scholarly journals Engaging Palm Oil and Hot Spot Area to Mitigate Forest Fires

2020 ◽  
Vol 20 ◽  
pp. 01003
Author(s):  
Ariesta Lestari ◽  
Katriani Puspita Ayu

Forest fire is one of environmental problem happens in Central Kalimantan. The fire does not only damage the forest ecosystem and biodiversity but also threaten the health and socio-economic of local people. Forest fire in Central Kalimantan is widely known as human-made, such as the process of shifting cultivation and land clearing. The expansion of forest into palm oil plantation is often blamed as the cause of forest fire since the forest clearing involves a massive amount of fires. Therefore, this study aims to explore whether the existence of palm oil cultivation contributes to the occurrence of forest fires. We used satellite imagery of hotspot, and overlay it with the land use data to generate the fire risk zone map using geographic information system (GIS) method. Through the map, the risk of fire can be monitored in advance to help the fire authority provide the act of mitigation. The result of this study suggested that risk mapping is vital for forest fire management to mitigate the spread of forest fire. The region to be fire-prone within the palm oil cultivation is suggested to form a preventive act through active forest-fires monitoring. In sum, this study is expected to provide a map of forest fires' risk around the cultivation area, mainly palm oil plantation, and help the fire authorities as well as stakeholders to identify the risk zone for fires prevention in the future.

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.


1993 ◽  
Vol 69 (3) ◽  
pp. 290-293 ◽  
Author(s):  
Brian J. Stocks

The looming possibility of global warming raises legitimate concerns for the future of the forest resource in Canada. While evidence of a global warming trend is not conclusive at this time, governments would be wise to anticipate, and begin planning for, such an eventuality. The forest fire business is likely to be affected both early and dramatically by any trend toward warmer and drier conditions in Canada, and fire managers should be aware that the future will likely require new and innovative thinking in forest fire management. This paper summarizes research activities currently underway to assess the impact of global warming on forest fires, and speculates on future fire management problems and strategies.


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.


2004 ◽  
Vol 155 (7) ◽  
pp. 263-277 ◽  
Author(s):  
Marco Conedera ◽  
Gabriele Corti ◽  
Paolo Piccini ◽  
Daniele Ryser ◽  
Francesco Guerini ◽  
...  

The Southern Alps, in particular the Canton Ticino, is the region of Switzerland that is most affected by the phenomenon of forest fires. Therefore, the cantonal authorities are continually confronted with problems of prevention, fire fighting and mitigation of the effects of forest fires. In this article forest fire management in Canton Ticino is analyzed in historical terms, verifying in particular the impact of the methods used and the improvement of technology addressing the frequency of events and the extent of burned surfaces. In this way it has been possible to show how a few structural measures (better organization of fire fighting crews and equipment, introduction of aerial fire fighting techniques, electrification followed by construction of shelters along railway lines, etc.) have rather reduced the extent of burned surfaces, while legislative measures such as restrictions of open fires help to reduce the number of forest fires.


2021 ◽  
pp. 177-195
Author(s):  
Sk Mujibar Rahaman ◽  
Masjuda Khatun ◽  
Sanjoy Garai ◽  
Pulakesh Das ◽  
Sharad Tiwari

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.


2019 ◽  
Vol 47 (12) ◽  
pp. 2047-2060 ◽  
Author(s):  
H. Yathish ◽  
K. V. Athira ◽  
K. Preethi ◽  
U. Pruthviraj ◽  
Amba Shetty

2005 ◽  
Vol 16 (3) ◽  
pp. 169-174 ◽  
Author(s):  
Xu Dong ◽  
Dai Li-min ◽  
Shao Guo-fan ◽  
Tang Lei ◽  
Wang Hui

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