A Review of the Main Driving Factors of Forest Fire Ignition Over Europe

Knowledge of the causes of forest fires, and of the main driving factors of ignition, is an indispensable step towards effective fire prevention policies. This study analyses the factors driving forest fire ignition in the Mediterranean region including the most common human and environmental factors used for modelling in the European context. Fire ignition factors are compared to spatial and temporal variations of fire occurrence in the region, then are compared to results obtained in other areas of the world, with a special focus on North America (US and Canada) where a significant number of studies has been carried out on this topic. The causes of forest fires are varied and their distribution differs among countries, but may also differ spatially and temporally within the same country. In Europe, and especially in the Mediterranean basin, fires are mostly human-caused mainly due arson. The distance to transport networks and the distance to urban or recreation areas are among the most frequently used human factors in modelling exercises and the Wildland-Urban Interface is increasingly taken into account in the modelling of fire occurrence. Depending on the socio-economic context of the region concerned, factors such as the unemployment rate or variables linked to agricultural activity can explain the ignition of intentional and unintentional fires. Regarding environmental factors, those related to weather, fuel and topography are the most significant drivers of ignition of forest fires, especially in Mediterranean-type regions. For both human and lightning-caused fires, there is a geographical gradient of fire ignition, mainly due to variations in climate and fuel composition but also to population density for instance. The timing of fires depends on their causes. In populated areas, the timing of human-caused fires is closely linked to human activities and peaks in the afternoon whereas, in remote areas, the timing of lightning-caused fires is more linked to weather conditions and the season, with most such fires occurring in summer.     

Biophysical and anthropogenic controls of forest fires in the Deccan Plateau, India

Forest fires constitute one of the most serious environmental problems in several forested regions of India. In the Indian sub-continent, relatively few studies have focused on the assessment of biophysical and anthropogenic controls of forest fires at a landscape scale and the spatial aspects of these relationships. In this study, we used fire count data sets from satellite remote sensing data covering 78 districts over four different states of the Deccan Plateau, India, for assessing the underlying causes of fires. Spatial data for explanatory variables of fires pertaining to topography, vegetation, climate, anthropogenic and accessibility factors have been gathered corresponding with fire presence/absence. A logistic regression model was used to estimate the probability of the presence of fires as a function of the explanatory variables. Results for fire area estimates suggested that, of the total fires covering 47,043km(2) that occurred during the year 2000 for the entire Indian region, 29.0% occurred in the Deccan Plateau, with Andhra Pradesh having 13.5%, Karnataka 14.7%, Kerala 0.1%, and Tamilnadu 1.15%. Results from the logistic regression suggest that the strongest influences on the fire occurrences were the amount of forest area, biomass densities, rural population density (PD), average precipitation of the warmest quarter, elevation (ELE) and mean annual temperature (MAT). Among these variables, biomass density (BD) and average precipitation of the warmest quarter had the highest significance, followed by others. These results on the best predictors of forest fires can be used both as a strategic planning tool to address broad scale fire risk concerns, and also as a tactical guide to help forest managers to design fire mitigation measures at the district level.     

Mapping probability of fire occurrence in San Jacinto Mountains,California, USA

An ecological data base for the San Jacinto Mountains, California, USA, was used to construct a probability model of wildland fire occurrence. The model incorporates both environmental and human factors, including vegetation, temperature, precipitation, human structures, and transportation. Spatial autocorrelation was examined for both fire activity and vegetation to determine the specification of neighborhood effects in the model. Parameters were estimated using stepwise logistic regressions. Among the explanatory variables, the variable that represents the neighborhood effects of spatial processes is shown to be of great importance in the distribution of wildland fires. An important implication of this result is that the management of wildland fires must take into consideration neighborhood effects in addition to environmental and human factors. The distribution of fire occurrence probability is more accurately mapped when the model incorporates the spatial term of neighborhood effects. The map of fire occurrence probability is useful for designing large-scale management strategies of wildfire prevention.     

Predicting Sustained Fire Spread in Tasmanian Native Grasslands

Fire is widely used in conservation management of native grasslands. Burning is often carried out under conditions that are marginal for sustained fire spread, and therefore it would be useful to be able to predict fire sustainability. There is currently no model allowing such prediction in temperate grasslands. This study aims to identify the environmental variables that determine whether fires will sustain in native grasslands in Tasmania, Australia, and develop a model for predicting fire sustainability in this vegetation. Fuel characteristics and weather conditions were recorded for 111 test fires. Logistic regression modeling identified dead fuel moisture content, fuel load, and percentage dead fuel as predictors of fire sustainability. Classification tree modeling identified dead fuel moisture and fuel load threshold values for sustaining fires. There was also evidence indicating a percentage dead fuel threshold. The logistic regression model and a model combining the results of the classification tree and the percentage dead fuel threshold accurately predicted the outcomes of a small set of experimental fires. These models are likely to have utility in predicting fire sustainability in Tasmanian grasslands and are also likely to be applicable to similar grasslands elsewhere.     

Forest-user attitudes toward alternative fire management policies

The formulation and implementation of new fire policies in the national forests depend upon public acceptance. A national survey of organized groups of forest users indicates that, contrary to the concern of many forest managers, considerable support exists for flexible fire suppression policies. Forest users are also willing to accept the risk associated with the manager's use of prescribed fire. However, important intergroup differences do exist. Such variation is discussed in relation to a number of socioeconomic variables, general fire knowledge, specific knowledge about the effects of low-intensity fires, and risk preference levels.     

Modeling the Landscape Drivers of Fire Recurrence in Sardinia (Italy)

Although recurrent fire events with very short return periods have the most dangerous effects on landscape degradation, only a few papers have explored the landscape ecological factors that drive the probability of fire recurrence. In this paper we apply a habitat suitability model for analyzing the spatial relationship between a selected set of landscape factors (mainly land use types) and fire recurrence in Sardinia (Italy) in the years 2005–2010. Our results point out that fire occurrence in already burned areas is lower than expected in natural and semi-natural land cover types, like forest and shrublands. To the contrary, like in all regions where human activity is the main source of fire ignitions, the probability of fire recurrence is higher at low altitudes and close to roads and to urban and agricultural land cover types, thus showing marked preference for those landscape factors denoting higher anthropogenic ignition risk.     

Using Satellite Fire Detection to Calibrate Components of the Fire Weather Index System in Malaysia and Indonesia

Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and Indonesia have two new sources of information to initiate fire prevention and suppression activities.     

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.     

Analysis of the prescribed burning practice in the pine forest of northwestern Portugal

The ignition of low-intensity fires in the dormant season in the pine stands of north-western Portugal seeks to reduce the existing fuel hazard without compromising site quality. The purpose of this study is to characterise this practice and assess its effectiveness, based on information resulting from the normal monitoring process at the management level, and using operational guidelines, fire behaviour models and a newly developed method to classify prescribed fire severity. Although the region's humid climate strongly constrains the activity of prescribed fire, 87% of the fires analysed were undertaken under acceptable meteorological and fuel moisture conditions. In fact, most operations achieved satisfactory results. On average, prescribed fire reduces by 96% the potential intensity of a wildfire occurring under extreme weather conditions, but 36% of the treated sites would still require heavy fire fighting resources to suppress such fire, and 17% would still carry it in the tree canopy. Only 10% of the prescribed burns have an excessive impact on trees or the forest floor, while 89% (normal fire weather) or 59% (extreme fire weather) comply with both ecological integrity maintenance and wildfire protection needs. Improved planning and monitoring procedures are recommended in order to overcome the current deficiencies.     

Predicted effects of prescribed burning and harvesting on forest recovery and sustainability in southwest Georgia, USA

A model-based analysis of the effect of prescribed burning and forest thinning or clear-cutting on stand recovery and sustainability was conducted at Fort Benning, GA, in the southeastern USA. Two experiments were performed with the model. In the first experiment, forest recovery from degraded soils was predicted for 100 years with or without prescribed burning. In the second experiment simulations began with 100 years of predicted stand growth, then forest sustainability was predicted for an additional 100 years under different combinations of prescribed burning and forest harvesting. Three levels of fire intensity (low, medium, and high), that corresponded to 17%, 33%, and 50% consumption of the forest floor C stock by fire, were evaluated at 1-, 2-, and 3-year fire return intervals. Relative to the control (no fire), prescribed burning with a 2- or 3-year return interval caused only a small reduction in predicted steady state soil C stocks (< or =25%) and had no effect on steady state tree wood biomass, regardless of fire intensity. Annual high intensity burns did adversely impact forest recovery and sustainability (after harvesting) on less sandy soils, but not on more sandy soils that had greater N availability. Higher intensity and frequency of ground fires increased the chance that tree biomass would not return to pre-harvest levels. Soil N limitation was indicated as the cause of unsustainable forests when prescribed burns were too frequent or too intense to permit stand recovery.     

A heuristic expert system for forest fire guidance in Greece

Forests and forestlands are common inheritance for all Greeks and a piece of the national wealth that must be handed over to the next generations in the best possible condition. After 1974, Greece faces a severe forest fire problem and forest fire forecasting is the process that will enable the Greek ministry of Agriculture to reduce the destruction. This paper describes the basic design principles of an Expert System that performs forest fire forecasting (for the following fire season) and classification of the prefectures of Greece into forest fire risk zones. The Expert system handles uncertainty and uses heuristics in order to produce scenarios based on the presence or absence of various qualitative factors. The initial research focused on the construction of a mathematical model which attempted to describe the annual number of forest fires and burnt area in Greece based on historical data. However this has proven to be impossible using regression analysis and time series. A closer analysis of the fire data revealed that two qualitative factors dramatically affect the number of forest fires and the hectares of burnt areas annually. The first is political stability and national elections and the other is drought cycles. Heuristics were constructed that use political stability and drought cycles, to provide forest fire guidance. Fuzzy logic was applied to produce a fuzzy expected interval for each prefecture of Greece. A fuzzy expected interval is a narrow interval of values that best describes the situation in the country or a part of the country for a certain time period. A successful classification of the prefectures of Greece in forest fire risk zones was done by the system, by comparing the fuzzy expected intervals to each other. The system was tested for the years 1994 and 1995. The testing has clearly shown that the system can predict accurately, the number of forest fires for each prefecture for the following year. The average accuracy was as high as 85.25% for 1995 and 80.89% for 1994. This makes the Expert System a very important tool for forest fire prevention planning.     

Evaluation of the Fire Simulation Processes of the National Fire Management System's Initial Attack Analysis Processor

The fire simulation processes of the National Fire Management System's (NFMAS) Initial Attack Analysis (IAA) processor were evaluated by conducting two types of sensitivity analysis: one based on a hypothetical set of data to assess IAA's outputs under a wide range of fire input values, and the other using an actual Stanislaus National Forest database to test IAA's validity with a real set of data. The results revealed that IAA's outputs (projected annual number of fires and area burned) were most sensitive, in descending order, to the input values of the fire spread rate, the productivity rates of the suppression forces, and the initial attack time, for all fuel models tested. In contrast, IAA's outputs were extremely insensitive to variations in the fire size at discovery. Changes are necessary in the ways IAA incorporates the fire size at discovery to facilitate the comparison among various fire detection options. The program's “escaped fire situation” analysis was found inadequate, because the projected annual frequencies and final sizes of the simulated escaped fire events produced unacceptable results with the Stanislaus National Forest database. Assigning final sizes to simulated escaped fires according to the fire intensity level in which they are historically expected to occur provides a consistent way of calculation of the projected annual area burned and the consequent cost plus net value change (C + NVC).     

Predictive model for areas with illegal landfills using logistic regression

The existence of illegal landfills is an environmental problem in most countries. However, research on this issue is scarce and limited by the availability and quality of data on the subject. Thus, most illegal landfill studies have only been conducted in a partial manner, focusing on geographical aspects or the causes of these landfills (lack of environmental awareness, inadequate waste management systems, and the role of local government). This research analyses a sample of 120 possible areas with illegal landfills in Andalusia using logistic regression in order to obtain a predictive model for the occurrence of these landfills, including both types of variables (geographical and behavioural) jointly. The results confirm that the variables that most influence the occurrence of illegal landfills are spatial (“Industrial Land”, “Plains” and “Rural Land”); whilst the variables that most reduce the likelihood of illegal landfills are those related to certain characteristics of the municipal waste management system and environmental awareness, such as “Availability of Recycling Facilities”, “Punitive Policies”, “Supervision” and “Awareness-raising Campaigns”. The model obtained shows that variables of very different nature and magnitude interact in the occurrence of illegal landfills, each of which contributes a series of features characteristic of its scale. It is advisable, therefore, to perform an analysis using a multi-scale approach in order to gain an overall understanding of the phenomenon.     

Lightning Fires in a Brazilian Savanna National Park: Rethinking Management Strategies

Fire occurrences and their sources were monitored in Emas National Park, Brazil (17°49′–18°28′S; 52°39′–53°10′W) from June 1995 to May 1999. The extent of burned area and weather conditions were registered. Forty-five fires were recorded and mapped on a GIS during this study. Four fires occurred in the dry winter season (June–August; 7,942 ha burned), all caused by humans; 10 fires occurred in the seasonally transitional months (May and September) (33,386 ha burned); 31 fires occurred in the wet season, of which 30 were caused by lightning inside the park (29,326 ha burned), and one started outside the park (866 ha burned). Wet season lightning fires started in the open vegetation (wet field or grassy savanna) at a flat plateau, an area that showed significantly higher fire incidence. On average, winter fires burned larger areas and spread more quickly, compared to lightning fires, and fire suppression was necessary to extinguish them. Most lightning fires were patchy and extinguished primarily by rain. Lightning fires in the wet season, previously considered unimportant episodes, were shown to be very frequent and probably represent the natural fire pattern in the region. Lightning fires should be regarded as ecologically beneficial, as they create natural barriers to the spread of winter fires. The present fire management in the park is based on the burning of preventive firebreaks in the dry season and exclusion of any other fire. This policy does not take advantage of the beneficial effects of the natural fire regime and may in fact reduce biodiversity. The results presented here stress the need for reevaluating present policies and management procedures concerning fire in cerrado conservation areas.     

A land management history for central Queensland,Australia as determined from land-holder questionnaire and aerial photography

Features of the land management history over a 125,755 km(2) area of central Queensland, Australia were determined from a variety of sources. A random sample of 205 site locations provided the basis for determining trends in land use. Trends in vegetation clearing were determined using sequential aerial photography for the sample sites, revealing a steady rate averaging nearly 1% of the region per annum over 41 years. This measure of sustained clearing over a large region is higher than recently published clearing rates from South America. Land types have been selectively cleared with over 90% of the Acacia on clay land type having been cleared. A land-holder questionnaire pertaining to the random sites yielded a response rate of 71% and provided information on vegetation clearing, ploughing, tree killing (ring-barking or tree poisoning), and fire frequency, season and intensity. The land-holder responses were compared with independent data sources where possible and revealed no mis-information. However, land-holders may have been marginally less likely to respond if the sample area had been cleared, although this effect was not statistically significant. Ploughing and tree killing are variable depending on land type, but the former has affected about 40% of the Acacia on clay land type, effectively eliminating options for natural regrowth. The proportion of decade-site combinations that were reported as having no fires increased from 22% in the 1950s to an average of 42% for subsequent decades, although the reporting of more than one fire per decade has been relatively constant through the study period. The reporting of at least one fire per decade varies from 46% for the Acacia on sand land type to 77% for the Eucalypt on sand land type for decade-site combinations. Fires are more intense when associated with clearing than in uncleared vegetation, but the proportion of cool and hot fires is relatively constant between land types in uncleared vegetation. Nearly all fires reported were either in spring or summer and this seasonally restricted regime is probably at variance with Aboriginal fire regimes. This study describes the rapid transformation of central Queensland. This has yielded substantially increased agricultural production but may also result in a range of negative impacts and these are discussed.     

A Multidisciplinary Decision Support System for Forest Fire Crisis Management

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The systems architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.     

A focus group study of factors that promote and constrain the use of satellite-derived fire products by resource managers in southern Africa

Semi-structured focus group interviews were employed to examine factors that affect the likelihood that resource managers in southern Africa will use information on vegetation fires provided by two satellite-derived products: an active fire product and a burned area product. The two products are updated regularly and aim to deliver the state-of-the-art in the global monitoring of fires from satellite remote-sensing. Both products are derived from data transmitted by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors carried onboard NASA's Aqua and Terra satellites. The active fire product can be accessed for free via the internet and on media by users working anywhere in the world; the burned area product will be accessible in a similar manner in 2006. The MODIS fire products provide systematic, near-global coverage and are freely available; as such, they give resource managers new opportunities to obtain or supplement information they need to manage vegetation fires effectively. However, the availability of these products does not mean that resource managers will use them, and many other factors are involved. To understand factors that affect whether southern African resource managers will use the two products, two focus groups were held with members of the Southern African Fire Network (SAFNet) in Malawi, Africa, August 2004. Analysis of the group discussions reveals a number of factors that influence whether they will use the products. The qualitative, in depth nature of the group discussions revealed 12 main factors that influence product use; not least the low international internet bandwidths for African countries outside of South Africa. Analysis of the group discussions also suggests how the uptake of MODIS fire products by resource managers in southern Africa might be enhanced by affecting specific changes to how MODIS products are packaged and delivered.     

Determining Relative Contributions of Vegetation and Topography to Burn Severity from LANDSAT Imagery

Fire is a dominant process in boreal forest landscapes and creates a spatial patch mosaic with different burn severities and age classes. Quantifying effects of vegetation and topography on burn severity provides a scientific basis on which forest fire management plans are developed to reduce catastrophic fires. However, the relative contribution of vegetation and topography to burn severity is highly debated especially under extreme weather conditions. In this study, we hypothesized that relationships of vegetation and topography to burn severity vary with fire size. We examined this hypothesis in a boreal forest landscape of northeastern China by computing the burn severity of 24 fire patches as the difference between the pre- and post-fire Normalized Difference Vegetation Index obtained from two Landsat TM images. The vegetation and topography to burn severity relationships were evaluated at three fire-size levels of small (<100 ha, n = 12), moderate (100–1,000 ha, n = 9), and large (>1,000 ha, n = 3). Our results showed that vegetation and topography to burn severity relationships were fire-size-dependent. The burn severity of small fires was primary controlled by vegetation conditions (e.g., understory cover), and the burn severity of large fires was strongly influenced by topographic conditions (e.g., elevation). For moderate fires, the relationships were complex and indistinguishable. Our results also indicated that the pattern trends of relative importance for both vegetation and topography factors were not dependent on fire size. Our study can help managers to design fire management plans according to vegetation characteristics that are found important in controlling burn severity and prioritize management locations based on the relative importance of vegetation and topography.