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The purpose of this paper is to valorize the contribution of the cost-benefit analysis (CBA) method in the evaluation of the prevention measures of forest fires.

The suggested approach is based on the economic analysis of the forest fires’ risks using the CBA which has become inevitable in risk analysis’ domain.

The suggested approach shows the interest of the CBA method in the sense that each reduction measure of the forest fires’ risk eliminates the potential damages and, therefore, it is likely to generate benefits for the company in terms of avoided damages on the territory that is concerned by these measures.

It consists in comparing on time, the benefit generated by a reduction measure of a forest fires’ risk and its implementation cost. This comparison gives an important focus on the economic relevance of such a reduction measure of forest fires’ risk.

The question is to highlight the importance of both: the investment in terms of forest fires and the allocation of this investment on various preventive measures of forest fires.

The purpose of this paper is to investigate forest fires and their relationship to prevention and mitigation strategies based on the empirical problems raised by this study. Public policy implementation (in this case, the policy of forest fire management) is influenced by the role played by government and by the participation of the public and stakeholders (in this case, companies), as well as the effects of good governance. Thus, from the empirical problems associated with theoretical problems and normative problems, this study raises the influence of the role of central and local government on the implementation of forest fire prevention policy in Indonesia, which is moderated by the good governance variable.

This study used a quantitative approach by adopting survey methodology. The study has aimed to assess both large and small population groups, by selecting and reviewing carefully chosen samples of the population to find the incidence, distribution and relative interrelation of the variables considered (Kerlinger and Lee, 2000). The survey was undertaken in areas of Indonesia that have a high level of vulnerability to forest fires. There are currently six provinces – Riau, Jambi, South Sumatra, West Kalimantan, East Kalimantan and South Kalimantan – that have the highest intensity of forest fires. The study population was taken from 105 villages in those six major provinces experiencing forest fires. Sample size precision was determined by using Slovin’s formula with a precision of 10 percent and, thus, a sample size of 52 was obtained.

The central government’s activities have no significant effect on regional forest fire prevention. However, the results found that there is a significant effect caused by the interaction between the central and local governments and their governance of forest fire prevention. Even though the direct effect is not significant, the interaction effect significantly influences the forest fire prevention governance variable, which is a pure moderator. This study found that the role of central government has no effect on forest fire prevention. If the role of the central government is high, it will not impact the effectiveness of forest fire prevention, which is reflected in the aspects of prevention and early warning, reward and punishment, the improvement and management of ecosystems by reviewing courts, law enforcement and national and regional synergy.

This is one of the few public administration science studies to have investigated the relationship between good governance and forest fire policy in Indonesia, particularly the combined roles played by central and local governments.

The purpose of this research is to analyze the effect of community and company participation on corporate governance and forest fire prevention in the forest zone, which has a high level of vulnerability to forest fires, in Indonesia.

The survey method in this research used a quantitative approach with the survey method, with the sample being forest areas having a high level of vulnerability to forest fires in Indonesia. This study used a questionnaire instrument and was conducted from January to March 2017. The research population was 105 villages located in forest areas in six major provinces known to endure the largest forest fires in Indonesia. From a total population of 258 villages, 52 were selected for this study. The proportional random sampling area technique was used. The data analysis methods selected in this research were descriptive analysis and inferential statistical analysis using the partial least squares method.

Community and company participation has a significant effect on the implementation of good governance. The implementation of good governance has a significant effect and community and company participation has no direct effect on the forest fire policy, but through good governance mediation, an indirect effect of community participation on the forest fire policy is seen.

No previous research has comprehensively studied the role of community and company participation and implementation of good forest fire governance on the forest fire policy.

In a tropical country like Malaysia, forest fire is a very common natural and man‐made disaster that prevails in the whole South East Asian region throughout the year. Recently, the haze problem in Malaysia has created a lot of awareness among the government and eco‐tourism sectors. Therefore, detection of the hotspot is very important to delineate the forest fire susceptibility mapping. In this study, remote sensing and geographical information systems (GIS) have been used to evaluate forest fire susceptibility at Sungai Karang and Raja Muda Musa Forest Reserve, Selangor, Malaysia. Frequency ratio model has been applied for the delineation of forest fire mapping for the study area.

Forest fire locations were identified in the study area from historical hotspots data from year 2000 to 2005 using AVHRR NOAA 12 and NOAA 16 satellite images. Various other supported data such as soil map, topographic data, and agro climate were collected and created using GIS. These data were constructed into a spatial database using GIS. The factors that influence fire occurrence, such as fuel type and Normalized Differential Vegetation Index (NDVI), were extracted from classified Landsat‐7 ETM imagery. Slope and aspect of topography were calculated from topographic database. Soil type was extracted from soil database and dry month code from agroclimate data. Forest fire susceptibility was analyzed using the forest fire occurrence factors by likelihood ratio method.

A new statistical method has been applied for the forest fire susceptibility mapping. The results of the analysis were verified using forest fire location data with the help of a newly written programming code. The validation results show satisfactory agreement between the susceptibility map and the existing data on forest fire location. The GIS was used to analyze the vast amount efficiently, and statistical programs were used to maintain the specificity and accuracy. The result can be used for early warning, fire suppression resources planning and allocation.

All data used in this study are original. The forest fire susceptibility mapping has been done in this study area for the first time. A new program has been coded to cross‐verify the susceptibility map. The results were also verified with field data and other supporting weather data.

Every year thousands of acres are burned and a number of people lose their lives in forest fires that increasingly surpass the wild land limit and lead on to touristic, urban areas. By and large, Mediterranean countries rely highly on offering a tourist product based on sea, sun, culture and nature. While the sea and sun are not affected by fire catastrophes, places of cultural and natural beauty are indeed hit; tourists end up being uninformed with no proper guidance from the firefighting authorities. This paper seeks to address these issues.

This paper attempts to highlight the relation between fire catastrophes and tourism development, to identify if and how state authorities take into account tourists in the planning and management of appropriate measures. A comparative study between Greece and Cyprus is presented. A number of interviews with stakeholders on the policy and operational level were conducted and the results and their implications are presented.

Planning and suppression is complicated with a number of actors involved in various stages; national tourism organizations in both countries do not take part in the information or planning process. There is an emerging need for the provision of useful, comprehensive, practical information aimed at tourists.

The findings of the paper are based in a number of interviews with key policy makers as well as key operational commanders. The participation of the above in the policy making as well as operational phase shows a number of limitations. This paper presents a qualitative approach to the subject. A follow‐up quantitative study is already planned.

Lessons learnt from previous catastrophes, in‐depth analysis of the existing “modus operandi” and “rules of engagement” should provide the necessary background for creating new risk‐based, comprehensive, focused communication campaigns.

Safer societies and lower impact on the environment are the main outcomes of a concerted communication campaign. Tourism represents and multiplies the image of the country as a whole to the world; a solution to the problem would offer added value.

The paper is based on a number of in‐depth interviews with actors that took part in the actual handling of the two major catastrophes in Cyprus and Greece. The outcome of the interviews is presented for the first time.

Peat swamp forest fire hazard areas were identified and mapped by integrating GIS‐grid‐based and multi‐criteria analysis to provide valuable information about the areas most likely to be affected by fire in the Pekan District, south of Pahang, Malaysia. A spatially weighted index model was implemented to develop the fire hazard assessment model used in this study. Fire‐causing factors such as land use, road network, slope, aspect and elevation data were used in this application. A two‐mosaic Landsat TM scene was used to extract land use parameters of the study area. A triangle irregular network was generated from the digitized topographic map to produce a slope risk map, an aspect risk map and an elevation risk map. Spatial analysis was applied to reclassify and overlay all grid hazard maps to produce a final peat swamp forest fire hazard map. To validate the model, the actual fire occurrence map was compared with the fire hazard zone area derived from the model. The model can be used only for specific areas, and other criteria should be considered if the model is used for other areas. The results show that most of the actual fire spots are located in very high and high fire risk zones identified by the model.

The purpose of this paper is to examine Greek forest fires in August 2007 and statements about terrorism (pyro-terrorism) and the impact on Greek banks stocks.

Event study methodology and market model is used in this paper and data of all Greek bank stocks prices listed in Athens Stock Exchange are analysed, before and after 17 August 2007, which is when forest fires took place in Greece.

Total number of burned acres during a seven-year period, 2000-2006, was 2,530,883, and during only August 2007, burned acres accounted to 2,059,615. The former Minister for Public Order, Vyron Polydoras, stated the fires may be a result of terrorist attacks, as many of the fires started simultaneously and in places where an arsonist could not be seen. The Minister also stated that the country is facing an asymmetric threat, a military term used for terrorist attacks. The findings of event study methodology and market model show that CAARs were slightly negative but not statistically significant and during event date, and average abnormal return (AAR) was slightly positive at 0.0273 per cent. The event caused no influence on the stock market.

Results are important for banking system, compliance and regulatory authorities, justice system and politicians.

The impact of Greek forest fires in August 2007 on Greek banks stocks has not been examined so far.

Climate change during the next century is likely to significantly influence forest ecosystems in the western United States, including indirect effects on forest and shrubland fire regimes. Further exacerbation of fire hazards by the warmer, drier summers projected for much of the western U.S. by climate models would compound already elevated fire risks caused by 20th century fire suppression. This has potentially grave consequences for the urban–wildland interface in drier regions, where residential expansion increasingly places people and property in the midst of fire-prone vegetation. Understanding linkages between climate variability and change, therefore, are central to our ability to forecast future risks and adapt land management, allocation of fire management resources, and suburban planning accordingly. To establish these linkages we review previous research and draw inferences from our own retrospective work focused on 20th century climate–fire relationships in the U.S. Pacific Northwest (PNW). We investigated relationships between the two dominant modes of climate variability affecting the PNW, which are Pacific Decadal Oscillation (PDO) and El Niño/Southern Oscillation (ENSO), and historic fire activity at multiple spatial scales. We used historic fire data spanning most of the 20th century for USDA Forest Service Region 6, individual states (Idaho, Oregon, and Washington), and 20 national forests representative of the region's physiographic diversity. Forest fires showed significant correlations with warm/dry phases of PDO at regional and state scales; relationships were variable at the scale of individual national forests. Warm/dry phases of PDO were especially influential in terms of the occurrence of very large fire events throughout the PNW. No direct statistical relationships were found between ENSO and forest fires at regional scales, although relationships may exist at smaller spatial scales. However, both ENSO and PDO were correlated with summer drought, as estimated by the Palmer Drought Severity Index (PDSI), and PDSI was correlated with fire activity at all scales. Even moderate (±0.3°C decadal mean) fluctuations in PNW climate over the 20th century have influenced wildfire activity based on our analysis. Similar trends have been reported for other regions of the western U.S. Thus, forest fire activity has been sensitive to past climate variability, even in the face of altered dynamics due to fire suppression, as in the case of our analysis. It is likely that fire activity will increase in response to future temperature increases, at the same or greater magnitude as experienced during past climate variability. If extreme drought conditions become more prevalent we can expect a greater frequency of large, high-intensity forest fires. Increased vulnerability to forest fires may worsen the current fire management problem in the urban–wildland interface. Adaptation of fire management and restoration planning will be essential to address fire hazards in areas of intermingled exurban development and fire-prone vegetation. We recommend: (1) landscape-level strategic planning of fire restoration and containment projects; (2) better use of climatic forecasts, including PDO and ENSO related predictions; and (3) community-based efforts to limit further residential expansion into fire-prone forested and shrubland areas.

The purpose of this paper is to present a deep ensemble neural network model for the detection of forest fires in aerial vehicle videos.

Presented deep ensemble models include four convolutional neural networks (CNNs): a faster region-based CNN (Faster R-CNN), a simple one-stage object detector (RetinaNet) and two different versions of the you only look once (Yolo) models. The presented method generates its output by fusing the outputs of these different deep learning (DL) models.

The presented fusing approach significantly improves the detection accuracy of fire incidents in the input data.

The computational complexity of the proposed method which is based on combining four different DL models is relatively higher than that of using each of these models individually. On the other hand, however, the performance of the proposed approach is considerably higher than that of any of the four DL models.

The simulation results show that using an ensemble model is quite useful for the precise detection of forest fires in real time through aerial vehicle videos or images.

By this method, forest fires can be detected more efficiently and precisely. Because forests are crucial breathing resources of the earth and a shelter for many living creatures, the social impact of the method can be considered to be very high.

This study fuses the outputs of different DL models into an ensemble model. Hence, the ensemble model provides more potent and beneficial results than any of the single models.

The purpose of study is linked to management and policy‐making strategies, such as forest management, land use planning and sustainable management of natural resources. It aims to help prevent forest fire by taking precautions. It also aims to be helpful for authorities coping during the event of occurrence of fire.

The methodology paradigm applied here is based on knowledge‐based and analytic hierarchy process (AHP) techniques. Knowledge‐based criteria involve topographic and different themes for risk assessment. The assignment of value given to equation is significant due to its importance.

Results are in strong agreement with actual fire occurrences in the past years. The risk zones are identified according to past occurrence of fire. The gradients of low‐ to high‐risk zones are according to fuel, topographic features and weather conditions. Direction and aspect value were taken accordingly.

The paper presents forest fire risk zones designed on knowledge‐based information. Crisp and fuzzy AHP approaches were applied to improve the efficacy of the model. The mapping results were in accordance with actual fire occurrences in the past years.