Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression

Oliveira, Sandra; Pereira, José M. C.; San-Miguel-Ayanz, Jesús; Lourenço, Luciano

doi:10.1016/j.apgeog.2014.04.002

Cited by 126 publications

(90 citation statements)

References 58 publications

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“…"Arrolamento Geral de Gados e Animais de Capoeira" : 1934, 1955and 1970"Recenseamento Agrícola do Continente": 1989, 1999, Instituto Nacional de Estatística of the Piodão and Pomares parishes, respectively) ( Figure 7). Several studies confirm that this land cover is one of the types most seriously affected by wildfires (Nunes et al 2005;Sebastián-López et al 2008;Catry et al 2009;Moreira et al 2009;Bajocco and Ricotta 2008;Nunes 2012;Carmo et al 2011;Oliveira et al 2012;Ganteaume and Jappiot, 2013;Oliveira 2014;Nunes et al 2016). Conversely, Nunes et al (2016) found that in Portugal at municipal level, traditional activities based on agriculture, grazing and forestry seem to reduce the burnt area, suggesting that the survival of Mediterranean silvopasture activities reduces the frequency and impact of forest fires.…”

Section: Social and Economic Changesmentioning

confidence: 96%

Increased vulnerability to wildfires and post fire hydro-geomorphic processes in Portuguese mountain regions: what has changed?

Nunes

Lourenço

2017

Open Agriculture

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Open Agriculture. 2017; 2: 70-82 restored to improve the capacity to cope with this high susceptibility to hazards. Keywords:Wildfires; Flash floods; Erosive processes; social and ecological vulnerability; Mountains of Central Portugal IntroductionMountain areas are vital and complex systems that provide biodiversity, water resources, valuable habitats, energy, fresh air and recreational sites, and are also part of our cultural heritage. According to Hewitt (1997), since the last century mountains have become increasingly hazard-prone areas and a high number of disasters occur there, in comparison to other environments. In the mountainous regions of the Mediterranean basin, where forest fires have been increasing (JRC 2005), flash-floods and intensive erosion processes seem to have become more regular, since the climate is characterized by heavy rainfall due to deep, intense cyclones (Jansa et al. 2014) and a complex topography. In fact, mountain regions are much more geophysically and hydrologically active in comparison to lowland areas. A better understanding of hazards and consequent disasters must therefore be based on knowledge of the bio-geophysical conditions and human dimensions (Blaikie et al. 1994;Klinenberg 2002).In Portuguese mountain areas, as in other Mediterranean countries, socioeconomic development has been affected by physical constraints, an inadequate road network, lack of industry, limitations on trade, reduced competitiveness and lack of tourism facilities. As a result, there has been an ongoing process of population migration in recent decades, which has increased demographic and structural problems and farmland abandonment. These changes are frequently followed by DOI 10.1515DOI 10. /opag-2017 Received December 11, 2016; accepted February 15, 2017 Abstract: The main objectives of this study were to understand the frequency of forest fires, post-fire off-site hydrological response and erosional processes from a social and ecological perspective in two basins located in the central cordillera, Portugal. It also discusses the driving forces that contribute towards increasing the social-ecological vulnerability of systems in the face of hazards and emphasizes the importance of learning from disasters. Based on the historical incidence of wildfires, it is possible to identify several areas affected by two, three or four fires, since 1975. Following the two major fires, in 1987 and 2005, flash floods, intense soil erosion and sedimentation processes were generated, causing severe damage. Significant socioeconomic, political and ecological changes have been affecting mountain regions in the last decades. Approximately 80% of the population and more than 90% of the livestock have disappeared, common lands have been afforested with Pinus pinaster, and several agricultural plots have been abandoned. These factors have all contributed towards creating non-or submanaged landscapes that have led to a dramatic increase in the magnitude and frequency of wildfires and to post-fire hydrological and ...

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Section: Social and Economic Changesmentioning

confidence: 96%

Increased vulnerability to wildfires and post fire hydro-geomorphic processes in Portuguese mountain regions: what has changed?

Nunes

Lourenço

2017

Open Agriculture

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“…Usually, lower elevation (Kalabokidis et al 2007;Sebastián-López et al 2008;Kwak et al 2012;Narayanaraj and Wimberly 2012;Liu and Wimberly 2015) and smaller slope gradient (Preisler et al 2004;Syphard et al 2008;Dondo Bühler et al 2013;Oliveira et al 2014;Argañaraz et al 2015) increase HCF occurrence. Since surface temperature and humidity are affected by terrain, these may be reflecting climatic conditions.…”

Section: Predictors For Long-term Studiesmentioning

confidence: 99%

Human-caused fire occurrence modelling in perspective: a review

Costafreda-Aumedes

Comas

Vega‐García

2017

Int. J. Wildland Fire

133

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Abstract. The increasing global concern about wildfires, mostly caused by people, has triggered the development of human-caused fire occurrence models in many countries. The premise is that better knowledge of the underlying factors is critical for many fire management purposes, such as operational decision-making in suppression and strategic prevention planning, or guidance on forest and land-use policies. However, the explanatory and predictive capacity of fire occurrence models is not yet widely applied to the management of forests, fires or emergencies. In this article, we analyse the developments in the field of human-caused fire occurrence modelling with the aim of identifying the most appropriate variables and methods for applications in forest and fire management and civil protection. We stratify our worldwide analysis by temporal dimension (short-term and long-term) and by model output (numeric or binary), and discuss management applications. An attempt to perform a meta-analysis based on published models proved limited because of non-equivalence of the metrics and units of the estimators and outcomes across studies, the diversity of models and the lack of information in published works.

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“…Topography is considered to be an important factor that influences forest fires because topographic properties affect distributions of vegetation and local climate such as wind speeds [11,12,31,32]. Therefore, a Digital Elevation Model (DEM) was generated using national topographic maps at a scale of 1:25,000.…”

Section: Fire Ignition Factorsmentioning

confidence: 99%

Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression

et al. 2016

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Abstract:The Cat Ba National Park area (Vietnam) with its tropical forest is recognized as being part of the world biodiversity conservation by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and is a well-known destination for tourists, with around 500,000 travelers per year. This area has been the site for many research projects; however, no project has been carried out for forest fire susceptibility assessment. Thus, protection of the forest including fire prevention is one of the main concerns of the local authorities. This work aims to produce a tropical forest fire susceptibility map for the Cat Ba National Park area, which may be helpful for the local authorities in forest fire protection management. To obtain this purpose, first, historical forest fires and related factors were collected from various sources to construct a GIS database. Then, a forest fire susceptibility model was developed using Kernel logistic regression. The quality of the model was assessed using the Receiver Operating Characteristic (ROC) curve, area under the ROC curve (AUC), and five statistical evaluation measures. The usability of the resulting model is further compared with a benchmark model, the support vector machine (SVM). The results show that the Kernel logistic regression model has a high level of performance in both the training and validation dataset, with a prediction capability of 92.2%. Since the Kernel logistic regression model outperforms the benchmark model, we conclude that the proposed model is a promising alternative tool that should also be considered for forest fire susceptibility mapping in other areas. The results of this study are useful for the local authorities in forest planning and management.

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Exploring the spatial patterns of fire density in Southern Europe using Geographically Weighted Regression

Cited by 126 publications

References 58 publications

Increased vulnerability to wildfires and post fire hydro-geomorphic processes in Portuguese mountain regions: what has changed?

Increased vulnerability to wildfires and post fire hydro-geomorphic processes in Portuguese mountain regions: what has changed?

Human-caused fire occurrence modelling in perspective: a review

Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression

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