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In Portugal, the rapid growth in housing in and near wildland-urban interfaces (WUIs) increases the wildfire risk to lives and structures. The goal of our study was to assess wildfire hazard in the Central Region of Portugal and in the contact areas of the 60,373 km of WUIs existing in the study area. The degree to which wildfire is a hazard to the...
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... line with these maps, the WUI is defined as an area where structures and wildland vegetation are in direct contact or in close proximity, separated by a clearly defined boundary [43], defined as the perimeter (or the segment) of the built-up area. In order to introduce detail to the interfaces identified in the aforementioned products, we decided to reorder it in only 4 types of infrastructure (Table 2), although in this work, only continuous built-up areas, discontinuous built-up areas, and industrial areas were incorporated, as they are more sensitive to the loss of people and goods. ...Similar publications
In Portugal, as in other parts of the world, the rapid growth of housing in and near the wildland–urban interface (WUI) increases the wildfire risk to lives and structures. To reduce this risk, it is necessary to identify WUI housing areas that are more susceptible to fire. The goal of our study was to assess wildfire hazard in the Central Region o...
Citations
... The hazard assessment was based on the methodology used in the work by Nunes et al. [45] and involved the following steps: (i) assessing susceptibility, using the slope, altitude, and land use and occupation variables, (ii) calculating probability based on the areas burnt between 1975 and 2020, and (iii) calculating hazard by multiplying susceptibility by probability. The validation process was supported by the ArcSDM toolbox, ArcGIS 10, which helped calculate the AUC (area under the curve). ...
... When the preponderance of coniferous and eucalyptus forests with high combustibility and flammability [57] is combined with steep slopes, the rapid progression of flames is assured. A number of authors confirm that areas occupied by coniferous forests and scrubland are the most prone to fire [45,58,59] compared to other uses of the land, notably agricultural. In fact, the very low and low wildfire hazard classes are dominant where agriculture is the most widespread land use. ...
... In fact, the very low and low wildfire hazard classes are dominant where agriculture is the most widespread land use. The less fire-proneness of agricultural areas has been recognised in several works in different geographical areas [45,[58][59][60][61] where farmland around isolated houses and villages can act as a buffer zone against wildfires. This only fails in the case of extreme wildfire events when fire selectivity in specific land cover types is drastically reduced [62,63]. ...
In recent decades, wildfires have become common disasters that threaten people’s lives and assets, particularly in wildland–urban interfaces (WUIs). Developing an effective evacuation strategy for a WUI presents challenges to emergency planners because of the spatial variations in biophysical hazards and social vulnerability. The aim of this study was to map priority WUIs in terms of evacuation. The factors considered were the seriousness of the risk of wildfire exposure, and the population centres whose greatest constraints on the evacuation process stemmed from the nature of the exposed population and the time required to travel to the nearest shelter/refuge. An integrated framework linking wildfire hazard, social vulnerability, and the time taken to travel by foot or by car to the nearest refuge/shelter was applied. The study area includes two municipalities (Lousã and Sertã) in the mountainous areas of central Portugal that are in high-wildfire-risk areas and have very vulnerable and scattered pockets of exposed population. The combination of wildfire risk and travelling time to the nearest shelters made it possible to identify 20% of the WUIs that were priority areas for evacuation in the case of Sertã. In the case of Lousã, 3.4% were identified, because they were highly exposed to wildfire risk and had a travelling time to the nearest shelter of more than 15 min on foot. These results can assist in designing effective pre-fire planning, based on fuel management strategies and/or managing an effective and safe evacuation.
... These exposures directly concern human life and the safety of property. While foundational research exists in risk prediction and exposure analysis, a lack of information remains: (1) Most current research treats exposure as a one-dimensional factor in disaster hazard [27,28] and vulnerability assessments [29][30][31], typically in non-disaster contexts. This approach does not address the risk analysis of exposures during the active spread of a wildfire. ...
This study focuses on constructions that are vulnerable to fire hazards during wildfire events, and these constructions are known as ‘exposures’, which are an increasingly significant area of disaster research. A key challenge lies in estimating dynamically and comprehensively the risk that individuals are exposed to during wildfire spread. Here, ‘exposure risk’ denotes the potential threat to exposed constructions from fires within a future timeframe. This paper introduces a novel method that integrates a spatiotemporal knowledge graph with wildfire spread data and an exposure risk analysis model to address this issue. This approach enables the semantic integration of varied and heterogeneous spatiotemporal data, capturing the dynamic nature of wildfire propagation for precise risk analysis. Empirical tests are employed for the study area of Xichang, Sichuan Province, using real-world data to validate the method’s efficacy in merging multiple data sources and enhancing the accuracy of exposure risk analysis. Notably, this approach also reduces the time complexity from O (m×n×p) to O (m×n).
... The growing problem of WUI fires highlights the need to develop methodologies for defining and mapping them. Numerous methodologies from academic field have emerged, considering different criteria to define the WUI using land cover maps, remote sensing data, satellite images, GIS tools, and population census data, primarily in the USA (Radeloff et al., 2005;Bar Massada et al., 2013) in Spain (Caballero, 2008;Alcasena et al., 2018), in France (Lampin-Maillet et al., 2010, Italy (Sirca et al., 2017), Greece (Mitsopoulos et al., 2020;Bachantourian et al., 2023), Portugal (Andrada et al., 2023;Nunes et al., 2023), Chile (Miranda et al., 2020;Sarricolea et al., 2020), and Argentina (Argañaraz et al., 2017;Godoy et al., 2019;Sanucci et al., 2022). For example, in the USA, two criteria are used to define the WUI: the density of homes and vegetation cover, resulting in three interface types (Radeloff et al., 2005), whereas, in France, Lampin-Maillet et al. (2010) propose the combination of a metric aggregation of vegetation (three classes) and density of homes (four classes) resulting in 12 interface types. ...
In recent decades, the risk of Wildland-Urban Interface (WUI) fires has increased due to urban growth, particularly in regions with a Mediterranean climate. The identification of the WUI is crucial for formulating fire prevention and management measures. However, there is no unified methodology for defining the WUI and it is not clear if proposals that emerge from scientific research are implemented by fire management agencies. Our objectives were to identify, describe, and compare the methods and criteria used by land and fire management agencies to define the WUI in Mediterranean-climate countries. We conducted a review of laws and fire prevention and management plans and protocols on the official websites of administrative bodies and agencies of the USA, Spain, Portugal, France, Italy, Greece, South Africa, Australia, Chile, and Argentina. Each document was read and analyzed and we conducted searches for the terminology used to name the WUI, the methodology and criteria used for defining the WUI, the fire prevention and management actions implemented in the WUI, the level of territorial organization and the responsible agencies for implementing the actions, and the presence of a methodology and a map at national scale. We found no consensus on the terminology for the WUI, the most common terms used being: wildland-urban interface, urban-rural interface, and urban-forest interface. With the exception of the USA and Portugal, there is no unified methodology at the national scale. We identified three general methods for defining the WUI: considering buffer distance for urban and vegetation areas (USA, Italy, Chile, South Africa), employing networks of strips (Spain, Portugal), and delineating risk-prone zones (Australia, France). All countries undertake fire prevention actions (e.g., fuel reduction and firebreak creation) often implemented at the municipal level. There is almost no interaction between academia and fire management agencies. Our review addresses the gap in the methods to define the WUI effectively implemented by fire management agencies. We highlight the need to implement actions aimed at enhancing the interaction between fire scientists and fire managers, which is essential for formulating and implementing effective strategies for fire prevention and optimizing resources.
... A review of the existing literature on wildfire risk assessment reveals a wide variety of approaches, such as multicriteria decision analysis (Nuthammachot & Stratoulias, 2021), fire modelling systems (Alcasena et al., 2021), contingent valuation (Molina, Moreno, Castillo, & Rodríguez y Silva, 2018), expert analysis (Alcasena, Salis, Ager, Castell, & Vega-García, 2017), social network analysis (Ager, Kline, & Fischer, 2015) and social media data analysis (Yue, Dong, Zhao, & Ye, 2021). However, risk mitigation strategies are mostly focused on protecting human lives and securing infrastructure at the wildland-urban interface (El Ezz, Boucher, Cotton-Gagnon & Godbout, 2022;Nunes, Figueiredo, Pinto & Lourenço, 2023), thus neglecting the importance of ecosystem services to the population's well-being. Although quantifying the risk of losing ecosystem services is critical in guiding effective management and policy interventions, it is still challenging (Lecina-Diaz, Martínez-Vilalta, Alvarez, Vayreda, & Retana, 2021). ...
... However, changes in land use in recent years [5,6] involving the abandonment of rural agricultural lands [7] because of countryside depopulation [8], mainly in mountainous areas [9], have caused fuel to accumulate and form seamless stands in areas with former lower fuel loads [10]. These dynamics increased fire hazards and thus ignition probability and resistance to fire control, particularly near the wildland-urban interface (WUI) [11][12][13][14]. ...
This study explored, for the first time, the drivers shaping large fire size and high severity of forest fires classified as level-2 in Spain, which pose a great danger to the wildland–urban interface. Specifically, we examined how bottom-up (fuel type and topography) and top-down (fire weather) controls shaped level-2 fire behavior through a Random Forest classifier at the regional scale in Galicia (NW Spain). We selected for this purpose 93 level-2 forest fires. The accuracy of the RF fire size and severity classifications was remarkably high (>80%). Fire weather overwhelmed bottom-up controls in controlling the fire size of level-2 forest fires. The likelihood of large level-2 forest fires increased sharply with the fire weather index, but plateaued at values above 40. Fire size strongly responded to minimum relative humidity at values below 30%. The most important variables explaining fire severity in level-2 forest fires were the same as in the fire size, as well as the pre-fire shrubland fraction. The high-fire-severity likelihood of level-2 forest fires increased exponentially for shrubland fractions in the landscape above 50%. Our results suggest that level-2 forest fires will pose an increasing danger to people and their property under predicted scenarios of extreme weather conditions.
... Forest fire hazards refer to the possibility of a disaster causing adverse effects, and the core is the degree of disaster-causing activity [21][22][23]. Generally, the forest fire intensity combines the two characteristics of fuel consumption and the forest fire spread speed to provide key information on forest fire behavior that may occur in different areas; this index is commonly used to measure fire hazards [24]. ...
Objective: This study established an index system for assessing forest fire spread hazards and conducted a forest fire spread hazard assessment in the mountainous district of Beijing (including Fangshan, Mentougou, Changping, Yanqing, Huairou, Miyun, and Pinggu). The relationship between forested landscape spatial pattern and forest fire spread hazard was explored; this method provided the basis for the establishment of a landscape forest fire security guarantee system. Methods: The forest fire spread hazard assessment index system was constructed from four aspects: forest fuel, meteorological factors, topographic factors, and fire behavior. The weighted comprehensive evaluation method and area-weighted average method were used to calculate the forest fire spread hazard indices at the subcompartment scale and township scale. Moran’s I index was selected as the spatial autocorrelation index to analyze the autocorrelation degree and spatial distribution of the forest fire spread hazard index. Eleven representative landscape pattern indices were selected to analyze the main landscape spatial pattern affecting forest fire spread hazard by correlation analysis and principal component analysis. Results: (1) The areas with high, medium–high, medium-low, and low forest fire spread hazard grades accounted for 39.87%, 33.10%, 11.37%, and 15.66% of the study area, respectively, at the subcompartment scale and for 52.36%, 22.58%, 18.39%, and 6.67% of the study area, respectively, at the township scale. (2) The forest fire spread hazard index results obtained at the subcompartment and township scales in the Mountainous District of Beijing showed a spatial agglomeration distribution law. (3) The forest fire spread hazard was influenced mainly by landscape diversity (SHDI and PRD), landscape aggregation (AI, CONTAG, and PD), and landscape area (TA). Conclusions: The overall forest fire spread hazard in the mountainous district of Beijing showed a gradual increase from plains to mountainous areas. The land types of the high-spread hazard subcompartment mainly included general shrubbery and coniferous forestlands, and the dominant species in the high-spread hazard arbor forest subcompartment were mainly Platycladus orientalis, Pinus tabuliformis, and Quercus mongolica.
... Thus, the WUI in Central Portugal is 60,373 km long [59], 15,000 km of which are builtup areas in direct contact with fuel. The predominant typology is discontinuous built-up area (80.6%), followed by continuous built-up area (13.1%) and industry (6.3%). ...
... In Portugal, WUIs are expanding [86] as a result of the increasing mix of urban settlements and woodland mainly due to (i) urbanised areas expanding into forest areas and (ii) woodland/scrubland colonizing rural areas as a result of rural abandonment and depopulation [59,87,88]. These changes in the vicinity of WUI areas have contributed to a large amount of fuel build-up as a result of the increase of forest and shrubland areas [88]. ...
... In fact, fuel in direct contact with the urban and industrial areas was the most important criterion highlighted by the experts concerned, especially when scrub and woodland dominate. A study carried out by Nunes et al. [59] found that scrubland and pinewood are the most common fuels in direct contact with the build-up in the Central Region of Portugal, meaning that these WUIs are more prone to fire in comparison to areas in which cropland and broadleaf forests predominate [61][62][63], since they can act as protective buffer against wildfires [50,59]. ...
Vulnerability assessment is a vital component of wildfire management. This research focuses on the evaluation of wildfire vulnerability in the Central Region of Portugal, an area historically affected by catastrophic fire events. The overall methodology entailed applying an analytical hierarchy process (AHP) to the relevant spatial variables for evaluating vulnerability associated with exposure, sensitivity, and response capacity at landscape and the wildland–urban interface (WUI) scale. Of the selected criteria, the existence of fuel in direct contact with built-up areas, population density, and firefighters’ travel time were considered the most important criteria for inclusion in the vulnerability map. At landscape scale, 31% of the Central Region presents high and very high classes of vulnerability, while 22% of WUIs are classified as highly vulnerable to fire. Although the inland areas emerge as the most vulnerable, this approach enables scattered vulnerable hotspots to be identified in almost all of the Central Region. The results could be very helpful in terms of developing and enhancing local policies to mitigate human and material damage.
The 2017 fires in Portugal strongly marked civil society, proving to be one of the deadliest in the country`s history,
resulting in the loss of 117 lives and very significant damage to homes, businesses and ecosystems. These events
underlined the urgent need to promote a culture of risk prevention in communities, especially rural communities. Thus,
with this purpose, the programs Safe Village, Safe People were created.
This work aims to explain the experience in implementing the Safe Village, Safe People programs, focusing on the
expertise developed by the Municipality of Ansião in the Village of Vale Florido. And, in particular, identify the obstacles encountered, strengths, weaknesses, difficulties and future perspectives for these programs. Finally, some
recommendations will be presented to effectively improve the implementation of the Safe Village, Safe People
programs. Methodologically, the collection of testimonies from the Municipal Civil Protection services of Ansião began,
in order to identify the main challenges that arise in the implementation of the ASPS programs in the first person.
This work's results, based on the municipalities experience in implementing ASPS, demonstrate the importance of a
community-centered approach. By involving local residents, municipalities can effectively develop a culture of proximity
between communities and civil protection. The involvement of Presidents of the Parish Council, due to its proximity to
the populations, proved to have a primary role in the adherence of the population to the program. The results also
highlight the need for continuous evaluation and adaptation of these programmes to ensure their long-term effectiveness
and to make them flexible in the face of new societal challenges. Ultimately, the success of these initiatives depends to
a large extent on the commitment and collaboration of all: rural communities and civil protection agents.
