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

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.

Author(s):  
S. Mariscal ◽  
M. Ríos ◽  
F. Soria

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.


2021 ◽  
Author(s):  

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.


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 ◽  
...  

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.


2022 ◽  
Author(s):  
Volkan Sevinc

Abstract Geographical information system data has been used in forest fire risk zone mapping studies commonly. However, forest fires are caused by many factors, which cannot be explained only by geographical and meteorological reasons. Human-induced factors also play an important role in occurrence of forest fires and these factors depend on various social and economic conditions. This article aims to prepare a fire risk zone map by using a data set consisting of nine human-induced factors, three natural factors, and a temperature factor causing forest fires. Moreover, an artificial intelligence method, k-means, clustering algorithm was employed in preparation of the fire risk zone map. Turkey was selected as the study area as there are social and economic varieties among its zones. Therefore, the forestry zones in Turkey were separated into three groups as low, moderate, and high-risk categories and a map was provided for these risk zones. The map reveals that the forestry zones on the west coast of Turkey are under high risk of forest fire while the moderate risk zones mostly exist in the southeastern zones. The zones located in the interior parts, in the east, and on the north coast of Turkey have comparatively lower forest fire risks.


2020 ◽  
Vol 5 (19) ◽  
pp. 202009
Author(s):  
Tarsis Esaú Gomes Almeida ◽  
Maria do Socorro Almeida Flores ◽  
Mário Vasconcellos Sobrinho

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.


2020 ◽  
Author(s):  
Burcu Calda ◽  
Kamil Collu ◽  
Aytac Pacal ◽  
Mehmet Levent Kurnaz

<p>Forest fires are naturals in the Mediterranean ecosystems. However, in the last decade, the number of wildfires has significantly increased in the Mediterranean basin along with climate change. Therefore, forecasts of this region by using fire indices are crucial to take necessary precautions. In the present study, the projected changes for the period 2070 - 2099 concerning the control period 1971 - 2000 were used to estimate forest fire risk by the Canadian Fire Weather Index (FWI). RCP4.5 and RCP8.5 emission scenarios (IPCC) outputs of MPI-ESM-MR and HadGEM2-ES dynamically downscaled to 50 km for the CORDEX-MENA domain with the use of the RegCM4 were utilized. ERA-Interim observational data from ECMWF covering the period 1980-2012 were also used to test the performances of models. The output of MPI-ESM-MR gave more similar fire risk prediction with the reforecast of observational data (ERA-Interim). Thus, the MPI-ESM-MR model could be more suitable to estimate fire risk by FWI. According to future projection, forest fire risk will significantly increase throughout the region for the last 30 years of this century.</p>


Environments ◽  
2019 ◽  
Vol 6 (3) ◽  
pp. 30 ◽  
Author(s):  
Ismael Vallejo-Villalta ◽  
Estefanía Rodríguez-Navas ◽  
Joaquín Márquez-Pérez

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.


2020 ◽  
Vol 3 (1) ◽  
pp. 30
Author(s):  
Luis Santos ◽  
Vasco Lopes ◽  
Cecília Baptista

The number of forest fires ignitions has decreased worldwide, thus observing increased levels of intensity and destruction, endangering urban areas and causing material damages and deaths (Portugal, 2017). Forest fire hazard mapping supported by the surveillance strategy targeted at very susceptible areas with high losses potential are the common tools of fire prevention. Each municipality creates its own Forest Fire Hazard Map, and so it is observed that along the administrative boundaries, discrepancies occur, even when identical types of land use are in place. The evolution of geographic information systems technology sustained by the open-source satellite imagery, along with the innovative Habitat Risk Assessment model of the InVEST software, allowed the creation of an easily applicable trans-administrative boundary fire hazard map, with frequent update capabilities and fully open source. This work considered three municipalities (Tomar, Ourém, and Ferreira do Zêzere) that annually observe various forest fire occurrences. Results enabled the creation of a homogeneous Forest Fire Risk Map, using landuse, slope, road access network, fire ignitions’ history, visualization basins, and the Normalized Difference Vegetation Index (NDVI) as variables. All variables correlate with each other using different weights, in which the different classes of land use are considered as habitats and the remaining variables as fire hazard stressors. The results produce a coherent monthly updated Risk Map, which is an alternative to many risk assessment systems used worldwide.


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