An Analysis to Predict Forest Fire Danger and Fire Spread

2003 ◽  
Author(s):  
Kohyu Satoh ◽  
Shiro Kitamura ◽  
Kunio Kuwahara ◽  
K. T. Yang
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Intelligent System ◽  
Fire Spread ◽  
Fire Danger ◽  
Weather Data ◽  
Fire Weather ◽  
The Us ◽  
Weather Stations ◽  
Forest Fire Danger

Forest fires are of common occurrence all over the world, causing severe damages to valuable natural environment and loss of human lives. In order to reduce the damages by forest fires, it is useful to utilize a system, which can predict the occurrence of forest fires and the spread of fires. Well known is a system in USA, called NFDRS to predict forest fire occurrence and FARSITE to predict fire growth, based on the fire weather information taken from a network, combined with forest fuel conditions and land topography data, and processed by an algorithm to generate the various fire danger indices. In Japan the number of forest fires is roughly 3,000 per year, which is 1/30 times compared with USA, and there are very few fires exceeding 1000 ha burnt area, hence there has existed scant demand for this type of intelligent system. Although recently there is an increasing demand for such a system in Japan, the US system for forest-fire prediction is however not applicable to Japan, since the forest topology and weather conditions between Japan and USA are far different. Moreover, many fire weather stations have been installed in the US forests, but in Japan no such fire weather stations are installed in forests. Thus, as a first step to develop an intelligent system for Japan, we have analyzed the fundamentals of forest fire danger rating and the fire spread, based on the weather data and other information on forest fires. The objective of this study is to examine how the fundamentals, based on analyzing the past fire occurrences and CFD simulations particularly on “Katunuma Fire”, can predict the occurrence of forest fires and the spread 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 Efficiency evaluation of the weighted mean calculation of the forest fire hazard class

2021 ◽  
Vol 875 (1) ◽  
pp. 012064
Author(s):  
R V Kotelnikov ◽  
A N Chugaev
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Hazard ◽  
Fire Danger ◽  
Weighted Mean ◽  
Calculation Algorithm ◽  
Forest Protection ◽  
The Mean ◽  
Weather Stations ◽  
Forest Fire Danger

Abstract Nowadays, cost-optimization of aerial patrolling plays a key role in the context of limited aerial forest protection funding. Forest Fire Danger Class is the main indicator that regulates the work of forest fire services. Usually, it’s calculated by the nearest weather station data. Some information systems use the mean of several nearby weather stations to estimate large areas, such as the surveyed area of aerial forest protection. The idea of using the mean weighted index with the weather stations weighting factor is not new. Even though, this idea isn’t widespread due to the calculation complexity and questionable efficiency in practice, this study proposes a scientifically substantiated method of quantitative comparison of two approaches and the direct calculation method of the economic impact when transition to using the mean weighted Forest Fire Danger Class calculation algorithm. The first time such an indicator was used to obtain derivatives of analytical information products. A long-term analysis of forest fire rate showed that the weighted mean of the Forest Fire Danger Class value is 6.7% greater in correlation with the number of forest fires than the usual mean value. The use logarithmic transformation of the forest fire occurrence frequency and population density allows statistical criteria to be reasonably used.

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 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 Long-term temporal changes in the occurrence of a high forest fire danger in Finland

2012 ◽  
Vol 12 (8) ◽  
pp. 2591-2601 ◽  
Author(s):  
H. M. Mäkelä ◽  
M. Laapas ◽  
A. Venäläinen
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Large Scale ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Fire Danger ◽  
Specific Information ◽  
Climate Data ◽  
Forest Fire Danger

Abstract. Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June–August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908–2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.

scholarly journals Introducing a New Remote Sensing-Based Model for Forecasting Forest Fire Danger Conditions at a Four-Day Scale

2019 ◽  
Vol 11 (18) ◽  
pp. 2101 ◽  
Author(s):  
M. Ahmed ◽  
Quazi Hassan ◽  
Masoud Abdollahi ◽  
Anil Gupta
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Land Surface ◽  
Vegetation Index ◽  
Significant Risk ◽  
Fire Danger ◽  
Area Of Interest ◽  
Forest Fire Danger ◽  
Very High

Forest fires are natural disasters that create a significant risk to the communities living in the vicinity of forested landscape. To minimize the risk of forest fires for the resilience of such urban communities and forested ecosystems, we proposed a new remote sensing-based medium-term (i.e., four-day) forest fire danger forecasting system (FFDFS) based on an existing framework, and applied the system over the forested regions in the northern Alberta, Canada. Hence, we first employed moderate resolution imaging spectroradiometer (MODIS)-derived daily land surface temperature (Ts) and surface reflectance products along with the annual land cover to generate three four-day composite for Ts, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) at 500 m spatial resolution for the next four days over the forest-dominant regions. Upon generating these four-day composites, we calculated the variable-specific mean values to determine variable-specific fire danger maps with two danger classes (i.e., high and low). Then, by assuming the cloud-contaminated pixels as the low fire danger areas, we combined these three danger maps to generate a four-day fire danger map with four danger classes (i.e., low, moderate, high, and very high) over our study area of interest, which was further enhanced by incorporation of a human-caused static fire danger map. Finally, the four-day scale fire danger maps were evaluated using observed/ground-based forest fire occurrences during the 2015–2017 fire seasons. The results revealed that our proposed system was able to detect about 75% of the fire events in the top two danger classes (i.e., high and very high). The system was also able to predict the 2016 Horse River wildfire, the worst fire event in Albertian and Canadian history, with about 67% agreement. The higher accuracy outputs from our proposed model indicated that it could be implemented in the operational management, which would be very useful for lessening the adverse impact of such fire events.

scholarly journals Impact of More Frequent Observations on the Understanding of Tasmanian Fire Danger

2011 ◽  
Vol 50 (8) ◽  
pp. 1617-1626 ◽  
Author(s):  
Paul Fox-Hughes
Keyword(s):  
Fire Danger ◽  
Weather Data ◽  
High Temporal Resolution ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Diurnal Variability ◽  
Weather Events ◽  
Forest Fire Danger ◽  
Synoptic Observations ◽  
Climate Studies

AbstractHalf-hourly airport weather observations have been used to construct high-temporal-resolution datasets of McArthur Mark V forest fire danger index (FFDI) values for three locations in Tasmania, Australia, enabling a more complete understanding of the range and diurnal variability of fire weather. Such an understanding is important for fire management and planning to account for the possibility of weather-related fire flare ups—in particular, early in a day and during rapidly changing situations. In addition, climate studies have hitherto generally been able to access only daily or at best 3-hourly weather data to generate fire-weather index values. Comparison of FFDI values calculated from frequent (subhourly) observations with those derived from 3-hourly synoptic observations suggests that large numbers of significant fire-weather events are missed, even by a synoptic observation schedule, and, in particular, by observations made at 1500 LT only, suggesting that many climate studies may underestimate the frequencies of occurrence of fire-weather events. At Hobart, in southeastern Tasmania, only one-half of diurnal FFDI peaks over a critical warning level occur at 1500 LT, with the remainder occurring across a broad range of times. The study reinforces a perception of pronounced differences in the character of fire weather across Tasmania, with differences in diurnal patterns of variability evident between locations, in addition to well-known differences in the ranges of peak values observed.

Wildfires and the Canadian Forest Fire Weather Index system for the Daxing'anling region of China

2011 ◽  
Vol 20 (8) ◽  
pp. 963 ◽  
Author(s):  
Xiaorui Tian ◽  
Douglas J. McRae ◽  
Jizhong Jin ◽  
Lifu Shu ◽  
Fengjun Zhao ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Coniferous Forest ◽  
Northern China ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Burnt Area ◽  
Weather Index ◽  
Fire Weather Index

The Canadian Forest Fire Weather Index (FWI) system was evaluated for the Daxing'anling region of northern China for the 1987–2006 fire seasons. The FWI system reflected the regional fire danger and could be effectively used there in wildfire management. The various FWI system components were classified into classes (i.e. low to extreme) for fire conditions found in the region. A total of 81.1% of the fires occurred in the high, very high and extreme fire danger classes, in which 73.9% of the fires occurred in the spring (0.1, 9.5, 33.3 and 33.1% in March, April, May and June). Large wildfires greater than 200 ha in area (16.7% of the total) burnt 99.2% of the total burnt area. Lightning was the main ignition source for 57.1% of the total fires. Result show that forest fires mainly occurred in deciduous coniferous forest (61.3%), grass (23.9%) and deciduous broad leaved forest (8.0%). A bimodal fire season was detected, with peaks in May and October. The components of FWI system were good indicators of fire danger in the Daxing'anling region of China and could be used to build a working fire danger rating system for the region.

Classification of Territory on Forest Fire Danger Level Using GIS and Remote Sensing

2020 ◽  
pp. 258-267 ◽  
Author(s):  
Elena Petrovna Yankovich ◽  
Ksenia S. Yankovich
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Fire Danger ◽  
Gis And Remote Sensing ◽  
Forest Fuels ◽  
Forest Fire Danger

The vegetation cover is the most important factor in forest fires, because it reflects the presence of forest fuels. The study of the variability of the vegetation cover, as well as observation of its condition, allows estimating the level of fire danger of the forest quarter. The work presents a geo-information system containing a set of tools to determine the level of fire danger of the forest quarter. The system is able to predict (determine the probability) and classify forest quarters according to the level of fire danger. The assessment of forest fire danger of Tomsk forestry of Tomsk region has been carried out. Fire probability maps of forest quarters were created based on remote sensing data and ArcGIS software.

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