scholarly journals Mapping Forest Fire Risk at a Local Scale—A Case Study in Andalusia (Spain)

Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 30 ◽  
Author(s):  
Ismael Vallejo-Villalta ◽  
Estefanía Rodríguez-Navas ◽  
Joaquín Márquez-Pérez
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Moisture Stress ◽  
Forest Environment ◽  
Protection Measures ◽  
Burned Areas ◽  
Fuel Models ◽  
Forest Fire Risk

Forest fires are a critical environmental problem facing current societies, with serious repercussions at ecological, economic and personal safety levels. Detailed maps enabling identification of areas liable to be affected is an indispensable first step allowing different prevention and protection measures vis-à-vis this kind of phenomenon. These maps could be especially valuable for use in land management and emergency planning at a municipality scale. A methodology is shown for producing local maps of mid- and short-term forest fire risk, integrating both natural and human factors. Among natural factors, variables normally used in hazard models are considered as fuel models, slopes or vegetation moisture stress. From the human perspective, more novel aspects have been evaluated, meant either to assess human-induced hazard (closeness to forestland of causative elements or the ability of people to penetrate the forest environment), or to assess vulnerability, considering the population’s location in urban centres and scattered settlements. The methodology is applied in a municipality of Andalusia (Spain) and obtained results were compared to burned areas maps.

Monitoring Forest Fire using Geo-Spatial Information Techniques and Spatial Statistics: One Case Study of Forest fire in Margalla Hills, Islamabad, Pakistan

2020 ◽  
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Saima Siddiqui
Keyword(s):  
Spatial Patterns ◽  
Forest Fire ◽  
Forest Fires ◽  
Human Activities ◽  
Fire Risk ◽  
Maximum Temperature ◽  
Forest Density ◽  
Burned Areas ◽  
Severity Rating

Abstract Background Understanding the spatial patterns of forest fires is of key importance for fire risk management with ecological implications. Fire occurrence, which may result from the presence of an ignition source and the conditions necessary for a fire to spread, is an essential component of fire risk assessment. Methods The aim of this research was to develop a methodology for analyzing spatial patterns of forest fire danger with a case study of tropical forest fire at Margalla Hills, Islamabad, Pakistan. A geospatial technique was applied to explore influencing factors including climate, vegetation, topography, human activities, and 299 fire locations. We investigated the spatial extent of burned areas using Landsat data and determined how these factors influenced the severity rating of fires in these forests. The importance of these factors on forest fires was analyzed and assessed using logistic and stepwise regression methods. Results The findings showed that as the number of total days since the start of fire has increased, the burned areas increased at a rate of 25.848 ha / day (R 2 = 0.98). The average quarterly mean wind speed, forest density, distance to roads and average quarterly maximum temperature were highly correlated to the daily severity rating of forest fires. Only the average quarterly maximum temperature and forest density affected the size of the burnt areas. Fire maps indicate that 22% of forests are at the high and very high level (> 0.65), 25% at the low level (0.45-0.65), and 53% at the very low level (0.25 – 0.45). Conclusion Through spatial analysis, it is found that most forest fires happened in less populated areas and at a long distance from roads, but some climatic and human activities could have influenced fire growth. Furthermore, it is demonstrated that geospatial information technique is useful for exploring forest fire and their spatial distribution.

scholarly journals MULTICRITERIA ANALYSIS FOR IDENTIFYING FOREST FIRE RISK ZONES IN THE BIOLOGICAL RESERVE OF THE SAMA CORDILLERA, BOLIVIA

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 113-118
Author(s):  
S. Mariscal ◽  
M. Ríos ◽  
F. Soria
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Risk Model ◽  
Multicriteria Analysis ◽  
Fire Risk ◽  
Temperature And Precipitation ◽  
Spatial Risk ◽  
Forest Fire Risk ◽  
Very High ◽  
Biological Reserve

Abstract. Forest fires have negative effects on biodiversity, the atmosphere and human health. The paper presents a spatial risk model as a tool to assess them. Risk areas refer to sectors prone to the spread of fire, in addition to the influence of human activity through remote sensing and multi-criteria analysis. The analysis includes information on land cover, land use, topography (aspect, slope and elevation), climate (temperature and precipitation) and socio-economic factors (proximity to settlements and roads). Weights were assigned to each in order to generate the forest fire risk map. The investigation was carried for a Biological Reserve in Bolivia because of the continuous occurrence of forest fires. Five risk categories for forest fires were derived: very high, high, moderate, low and very low. In summary, results suggest that approximately 67% of the protected area presents a moderate to very high risk; in the latter, populated areas are not dense which reduces the actual risk to the type of events analyzed.

scholarly journals Climate change and forest management affect forest fire risk in Fennoscandia

2021 ◽  
Author(s):  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Black Carbon ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
The Arctic ◽  
Large Fires ◽  
Forest Fire Risk ◽  
Fire Ignition

Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.

scholarly journals Developing a New Hourly Forest Fire Risk Index Based on Catboost in South Korea

2020 ◽  
Vol 10 (22) ◽  
pp. 8213
Author(s):  
Yoojin Kang ◽  
Eunna Jang ◽  
Jungho Im ◽  
Chungeun Kwon ◽  
Sungyong Kim
Keyword(s):  
South Korea ◽  
Forest Fire ◽  
Forest Fires ◽  
Risk Index ◽  
Fire Risk ◽  
Ensemble Model ◽  
Weather Factors ◽  
Meteorological Model ◽  
Forest Fire Risk ◽  
Fire Risk Index

Forest fires can cause enormous damage, such as deforestation and environmental pollution, even with a single occurrence. It takes a lot of effort and long time to restore areas damaged by wildfires. Therefore, it is crucial to know the forest fire risk of a region to appropriately prepare and respond to such disastrous events. The purpose of this study is to develop an hourly forest fire risk index (HFRI) with 1 km spatial resolution using accessibility, fuel, time, and weather factors based on Catboost machine learning over South Korea. HFRI was calculated through an ensemble model that combined an integrated model using all factors and a meteorological model using weather factors only. To confirm the generalized performance of the proposed model, all forest fires that occurred from 2014 to 2019 were validated using the receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) values through one-year-out cross-validation. The AUC value of HFRI ensemble model was 0.8434, higher than the meteorological model. HFRI was compared with the modified version of Fine Fuel Moisture Code (FFMC) used in the Canadian Forest Fire Danger Rating Systems and Daily Weather Index (DWI), South Korea’s current forest fire risk index. When compared to DWI and the revised FFMC, HFRI enabled a more spatially detailed and seasonally stable forest fire risk simulation. In addition, the feature contribution to the forest fire risk prediction was analyzed through the Shapley Additive exPlanations (SHAP) value of Catboost. The contributing variables were in the order of relative humidity, elevation, road density, and population density. It was confirmed that the accessibility factors played very important roles in forest fire risk modeling where most forest fires were caused by anthropogenic factors. The interaction between the variables was also examined.

scholarly journals FOREST FIRE RISK ZONING FOR THE VILA VELHA STATE PARK AND ITS SURROUNDINGS (PONTA GROSSA, PARANÁ)

FLORESTA ◽  
2020 ◽  
Vol 50 (4) ◽  
pp. 1818
Author(s):  
Bruna Kovalsyki ◽  
Alexandre França Tetto ◽  
Antonio Carlos Batista ◽  
Nilton José Sousa ◽  
Marta Regina Barrotto do Carmo ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Hazard ◽  
Fire Risk ◽  
Risk Mapping ◽  
Ignition Probability ◽  
Risk Zoning ◽  
Extreme Risk ◽  
Forest Fire Hazard ◽  
Forest Fire Risk

Forest fire hazard and risk mapping is an essential tool for planning and decision making regarding the prevention and suppression of forest fires,as well as fire management in general, as it allows the spatial visualization of areas with higher and lower ignition probability. This study aimed to develop a forest fire risk zoning map for the Vila Velha State Park and its surroundings (Ponta Grossa, Paraná State, Brazil), for the period of higher incidence of forest fires (from April to September) and for the period of lower incidence (from October to March). The following risk and hazard variables were identified: human presence, usage zones, topographical features, soil coverage and land use and meteorological conditions. Coefficients (0 to 5) reflecting the fire risk or hazard degree were allocated to each variable in order to construct the maps. The integration of these maps, through a weighting model, resulted in the final risk mapping. The very high and extreme risk classes represented about 38% of the area for both periods. The forest fire risk mapping spatially represented the levels of fire risk in the area, allowing the managers to identify the priority sectors for preventive actions in both fire seasons.

Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil

2016 ◽  
Vol 173 ◽  
pp. 65-71 ◽  
Author(s):  
Fernando Coelho Eugenio ◽  
Alexandre Rosa dos Santos ◽  
Nilton Cesar Fiedler ◽  
Guido Assunção Ribeiro ◽  
Aderbal Gomes da Silva ◽  
...  
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Espírito Santo ◽  
Espirito Santo ◽  
Forest Fire Risk

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

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