽  
Nerantzis Kazakis ◽  
Nicolò Colombani
Keyword(s):  
Forest Fire ◽  
Anthropogenic Activities ◽  
Fire Risk ◽  
Volcanic Eruptions ◽  
Evaluation Methodology ◽  
Climate Projections ◽  
Analytic Hierarchy ◽  
Campania Region ◽  
Forest Fire Risk ◽  
Forest Wildfires

Forest wildfires usually occur due to natural processes such as lightning and volcanic eruptions, but at the same time they are also an effect of uncontrolled and illegal anthropogenic activities. Different factors can influence forest wildfires, like the type of vegetation, morphology, climate, and proximity to human activities. A precise evaluation of forest fire issues and of the countermeasures needed to limit their impact could be satisfactory especially when forest fire risk (FFR) mapping is available. Here, we proposed an FFR evaluation methodology based on Geographic Information System (GIS) and the analytic hierarchy process (AHP). The study area is the Campania region (Southern Italy) that, for the last 30 years, has been affected by numerous wildfires. The proposed methodology analyzed 12 factors, and AHP was used for weight assignment, offering a new approach to some parameters. The method divided the study area into five risk classes, from very low to very high. Validation with fire alerts showed a good correlation between observed and predicted fires (0.79 R2). Analyzing the climate projections, a future FFR for 2040 was also assessed. The proposed methodology represents a reliable screening tool to identify areas under forest fire risk, and can help authorities to direct preventive actions.

scholarly journals Forest fire risk mapping using analytical hierarchy process (AHP) and earth observation datasets: a case study in the mountainous terrain of Northeast India

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Ridalin Lamat ◽  
Mukesh Kumar ◽  
Arnab Kundu ◽  
Deepak Lal
Keyword(s):  
High Risk ◽  
Forest Fire ◽  
Analytical Hierarchy Process ◽  
Fire Risk ◽  
Control Measures ◽  
Fire Control ◽  
Risk Zones ◽  
Hierarchy Process ◽  
Forest Fire Risk ◽  
Very High

AbstractThis study presents a geospatial approach in conjunction with a multi-criteria decision-making (MCDM) tool for mapping forest fire risk zones in the district of Ri-Bhoi, Meghalaya, India which is very rich in biodiversity. Analytical hierarchy process (AHP)-based pair-wise comparison matrix was constructed to compare the selected parameters against each other based on their impact/influence (equal, moderate, strong, very strong, and extremely strong) on a forest fire. The final output delineated fire risk zones in the study area in four categories that include very high-risk, high-risk, moderate-risk, and low-risk zones. The delineated fire risk zones were found to be in close agreement with actual fire points obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) fire data for the study area. Results indicated that Ri-Bhoi’s 804.31 sq. km. (32.86%) the area was under ‘very high’ fire susceptibility. This was followed by 583.10 sq. km. (23.82%), 670.47 sq. km. (27.39%), and 390.12 sq. km. (15.93%) the area under high, moderate, and low fire risk categories, respectively. These results can be used effectively to plan fire control measures in advance and the methodology suggested in this study can be adopted in other areas too for delineating potential fire risk zones.

scholarly journals PRIORITIZATION OF FOREST FIRE HAZARD RISK SIMULATION USING HYBRID GREY RELATIVITY ANALYSIS (HGRA) AND FUZZY ANALYTICAL HIERARCHY PROCESS (FAHP) COUPLED WITH MULTICRITERIA DECISION ANALYSIS (MCDA) TECHNIQUES – A COMPARATIVE STUDY ANALYSIS

2021 ◽  
Vol 47 (3) ◽  
pp. 147-161
Author(s):  
Michael Stanley Peprah ◽  
Bernard Kumi-Boateng ◽  
Edwin Kojo Larbi
Keyword(s):  
Forest Fire ◽  
Risk Model ◽  
Fire Risk ◽  
Fuzzy Analytical Hierarchy Process ◽  
Weighted Overlay ◽  
Causative Factors ◽  
Major Criterion ◽  
Gis Environment ◽  
Hierarchy Process ◽  
Forest Fire Risk

Forests are important dynamic systems which are widely attracted by wild fires worldwide. Due to the complexity and non-linearity of the causative forest fire problems, employing sophisticated hybrid evolutionary algorithms is a logical task to achieve a reliable approximation of this environmental threats. This estimate will provide the outline of priority areas for preventing activities and allocation of fire fighters’ stations, seeking to minimize possible damages caused by fires. This study aims at prioritizing the forest fire risk of Wassa West district of Ghana. The study considered static causative factors such as Land use and land cover (which include forest, built-ups and settlement areas), slope, aspect, linear features (water bodies and roads) and dynamic causative factors such as wind speed, precipitation, and temperature were used. The methods employed include a Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) techniques. The fuzzy sets integrated with AHP in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. FAHP and HGRA methods were used for estimating the importance (weights) of the effective factors in forest fire modelling. Based on their modelling methods, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas were analyzed based on FAHP and HGRA. The major criteria models and fire risk model were presented based on these FAHP and HGRA weights. On the other hand, the spatial data of the sub criteria were provided and assembled in GIS environment to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risks of its classes to fire occurrence. The maps of each major criterion were obtained by weighted overlay of its sub criteria maps considering to major criterion model in GIS environment. Finally, the map of fire risk was obtained by weighted overlay of major criteria maps considering to fire risk model in GIS. The results showed that the FAHP model showed superiority than HGRA in prioritizing forest fire risk of the study area in terms of statistical analysis with a standard deviation of 0.09277 m as compared to 0.1122 m respectively. The obtained fire risk map can be used as a decision support system for predicting of the future trends in the study area. The optimized structures of the proposed models could serve as a good alternative to traditional forest predictive models, and this can be a promisingly testament used for future planning and decision making in the proposed areas.

scholarly journals GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing

2021 ◽  
Vol 13 (18) ◽  
pp. 3704
Author(s):  
Pengcheng Zhao ◽  
Fuquan Zhang ◽  
Haifeng Lin ◽  
Shuwen Xu
Keyword(s):  
High Risk ◽  
Forest Fire ◽  
Risk Model ◽  
Fire Risk ◽  
Low Risk ◽  
Assessment Model ◽  
National Forest ◽  
Risk Map ◽  
Forest Park ◽  
Forest Fire Risk

Fire risk prediction is significant for fire prevention and fire resource allocation. Fire risk maps are effective methods for quantifying regional fire risk. Laoshan National Forest Park has many precious natural resources and tourist attractions, but there is no fire risk assessment model. This paper aims to construct the forest fire risk map for Nanjing Laoshan National Forest Park. The forest fire risk model is constructed by factors (altitude, aspect, topographic wetness index, slope, distance to roads and populated areas, normalized difference vegetation index, and temperature) which have a great influence on the probability of inducing fire in Laoshan. Since the importance of factors in different study areas is inconsistent, it is necessary to calculate the significance of each factor of Laoshan. After the significance calculation is completed, the fire risk model of Laoshan can be obtained. Then, the fire risk map can be plotted based on the model. This fire risk map can clarify the fire risk level of each part of the study area, with 16.97% extremely low risk, 48.32% low risk, 17.35% moderate risk, 12.74% high risk and 4.62% extremely high risk, and it is compared with the data of MODIS fire anomaly point. The result shows that the accuracy of the risk map is 76.65%.

scholarly journals MAPEAMENTO DE RISCO DE DESASTRE POR INCÊNDIO FLORESTAL NA AMAZÔNIA: uma abordagem multifatorial no município de Moju (PA)

2020 ◽  
Vol 5 (19) ◽  
pp. 202009
Author(s):  
Tarsis Esaú Gomes Almeida ◽  
Maria do Socorro Almeida Flores ◽  
Mário Vasconcellos Sobrinho
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Disaster Risk ◽  
Risk Map ◽  
Economic Activities ◽  
Socioeconomic Aspects ◽  
Fire Disaster ◽  
Risk Maps ◽  
Forest Fire Risk

MAPPING DISASTER RISK BY FOREST FIRE IN THE AMAZON: a multifactorial approach in the municipality of Moju (PA)MAPEO DEL RIESGO DE DESASTRE POR INCENDIO FLORESTAL EN LA AMAZONÍA: un enfoque multifactorial en el municipio de Moju (PA)RESUMONo estado do Pará o município de Moju é um dos que apresentam a maior quantidade de focos de calor conforme dados oficiais. Note-se que a base de suas atividades econômicas são a agricultura familiar e as plantações de dendê e coco-da-baía, diante disso propôs-se questionar sobre o risco não apenas da existência de incêndios florestais, mas da magnitude das consequências socioeconômicas deles. A pesquisa bibliográfica e documental em artigos acadêmicos e científicos, dissertações e teses possibilitou a compreensão do significado de mapeamento de áreas de risco de incêndio florestal identificadas no mapa de risco, bem como a possibilidade de desenvolver com base teórica e metodológica a criação de um mapeamento e ponderação de aspectos socioeconômicos expressado no mapa de vulnerabilidade, a fim de refinar um produto final na elaboração do mapa de risco de desastre. Assim, objetivo deste artigo é mostrar e discutir a incorporação de fatores sociais e econômicos na formulação dos mapas de risco de incêndio florestal. Mais precisamente, um Mapa de Risco de Desastre por Incêndio Florestal (MRDIF), que consiste na fusão entre Mapas de Risco de Incêndio Florestal e um Mapa Avaliativo Socioeconômico. Como resultado imediato da formação do MRDIF é o planejamento de ações preventivas. Percebeu-se que houve variação nas áreas de risco dos mapas com e sem a inclusão dos aspectos socioeconômicos, o que pode indicar quais sejam as áreas principais para ações a fim de diminuir os riscos ou as consequências dos possíveis desastres causados por incêndios florestais. Palavras-chave: Gestão de Risco; Incêndios Florestais; Uso do Solo na Amazônia; Cartografia.ABSTRACTIn the state of Pará, the municipality of Moju is one of those with the highest number of hot spots according to official data. It should be noted that the basis of its economic activities are family farming and oil palm and coconut plantations. In view of this, it was proposed to ask about the risk not only of the existence of forest fires, but of the magnitude of their socioeconomic consequences. Bibliographic and documentary research in academic and scientific articles, dissertations and theses made it possible to understand the meaning of mapping areas of forest fire risk identified in the risk map, as well as the possibility of developing a mapping with theoretical and methodological basis. and weighting of socioeconomic aspects expressed in the Vulnerability Map, in order to refine a final product in the preparation of the disaster risk map. Thus, the objective of this article is to show and discuss the incorporation of social and economic factors in the formulation of forest fire risk maps. More precisely, a Forest Fire Disaster Risk Map (FFDRP), which consists of the merger between Forest Fire Risk Maps and a Socioeconomic Assessment Map. As an immediate result of the formation of FFDRP is the planning of preventive actions. It was noticed that there was variation in the risk areas of the maps with and without the inclusion of socioeconomic aspects, which may indicate what are the main areas for actions in order to reduce the risks or the consequences of possible disasters caused by forest fires.Keywords: Risk Management; Fire Forest; Land Use in the Amazon; Cartography.RESUMENEn el estado de Pará, el municipio de Moju es una de las regiones con el mayor número de focos de calor según datos oficiales. Cabe señalar que la base de sus actividades económicas son la agricultura familiar y las plantaciones de palma aceitera y coco, en vista de esto, se propuso preguntar sobre el riesgo no solo de la existencia de incendios forestales, sino de la magnitud de sus consecuencias socioeconómicas. La investigación bibliográfica y documental en artículos académicos y científicos, disertaciones y tesis permitió comprender el significado de las áreas de mapeo de riesgo de incendio forestal identificadas en el mapa de riesgo, así como la posibilidad de desarrollar un mapeo con base teórica y metodológica. y ponderación de los aspectos socioeconómicos expresados en el mapa de vulnerabilidad, con el fin de refinar un producto final en la preparación del mapa de riesgo de desastres. Por lo tanto, el objetivo de este artículo es mostrar y discutir la incorporación de factores sociales y económicos en la formulación de mapas de riesgo de incendios forestales. Más precisamente, un Mapa de Riesgo de Desastres por Incendios Forestales (MRDIF), que consiste en la fusión entre Mapas de riesgo de incendios forestales y un Mapa de evaluación socioeconómica. Como resultado inmediato de la formación de MRDIF es la planificación de acciones preventivas. Se observó que hubo variación en las áreas de riesgo de los mapas con y sin la inclusión de aspectos socioeconómicos, lo que puede indicar cuáles son las principales áreas de acción para reducir los riesgos o las consecuencias de posibles desastres causados por incendios forestales.Palabras clave: Gestión de Riesgos; Incendios Florestales; Uso del Suelo en la Amazonia; Cartografía.

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