scholarly journals A Probabilistic Method Predicting Forest Fire Occurrence Combining Firebrands and the Weather-Fuel Complex in the Northern Part of the Daxinganling Region, China

Forests ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 428 ◽  
Author(s):  
Ping Sun ◽  
Yunlin Zhang
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Probabilistic Method ◽  
Fire Risk ◽  
The United States ◽  
Fire Danger ◽  
Fire Occurrence ◽  
Weather Variables ◽  
Rating Method ◽  
Actual Fire

The fire danger rating method currently used in the northern part of the Daxinganling Region with the most severe forest fires in China only uses weather variables without considering firebrands. The discrepancy between fire occurrence and fire risk by FFDWR (Forest Fire-Danger Weather Rating, a method issued by the National Meteorological Bureau, that is used to predict forest fire probability through links between forest fire occurrence and weather variables) in the northern part is more obvious than that in the southern part. Great discrepancy has emerged between fire danger predicted by the method and actual fire occurrence in recent years since a strict firebrand prohibition policy has significantly reduced firebrands in the region. A probabilistic method predicting fire probability by introducing an Ignition Component (IC) in the National Fire Danger Rating System (NFDRS) adopted in the United States to depict effects of both firebrand and weather-fuel complex on fire occurrence is developed to solve the problem. The suitability and accuracy of the new method in the region were assessed. Results show that the method is suitable in the region. IC or the modified IC can be adopted to depict the effect of the weather-fuel complex on fire occurrence and to rate fire danger for periods with fewer firebrands. Fire risk classes and corresponding preparedness level can be determined from IC in the region. Methods of the same principle could be established to diminish similar discrepancy between actual fire occurrence and fire danger in other countries.

scholarly journals Forest Fire Probability Mapping in Eastern Serbia: Logistic Regression versus Random Forest Method

Forests ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 5
Author(s):  
Slobodan Milanović ◽  
Nenad Marković ◽  
Dragan Pamučar ◽  
Ljubomir Gigović ◽  
Pavle Kostić ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Suppression ◽  
Standard Procedure ◽  
Predictive Ability ◽  
Fire Risk ◽  
Fire Season ◽  
Fire Occurrence ◽  
Probability Mapping

Forest fire risk has increased globally during the previous decades. The Mediterranean region is traditionally the most at risk in Europe, but continental countries like Serbia have experienced significant economic and ecological losses due to forest fires. To prevent damage to forests and infrastructure, alongside other societal losses, it is necessary to create an effective protection system against fire, which minimizes the harmful effects. Forest fire probability mapping, as one of the basic tools in risk management, allows the allocation of resources for fire suppression, within a fire season, from zones with a lower risk to those under higher threat. Logistic regression (LR) has been used as a standard procedure in forest fire probability mapping, but in the last decade, machine learning methods such as fandom forest (RF) have become more frequent. The main goals in this study were to (i) determine the main explanatory variables for forest fire occurrence for both models, LR and RF, and (ii) map the probability of forest fire occurrence in Eastern Serbia based on LR and RF. The most important variable was drought code, followed by different anthropogenic features depending on the type of the model. The RF models demonstrated better overall predictive ability than LR models. The map produced may increase firefighting efficiency due to the early detection of forest fire and enable resources to be allocated in the eastern part of Serbia, which covers more than one-third of the country’s area.

scholarly journals Temporal variations and change of forest fire danger in Europe in 1960–2012

2013 ◽  
Vol 1 (6) ◽  
pp. 6291-6326
Author(s):  
A. Venäläinen ◽  
N. Korhonen ◽  
N. Koutsias ◽  
F. Xystrakis ◽  
I. R. Urbieta ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Fire Danger ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Current Season ◽  
Fire Activity ◽  
Forest Fire Danger ◽  
In Fire

Abstract. Understanding how fire-weather danger indices changed in the past, and detecting how changes affected forest fire activity is important in changing climate. We used the Canadian Fire Weather Index (FWI), calculated from two reanalysis datasets, ERA 40 and ERA Interim, to examine the temporal variation of forest fire danger in Europe in 1960–2012. Additionally, we used national forest-fires statistical data from Greece and Spain to relate fire danger and fire activity. There is no obvious trend in fire danger for the time period covered by ERA 40 (1960–1999) whereas for the period 1980–2012 covered by ERA Interim, the mean FWI and the number of high fire risk days shows an increasing trend which is significant at the 99% confidence level for South and East Europe. The cross-correlation calculated at national level in Greece and Spain between mean yearly area burned and mean FWI of the current season is of the order 0.5–0.6, and demonstrates the importance of the fire-season weather on forest fires. Our results show that, fire risk is multifaceted, and factors like changes in fire fighting capacity, ignition patterns, or landscapes might have played a role in forest fires trends. However, weather trends remain as important determinants of forest fires.

scholarly journals Temporal variations and change in forest fire danger in Europe for 1960–2012

2014 ◽  
Vol 14 (6) ◽  
pp. 1477-1490 ◽  
Author(s):  
A. Venäläinen ◽  
N. Korhonen ◽  
O. Hyvärinen ◽  
N. Koutsias ◽  
F. Xystrakis ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
National Level ◽  
Temporal Variations ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Current Season ◽  
Forest Fire Danger

Abstract. Understanding how fire weather danger indices changed in the past and how such changes affected forest fire activity is important in a changing climate. We used the Canadian Fire Weather Index (FWI), calculated from two reanalysis data sets, ERA-40 and ERA Interim, to examine the temporal variation of forest fire danger in Europe in 1960–2012. Additionally, we used national forest fire statistics from Greece, Spain and Finland to examine the relationship between fire danger and fires. There is no obvious trend in fire danger for the time period covered by ERA-40 (1960–1999), whereas for the period 1980–2012 covered by ERA Interim, the mean FWI shows an increasing trend for southern and eastern Europe which is significant at the 99% confidence level. The cross correlations calculated at the national level in Greece, Spain and Finland between total area burned and mean FWI of the current season is of the order of 0.6, demonstrating the extent to which the current fire-season weather can explain forest fires. To summarize, fire risk is multifaceted, and while climate is a major determinant, other factors can contribute to it, either positively or negatively.

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 GIS-analysis of ground transport accessibility of fire stations at regional scale

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Ekaterina Podolskaia ◽  
Dmitriy Ershov ◽  
Konstantin Kovganko
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Road Network ◽  
Fire Danger ◽  
Ground Movement ◽  
Gis Analysis ◽  
Transport Accessibility ◽  
Irkutsk Region ◽  
Fire Station ◽  
Fire Stations

<p><strong>Abstract.</strong> Geospatial approaches are widely used to organize access and to manage the extinguishing of forest fires globally. Term “transport accessibility” is used in a variety of geographical and economic researches. Assessment of transport accessibility is directly related to the feasibility study to locate the fire stations in a particular region. Location analysis of objects relative to other objects, while taking into account various quantitative and qualitative parameters, is a classical problem solved by geoinformation systems.</p><p>Present research work is aimed to be used to improve the situation with forest fires in Russia where one of the main asset of operational regional firefighting in the forests is a fire-and-chemical (fire) station. Traditionally station placement is under the responsibility of Russian region to which stations are administratively subordinate. The location of fire station is determined taking into account the species structure of forests, natural fire danger, road infrastructure and some other factors. Irkutsk region, one of the territories with the constant perennial fire danger in the forests, was chosen as a test area.</p><p>Using this area as a typical example of regional extent, an analysis of fire stations placement then planning the ground movement of fire brigades from a station to the forest fire locations has been carried out. Previously obtained results to create the shortest routes within three-hour accessibility for the fire hazardous seasons 2002&amp;ndash;2017 are used. Russian regulatory documents of the forest industry are applied. Thus, topic of GIS analysis serves as a continuation of the study (http://cepl.rssi.ru/wp-content/uploads/2018/11/Podolskaya-E.S.-et.-al..pdf, in Russian) and various aspects of transportation problem are considered on the example of Irkutsk region.</p><p>We used the following input data: point layer of fire stations, road network (including roads of different classes and forest glades), and archive of forest fires detected using the spectroradiometer MODIS from the Aqua and Terra spacecraft. Additional data were collected from the open regional Internet sources. GIS analysis used ArcGIS ArcMap Desktop extensions such as Network Analyst, Spatial Analyst, and ArcGIS tools like ET GeoWizards (https://www.ian-ko.com/).</p><p>We have developed and have used a <i>forest fire transport model of ground access</i> by trucks for the Irkutsk region with the spatial arrangement of fire stations, two protection zones and road network. Speed of the forest fire trucks is classified into 5 groups, taking into account the official permissions and road class. Also every segment of road has its attributive data of speed “adjusted” by the elevation value of the ETopo2, an open-access model (https://www.ngdc.noaa.gov/mgg/global/etopo2.html). Taking into consideration these relief data allows to decrease the vehicle’s speed in the mountainous conditions.</p><p>Based on the regional specifics and available data for a fire hazardous season, the following set of evaluation parameters was proposed, namely:</p><ul><li>Road network: roads existence, length, density, and configuration;</li><li>Spatial distribution of detected forest fires;</li><li>Territory of fire stations servicing.</li></ul><p>All the listed parameters are interconnected to each other and, in combination, jointly impact the stations ground transport accessibility assessment at the regional level. We have used GIS-analysis methods such as buffering, allocation, and density, as well as geographic and directional distribution. Time frame of analysis is the full fire hazardous season. Undertaken analysis for the forest fires detected within the ground protection zone (archive of 2002&amp;ndash;2017) has shown that the fire stations’ distribution was appropriate. The analysis was based on the assumption that stations had the same weight, geographical and transport location of the stations was reviewed in conjunction to the thematical forestry recommendations. To go further in the GIS analysis some characteristics (work force and technical resources) of the weighted stations could be added.</p><p>Additional factors of influence can be the location of protected areas with their specific access regime, seasonality of road use, forest fire zoning, forestry boundaries, economic criteria, placement of fire stations in the populated area, etc. It is advisable to conduct a fire stations placement analysis as a preparation event before and after the end of the fire-hazardous season to summarize the effectiveness of actions to extinguish forest fires in the region. Practical results of the study can be used as well to prepare the regional forestry development programs and plans.</p>

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 Comparison of Methods for the Assessment of Fire Danger in the Czech Republic

2019 ◽  
Vol 67 (5) ◽  
pp. 1285-1295 ◽  
Author(s):  
František Jurečka ◽  
Martin Možný ◽  
Jan Balek ◽  
Zdeněk Žalud ◽  
Miroslav Trnka
Keyword(s):  
Czech Republic ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Danger ◽  
Special Focus ◽  
Fire Weather ◽  
Fire Event ◽  
Fire Weather Index ◽  
The Czech Republic ◽  
Fire Danger Indices

The performance of fire indices based on weather variables was analyzed with a special focus on the Czech Republic. Three fire weather danger indices that are the basis of fire danger rating systems used in different parts of the world were assessed: the Canadian Fire Weather Index (FWI), Australian Forest Fire Danger Index (FFDI) and Finnish Forest Fire Index (FFI). The performance of the three fire danger indices was investigated at different scales and compared with actual fire events. First, the fire danger indices were analyzed for different land use types during the period 1956–2015. In addition, in the analysis, the three fire danger indices were compared with wildfire events during the period 2001–2015. The fire danger indices were also analyzed for the specific locality of the Bzenec area where a large forest fire event occurred in May 2012. The study also focused on the relationship between fire danger indices and forest fires during 2018 across the area of the Jihomoravský region. Comparison of the index values with real fires showed that the index values corresponded well with the occurrence of forest fires. The analysis of the year 2018 showed that the highest index values were reached on days with the greater fire occurrence. On days with 5 or 7 reported fires per day, the fire danger indices reached values between 3 and 4.

scholarly journals Risk of large-scale fires in boreal forests of Finland under changing climate

2016 ◽  
Vol 16 (1) ◽  
pp. 239-253 ◽  
Author(s):  
I. Lehtonen ◽  
A. Venäläinen ◽  
M. Kämäräinen ◽  
H. Peltola ◽  
H. Gregow
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Forest Fires ◽  
Large Scale ◽  
Fire Danger ◽  
Short Period ◽  
Projected Change ◽  
Fire Activity ◽  
Model Variability ◽  
The Impact

Abstract. The target of this work was to assess the impact of projected climate change on forest-fire activity in Finland with special emphasis on large-scale fires. In addition, we were particularly interested to examine the inter-model variability of the projected change of fire danger. For this purpose, we utilized fire statistics covering the period 1996–2014 and consisting of almost 20 000 forest fires, as well as daily meteorological data from five global climate models under representative concentration pathway RCP4.5 and RCP8.5 scenarios. The model data were statistically downscaled onto a high-resolution grid using the quantile-mapping method before performing the analysis. In examining the relationship between weather and fire danger, we applied the Canadian fire weather index (FWI) system. Our results suggest that the number of large forest fires may double or even triple during the present century. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to active and efficient fire suppression. However, the results reveal substantial inter-model variability in the rate of the projected increase of forest-fire danger, emphasizing the large uncertainty related to the climate change signal in fire activity. We moreover showed that the majority of large fires in Finland occur within a relatively short period in May and June due to human activities and that FWI correlates poorer with the fire activity during this time of year than later in summer when lightning is a more important cause of fires.

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.

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