Spatial Statistics and Operational Research for Wildfires Management

A special issue of Fire (ISSN 2571-6255). This special issue belongs to the section "Fire Research at the Science–Policy–Practitioner Interface".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 12043

Special Issue Editors

Department of Statistics and Operations Research, Interdisciplinary Mathematics Institute, Complutense University of Madrid, 28040 Madrid, Spain
Interests: mathematical programming; multicriteria decision making; uncertainty; decision aid models for logistics; disaster management and sustainable development
Department of Financial and Actuarial Economics and Statistics, Faculty of Economics and Business, University Complutense of Madrid, 28040 Madrid, Spain
Interests: spatial statistics; econometrics; wildfires; public policy; ecosystem services; timber production; socioeconomic patterns

Special Issue Information

Dear Colleagues,

Wildfires are the most critical hazard that threatens forest areas, causing harming people (casualties and injured), environmental damage, reducing ecosystem services, altering local lifestyle, and increasing climate change. These fires significantly impact the forest stand, which depends on the recovery effort to have similar natural quality levels as had been registered before wildfires. It supposes a significant economic endeavor to support efficient actions to regenerate the forest cycle and mitigate the effect of wildfires on biodiversity. These fires could also cause social alarm and catastrophic consequences in the affected areas and surrenders. In other words, the large forest fires cause several damages that generate social anxiety related to the uncertainty of losing their lives, properties, or lifestyle. When it is over, the newly devasted landscape changes the daily life and social-emotional status in affected areas for a considerable period until the forest is restored.

With all previous considerations, wildfire analysis will be crucial for avoiding or minimizing damage to forest areas by designing efficient actions focused on preventing or developing a fast response to extinguish it. A relevant aspect of this response is the preparedness activities, in particular the arrangement and dimensioning of the fire extinguishing means. Therefore, a continuous study is essential for better social and natural environment adaptations to reduce wildfires and burnt areas. Then, this Special Issue aims to promote the application of novelty methodologies related to spatial statistics and econometrics or operational research to provide innovative tools to policy and decision makers for designing better programs and taking actions to reduce the impact of wildfires. This framework is essential to focus public policy in the right direction to mitigate the effect of fire on natural resources and society. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Socioeconomic influence in wildfire patterns
  • Spatial Statistics and Econometrics in wildfire analysis
  • Wildfire predictions
  • Operational Research models for wildfire management
  • Preventive and mitigation actions
  • Preparedness for firefighting
  • Public policy
  • Decision Aid Models for fire suppression
  • Decision Aid Models for protecting life and assets

We look forward to receiving your contributions.

Dr. Begoña Vitoriano
Dr. Jesús Barreal
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fire is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spatial statistics
  • operational research
  • preventive actions
  • predictions
  • fire suppression
  • resources allocation
  • life and assets protection
  • public policy

Published Papers (7 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Other

24 pages, 12068 KiB  
Article
Geostatistical Modeling of Wildfire Occurrence Probability: The Case Study of Monte Catillo Natural Reserve in Italy
Fire 2023, 6(11), 427; https://doi.org/10.3390/fire6110427 - 08 Nov 2023
Viewed by 1341
Abstract
The increasing incidence of wildfires in the Mediterranean region has raised significant scientific and environmental concerns. This study focuses on a retrospective analysis of wildfire ignition and propagation within the context of the Monte Catillo Natural Reserve in Italy. After conducting a comprehensive [...] Read more.
The increasing incidence of wildfires in the Mediterranean region has raised significant scientific and environmental concerns. This study focuses on a retrospective analysis of wildfire ignition and propagation within the context of the Monte Catillo Natural Reserve in Italy. After conducting a comprehensive review of the current state-of-the-art wildfire susceptibility mapping, propagation modeling, probability assessment, forest vulnerability models, and preventive silvicultural measures, we examine the regulatory framework surrounding wildfires in the national context, with a specific focus on prevention, prediction, and active firefighting measures. A geostatistical model of wildfire occurrence was developed, starting with the characterization of the area vegetation and anthropogenic factors influencing wildfire ignition. After that, wildfire observations from the period between 2010 and 2021 were included. The objective is to generate a wildfire hazard map for two distinct vegetation communities. To accomplish this, a statistical analysis was applied using the Poisson Model, assessing its goodness-of-fit by comparing observed frequencies with experimental data through the chi-square test. In conclusion, this model serves as a valuable tool for characterizing wildfire hazards, including ignition probabilities and propagation scenarios, within the Monte Catillo Natural Reserve. The research significantly contributes to enhancing our understanding of wildfire dynamics and plays a crucial role in the development of effective strategies for wildfire risk management. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

21 pages, 6632 KiB  
Article
Spatial Dependencies and Neighbour Interactions of Wildfire Patterns in Galician Mountain Areas (NW Spain)
Fire 2023, 6(4), 165; https://doi.org/10.3390/fire6040165 - 18 Apr 2023
Viewed by 1412
Abstract
Galicia is the Spanish region most affected by wildfires, and these wildfire patterns are the object of intense research. However, within Galicia, the mountain areas have certain socioeconomic and ecological characteristics that differentiate them from the rest of the region and have thus [...] Read more.
Galicia is the Spanish region most affected by wildfires, and these wildfire patterns are the object of intense research. However, within Galicia, the mountain areas have certain socioeconomic and ecological characteristics that differentiate them from the rest of the region and have thus far not received any specific research attention. This paper proposes an analysis of the spatial wildfire patterns in the core Galician mountain systems in terms of the frequency, ratio of affected area, suppression time, and extension. The contiguity relations of these variables were examined in order to establish neighbour interactions and identify local concentrations of wildfire incidences. Furthermore, a spatial econometric model is proposed for these dependent variables in terms of a set of land cover (coniferous, transitional woodland–shrub) and land use (agricultural, industrial), complemented by population density, ecological protection, and common lands. The relevance of these parameters was studied, and it was found amongst other results, that economic value (agricultural and/or industrial) mitigates wildfire risk and impact, whereas ecological protection does not. In terms of land cover, conifers reduce the frequency and affected area of wildfires, whereas transitional land has a mixed effect, mitigating suppression time and extension but increasing the wildfire frequency. Suggestions for policy improvements are given based on these results, with a particular emphasis on the need for coordination of local policies in order to take into account the neighbour dependencies of wildfire risk and impact. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

16 pages, 2415 KiB  
Article
An Empirical Modelling and Simulation Framework for Fire Events Initiated by Vegetation and Electricity Network Interactions
Fire 2023, 6(2), 61; https://doi.org/10.3390/fire6020061 - 08 Feb 2023
Viewed by 1326
Abstract
Electrical infrastructure is one of the major causes of bushfire in Australia alongside arson and lightning strikes. The two main causes of electrical-infrastructure-initiated fires are asset failure and powerline vegetation interactions. In this paper, we focus on powerline–vegetation interactions that are caused by [...] Read more.
Electrical infrastructure is one of the major causes of bushfire in Australia alongside arson and lightning strikes. The two main causes of electrical-infrastructure-initiated fires are asset failure and powerline vegetation interactions. In this paper, we focus on powerline–vegetation interactions that are caused by vegetation falling onto or blowing onto electrical infrastructure. Currently, there is very limited understanding of both the spatio-temporal variability of these events and their causative factors. Bridging this knowledge gap provides an opportunity for electricity utility companies to optimally allocate vegetation management resources and to understand the risk profile presented by vegetation fall-in initiated fires, thereby improving both operational planning and strategic resource allocation. To bridge this knowledge gap, we developed a statistical rare-event modelling and simulation framework based on Endeavour Energy’s fire start and incident records from the last 10 years. The modelling framework consists of nested, rare-event-corrected, conditional probability models for vegetation events and consequent ignition events that provide an overall model for vegetation-initiated ignitions. Model performance was tested on an out-of-time test set to determine the predictive utility of the models. Predictive performance was reasonable with test set AUC values of 0.79 and 0.66 for the vegetation event and ignition event models, respectively. The modelling indicates that wind speed and vegetation features are strongly associated with vegetation events, and that Forest Fire Danger Index (FFDI) and soil type are strongly associated with ignition events. The framework can be used by energy utilities to optimize resource allocation and prepare future networks for climate change. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

27 pages, 363 KiB  
Article
Decision Support Models and Methodologies for Fire Suppression
Fire 2023, 6(2), 37; https://doi.org/10.3390/fire6020037 - 17 Jan 2023
Cited by 1 | Viewed by 2012
Abstract
Wildfires are recurrent natural events that have been increasing in frequency and severity in recent decades. They threaten human lives and damage ecosystems and infrastructure, leading to high recovery costs. To address the issue of wildfires, several activities must be managed and coordinated [...] Read more.
Wildfires are recurrent natural events that have been increasing in frequency and severity in recent decades. They threaten human lives and damage ecosystems and infrastructure, leading to high recovery costs. To address the issue of wildfires, several activities must be managed and coordinated in order to develop a suitable response that is both effective and affordable. This includes actions taken before (mitigation, prevention, and preparedness), during (response), and after the event (recovery). Considering the available resources and the safety of the involved personnel is a key aspect. This article is a review focused on fire suppression, which comprises actions belonging to the preparedness phase (deployment) and the response phase (dispatching) of the wildfire management scheme. It goes through the models and methodologies that, applying operations research and optimization techniques, address the management of resources to address fire suppression. This article presents a review of the studies published after the last review on the topic in 2017, but also includes some interesting papers before that date. It concludes with some classifying tables and a few conclusions about possible future lines of research. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
14 pages, 2030 KiB  
Article
Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China
Fire 2022, 5(6), 215; https://doi.org/10.3390/fire5060215 - 14 Dec 2022
Cited by 4 | Viewed by 2942 | Correction
Abstract
Control of forest fire ignition sources is the top priority in fire management practices. China has gained great success in reducing forest fires in recent years, and the relevant safety measures taken during this process are worthy of investigation and publicity. Based on [...] Read more.
Control of forest fire ignition sources is the top priority in fire management practices. China has gained great success in reducing forest fires in recent years, and the relevant safety measures taken during this process are worthy of investigation and publicity. Based on fire statistical data through the years between 2003 and 2017, we analyzed the detailed classification of fire ignition sources and their contribution to the annual forest fire occurrence. The role of different ignition sources in altering fire occurrence was quantified and ranked by defining a contribution extent parameter. A statistical tool was also applied to conduct correlation analysis to identify variation patterns of time series data from individual fire causes. The annual fire numbers declined after 2008 and stabilized at a level < 2000 in recent years, pointing to the containment of several major ignition sources. Starting from the legislative development, an accountability system was established at all levels from administrative heads to local residents, paving the way for the multifaceted and full-coverage fire prevention publicity and education as well as the fire use restriction in particular seasons. The effectiveness of management measures in lessening forest fire occurrence was interpreted using the results of correlation analysis among the fire numbers initiated by individual ignition sources. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

22 pages, 8562 KiB  
Article
Chromatic Coding (ConForest_RGB) for the Detection of Spatial-Temporal Patterns in Collective Lands in Galicia (Spain)
Fire 2022, 5(6), 179; https://doi.org/10.3390/fire5060179 - 31 Oct 2022
Viewed by 1097
Abstract
In the scientific literature, numerous different analyses have been reported on forest fires, in a constant effort to predict their behavior and occurrence. It is known that a variety of factors come together in these events: climatic, physiographic, socioeconomic and territorial, among others. [...] Read more.
In the scientific literature, numerous different analyses have been reported on forest fires, in a constant effort to predict their behavior and occurrence. It is known that a variety of factors come together in these events: climatic, physiographic, socioeconomic and territorial, among others. However, although forest fires have a significant relationship with social conflict, this aspect has not been sufficiently studied. This aspect is particularly important in regions such as Galicia (Northwest Spain), where forest fires, either intentional or related to human activity, account for up to 95% of the total annual number of fires. As a measure of this social conflict, in this article, we compile the court sentences and newspaper reports, in which the montes vecinales en mano común VMC) of Galicia (a special type of property and tenure right) have been involved, which allows us to elaborate a chromatic coding that relates the three factors and allows us to detect spatio-temporal patterns. The resulting coding is a grid made up of 3034 rows and 15 columns, in which the color of each cell indicates the relationship between fires, newspaper reports, and court rulings. This coding also makes it possible to detect differences between the geographical sectors considered, which helps to detect spatio-temporal patterns and facilitates the implementation of specific prevention policies for each geographical sector. Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

Other

Jump to: Research

2 pages, 508 KiB  
Correction
Correction: Wang et al. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215
Fire 2023, 6(3), 80; https://doi.org/10.3390/fire6030080 - 21 Feb 2023
Viewed by 779
Abstract
In the original publication [...] Full article
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)
Show Figures

Figure 1

Back to TopTop