Special Issue "Dynamic Modelling and Risk Assessment of Wildfire"

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Quantitative Methods and Remote Sensing".

Deadline for manuscript submissions: closed (30 October 2019).

Special Issue Editor

Prof. Marcos Rodrigues

Guest Editor
Department of Agricultural andForest Engineering, Universitat de Lleida, Lleida, Spain
Interests: wildfire modeling; post-fire response; GIS; remote sensing

Special Issue Information

Dear Colleagues,

Wildfires are a major and recurrent threat to valued forest resources and assets resulting from complex interactions and synergies between humans and landscape. Wildfire modeling is currently a mature discipline in which a large number of approaches have been developed, from ‘static’ models based on long-term historical fire data to operational simulations and forecasts.
Science-based decision-making requires reliable and accurate inputs in order to provide effective recommendations. The most recent developments are clearly influenced by the increasing availability of information. We find examples of this in the massive availability of remote sensing imagery, weather models and other highly precise sources such as LiDAR point clouds. Despite the challenge of managing such a huge amount of information, the current situation regarding data inputs and techniques opens the door to the development of dynamic models, conducive to the simulation and forecast of processes related to fire.
The present Special Issue will comprise a selection of papers dealing with non-stationary modeling approaches of wildfire, paying special attention to fire risk. This includes (but it is not limited to) empirical models or simulations of hazard probability, fire danger, propagation, vulnerability, exposure assessments or post-fire response. Original works and reviews are both welcome.

Prof. Marcos Rodrigues
Guest Editor

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 papers will be 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. Forests 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 1800 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

  • forest fire
  • risk
  • model
  • forecast
  • simulation
  • danger
  • exposure
  • propagation
  • fuel
  • post-fire response

Published Papers (3 papers)

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Research

Open AccessArticle
The Interaction of Wildfire Risk Mitigation Policies in the Presence of Spatial Externalities and Heterogeneous Landowners
Forests 2020, 11(1), 15; https://doi.org/10.3390/f11010015 - 19 Dec 2019
Abstract
The dramatic increase in the number of uncontrollable wildfires in the United States has become an important policy issue as they threaten valuable forests and human property. The derived stochastic dynamic model of this study is capable of determining optimal fuel treatment timing [...] Read more.
The dramatic increase in the number of uncontrollable wildfires in the United States has become an important policy issue as they threaten valuable forests and human property. The derived stochastic dynamic model of this study is capable of determining optimal fuel treatment timing and level simultaneously and as a function of fire risk and fuel biomass dynamics. This study develops a stochastic dynamic model to evaluate the interaction of fuel treatment decisions for two adjacent landowners under various scenarios of misinformation about fire occurrence and spread. Findings indicate that a landowner tends to free ride on fuel treatment undertaken by his adjacent landowner. However, the study finds that the free riding potential of a landowner could be alleviated to some extent by having a neighboring landowner who is aware of fire spillover effects. In addition, the study reveals that the social cost resultant from free riding behavior is lower that the social cost associated with complete absence of fire externality awareness for both landowners. These findings imply that governments could introduce more effective educational programs to ensure that all landowners are fully aware of cross-parcel benefits of fuel treatment in order to align socially and privately optimal decisions, thus minimizing externality costs. Full article
(This article belongs to the Special Issue Dynamic Modelling and Risk Assessment of Wildfire)
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Open AccessArticle
Modeling the Influence of Eucalypt Plantation on Wildfire Occurrence in the Brazilian Savanna Biome
Forests 2019, 10(10), 844; https://doi.org/10.3390/f10100844 - 27 Sep 2019
Abstract
In the last decades, eucalypt plantations are expanding across the Brazilian savanna, one of the most frequently burned ecosystems in the world. Wildfires are one of the main threats to forest plantations, causing economic and environmental loss. Modeling wildfire occurrence provides a better [...] Read more.
In the last decades, eucalypt plantations are expanding across the Brazilian savanna, one of the most frequently burned ecosystems in the world. Wildfires are one of the main threats to forest plantations, causing economic and environmental loss. Modeling wildfire occurrence provides a better understanding of the processes that drive fire activity. Furthermore, the use of spatially explicit models may promote more effective management strategies and support fire prevention policies. In this work, we assessed wildfire occurrence combining Random Forest (RF) algorithms and cluster analysis to predict and detect changes in the spatial pattern of ignition probability over time. The model was trained using several explanatory drivers related to fire ignition: accessibility, proximity to agricultural lands or human activities, among others. Specifically, we introduced the progression of eucalypt plantations on a two-year basis to capture the influence of land cover changes over fire likelihood consistently. Fire occurrences in the period 2010–2016 were retrieved from the Brazilian Institute of Space Research (INPE) database. In terms of the AUC (area under the Receiver Operating Characteristic curve), the model denoted fairly good predictive accuracy (AUC ≈ 0.72). Results suggested that fire occurrence was mainly linked to proximity agricultural and to urban interfaces. Eucalypt plantation contributed to increased wildfire likelihood and denoted fairly high importance as an explanatory variable (17% increase of Mean Square Error [MSE]). Nevertheless, agriculture and urban interfaces proved to be the main drivers, contributing to decreasing the RF’s MSE in 42% and 38%, respectively. Furthermore, eucalypt plantations expansion is progressing over clusters of high wildfire likelihood, thus increasing the exposure to wildfire events for young eucalypt plantations and nearby areas. Protective measures should be focus on in the mapped Hot Spot zones in order to mitigate the exposure to fire events and to contribute for an efficient initial suppression rather than costly firefighting. Full article
(This article belongs to the Special Issue Dynamic Modelling and Risk Assessment of Wildfire)
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Open AccessArticle
Peatland Hydrological Dynamics as A Driver of Landscape Connectivity and Fire Activity in the Boreal Plain of Canada
Forests 2019, 10(7), 534; https://doi.org/10.3390/f10070534 - 26 Jun 2019
Cited by 5
Abstract
Drought is usually the precursor to large wildfires in northwestern boreal Canada, a region with both large wildfire potential and extensive peatland cover. Fire is a contagious process, and given weather conducive to burning, wildfires may be naturally limited by the connectivity of [...] Read more.
Drought is usually the precursor to large wildfires in northwestern boreal Canada, a region with both large wildfire potential and extensive peatland cover. Fire is a contagious process, and given weather conducive to burning, wildfires may be naturally limited by the connectivity of fuels and the connectivity of landscapes such as peatlands. Boreal peatlands fragment landscapes when wet and connect them when dry. The aim of this paper is to construct a framework by which the hydrological dynamics of boreal peatlands can be incorporated into standard wildfire likelihood models, in this case the Canadian Burn-P3 model. We computed hydrologically dynamic vegetation cover for peatlands (37% of the study area) on a real landscape in the Canadian boreal plain, corresponding to varying water table levels representing wet, moderate, and severely dry fuel moisture and hydrological conditions. Despite constant atmospheric drivers of fire spread (air temperature, humidity, and wind speed) between drought scenarios, fire activity increased 6-fold in moderate drought relative to a low drought baseline; severe (1 in 40 years) drought scenarios drove fires into previously fire-restrictive environments. Fire size increased 5-fold during moderate drought conditions and a further 20–25% during severe drought. Future climate change is projected to lead to an increase in the incidence of severe drought in boreal forests, leading to increases in burned area due to increasing fire frequency and size where peatlands are most abundant. Future climate change in regions where peatlands have historically acted as important barriers to fire spread may amplify ongoing increases in fire activity already observed in Western North American forests. Full article
(This article belongs to the Special Issue Dynamic Modelling and Risk Assessment of Wildfire)
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