Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)

San-Miguel-Ayanz, Jesús; Schulte, E.; Schmuck, G.; Camia, Andrea; Strobl, Peter; Giorgio, Liberta'; Giovando, Cristiano; Roberto, Boca; Sedano, Fernando; Kempeneers, Pieter; McInerney, Daniel; Withmore, Ceri; Oliveira, Sandra; Rodrígues, Marcos; Durrant, Tracy Houston; Corti, Paolo; Oehler, Friderike; Vilar, Lara; Amatulli, Giuseppe

doi:10.5772/28441

Cited by 213 publications

(174 citation statements)

References 23 publications

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“…In the last decades, Europe registered a high number of fires (hereafter, NF) and burnt area (hereafter, BA) with different spatial and temporal trends as the result of human-driven fuel transformations and climate change (Fernandes, 2013;Pereira et al, 2013Pereira et al, , 2014San-Miguel-Ayanz et al, 2016;Vilar et al, 2016). The society and the scientific community regard this phenomenon as a natural ecological factor and, at least in some cases, a natural/human disaster (Nunes et al, 2016;Vilar et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Negligent and intentional fires in Portugal: Spatial distribution characterization

Parente

Pereira

Amraoui

et al. 2018

Science of The Total Environment

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In the European context, Portugal is the country with the highest number of wildfires and the second with more burnt area. The vast majority of these events are of human origin, whether caused by accident, negligence or arson, reason why it is particularly important to know the regime of these wildfires for forest and wildfire management activities. The study focuses on the most recent years of 2001-2014, when wildfire ignition's coordinates are known, and aims to identify and characterize the wildfire incidence spatial patterns of variability as well as their main drivers. After grouping wildfires with human cause into negligent and intentional, we studied their spatial distribution in terms of normalized number of wildfires (NNF) and burnt area (NBA) in the five Nomenclature of Territorial Units for Statistics II regions of mainland Portugal. Results disclose an uneven spatial distribution of the fire incidence, characterized by a south-north gradient, much higher values in Norte region and more evident for intentional than for negligent wildfires. Human and biophysical drivers strongly influence NNF and NBA, at regional and national scales. Distribution patterns at regional scale, for negligent and intentional wildfires are quite different from entire mainland and all wildfires. Drivers' influence is higher for intentional than for negligent wildfires, for southern than for northern regions and for NBA than for NNF. The leading drivers of NNF are distance to roads (d) population density (pd) and altitude (h) while of NBA are h, d, slope and pd, and this influence is higher for intentional than for negligent wildfires.

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Section: Introductionmentioning

confidence: 99%

Negligent and intentional fires in Portugal: Spatial distribution characterization

Parente

Pereira

Amraoui

et al. 2018

Science of The Total Environment

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“…The system provides information to over 30 countries in the European and Mediterranean regions, to the aim of harmonising the prevention and fire fighting [1].…”

Section: The European Forest Fire Information System (Effis)mentioning

confidence: 99%

“…Wildfire information has been collected in Europe for a long time, with particular focus on forest fires. The European Forest Fire Information System (EFFIS) of the European Commission complements and harmonises the information collected by member countries and covers the forest fire management cycle [1]. Analysis and prediction of wildfire propagation is growingly supported by computational modelling.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Data Driven Ensemble for Wildfire Behaviour Assessment: A Case Study

Leo

Rigo

Rodriguez-Aseretto

et al. 2013

IFIP Advances in Information and Communication Technology

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Abstract. Wildfire information has long been collected in Europe, with particular focus on forest fires. The European Forest Fire Information System (EFFIS) of the European Commission complements and harmonises the information collected by member countries and covers the forest fire management cycle. This latter ranges from forest fire preparedness to post-fire impact analysis. However, predicting and simulating fire event dynamics requires the integrated modelling of several sources of uncertainty. Here we present a case study of a novel conceptualization based on a Semantic Array Programming (SemAP) application of the Dynamic Data Driven Application Systems (DDDAS) concept. The case study is based on a new architecture for adaptive and robust modelling of wildfire behaviour. It focuses on the module for simulating wildfire dynamics under fire control scenarios. Rapid assessment of the involved impact due to carbon emission and potential soil erosion is also shown. Uncertainty is assessed by ensembling an array of simulations which consider the uncertainty in meteorology, fuel, software modules. The event under investigation is a major wildfire occurred in 2012, widely reported as one of the worst in the Valencia region, Spain. The inherent data, modelling and software uncertainty are discussed and preliminary results of the robust data-driven ensemble application are presented. The case study suitably illustrates a typical modelling context in many European areas -for which timely collecting accurate local information on vegetation, fuel, humidity, wind fields is not feasible -where robust and flexible approaches may prove as a viable modelling strategy.

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“…This is the case of the continental scale, here addressed for Europe. Besides and complementing national scale systems, fire information in Europe can rely on the European Forest Fire Information System (EFFIS) which operates over 30 countries in the European and Mediterranean regions, covering the full cycle of forest fire management [6]. Ongoing research [9,25] investigates integrated fire behaviour modelling with the help of high resolution meteorological data (e.g.…”

Section: Transdisciplinary Wildfire Behaviour: Continental Scale Inrmmmentioning

confidence: 99%

“…The complexity and uncertainty associated with these interactions -along with the severity and variety of the involved impacts -urge robust, holistic and transparent approaches [5]. In Europe [6], wildfires are one of the major treats at landscape scale. Wildfires have a particular impact in the Mediterranean Europe [7][8][9] while affecting the aerosol load even in Northern part of the continent [10,11].…”

Section: Introductionmentioning

confidence: 99%

An Architecture for Adaptive Robust Modelling of Wildfire Behaviour under Deep Uncertainty

Rigo

Rodriguez-Aseretto

Bosco

et al. 2013

IFIP Advances in Information and Communication Technology

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Abstract. Wildfires in Europe -especially in the Mediterranean region -are one of the major treats at landscape scale. While their immediate impact ranges from endangering human life to the destruction of economic assets, other damages exceed the spatio-temporal scale of a fire event. Wildfires involving forest resources are associated with intense carbon emissions and alteration of surrounding ecosystems. The induced land cover degradation has also a potential role in exacerbating soil erosion and shallow landslides. A component of the complexity in assessing fire impacts resides in the difference between uncontrolled wildfires and those for which a control strategy is applied. Robust modelling of wildfire behaviour requires dynamic simulations under an array of multiple fuel models, meteorological disturbances and control strategies for mitigating fire damages. Uncertainty is associated to meteorological forecast and fuel model estimation. Software uncertainty also derives from the datatransformation models needed for predicting the wildfire behaviour and its consequences. The complex and dynamic interactions of these factors define a context of deep uncertainty. Here an architecture for adaptive and robust modelling of wildfire behaviour is proposed, following the semantic array programming paradigm. The mathematical conceptualisation focuses on the dynamic exploitation of updated meteorological information and the design flexibility in adapting to the heterogeneous European conditions. Also, the modelling architecture proposes a multicriteria approach for assessing the potential impact with qualitative rapid assessment methods and more accurate a-posteriori assessment.

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Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)

Cited by 213 publications

References 23 publications

Negligent and intentional fires in Portugal: Spatial distribution characterization

Negligent and intentional fires in Portugal: Spatial distribution characterization

Dynamic Data Driven Ensemble for Wildfire Behaviour Assessment: A Case Study

An Architecture for Adaptive Robust Modelling of Wildfire Behaviour under Deep Uncertainty

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