Assessment of forest fire danger using automatic weather stations and MODIS TERRA satellite datasets for the state Madhya Pradesh, India

2017 ◽  
Author(s):  
K.V. Suresh Babu ◽  
Venkata Sai Krishna Vanama ◽  
Arijit Roy ◽  
P. Ramachandra Prasad
Keyword(s):  
Forest Fire ◽  
The State ◽  
Madhya Pradesh ◽  
Fire Danger ◽  
Weather Stations ◽  
Forest Fire Danger ◽  
Terra Satellite

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.

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 Forest fire danger rating in complex topography – results from a case study in the Bavarian Alps in autumn 2011

2013 ◽  
Vol 13 (9) ◽  
pp. 2157-2167 ◽  
Author(s):  
C. Schunk ◽  
C. Wastl ◽  
M. Leuchner ◽  
C. Schuster ◽  
A. Menzel
Keyword(s):  
Forest Fire ◽  
Temperature Inversion ◽  
Fire Danger ◽  
Complex Topography ◽  
Pressure System ◽  
Drought Period ◽  
Bavarian Alps ◽  
Forest Fire Danger ◽  
Fire Danger Indices

Abstract. Forest fire danger rating based on sparse meteorological stations is known to be potentially misleading when assigned to larger areas of complex topography. This case study examines several fire danger indices based on data from two meteorological stations at different elevations during a major drought period. This drought was caused by a persistent high pressure system, inducing a pronounced temperature inversion and its associated thermal belt with much warmer, dryer conditions in intermediate elevations. Thus, a massive drying of fuels, leading to higher fire danger levels, and multiple fire occurrences at mid-slope positions were contrasted by moderate fire danger especially in the valleys. The ability of fire danger indices to resolve this situation was studied based on a comparison with the actual fire danger as determined from expert observations, fire occurrences and fuel moisture measurements. The results revealed that, during temperature inversion, differences in daily cycles of meteorological parameters influence fire danger and that these are not resolved by standard meteorological stations and fire danger indices (calculated on a once-a-day basis). Additional stations in higher locations or high-resolution meteorological models combined with fire danger indices accepting at least hourly input data may allow reasonable fire danger calculations under these circumstances.

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 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.

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