en en en fi en en en en en en en en en en en en en en en en en en en en en es gl en en en en en en en en en en en es en gl en en en en en en gl en en en es en it en en en en en en en en en es en es gl es es pt fr en en en en en es es es en en en es es es en es en en en es en en en en es en en es gl en en es es en gl en de el en nb en en en ja ru id en en en ru bo en en en es en en en en en en en en en ru uk en en oc en oc en zh en ca en fr en fr en da en oc en oc en fr en es es en en en en
Modelling spatial patterns and temporal trends of wildfires in Galicia (NW Spain) | Forest Systems
Skip to main content Skip to main navigation menu Skip to site footer
Jesús Barreal Departamento de Fundamentos da Análise Económica, Facultad de C. Económicas de Santiago de Compostela
Aim of study: The goal of this paper is to analyse the importance of the main contributing factors to the occurrence of wildfires.
Area of study: We employ data from the region of Galicia during 2001-2010; although the similarities shared between this area and other rural areas may allow extrapolation of the present results.
Material and Methods: The spatial dependence is analysed by using the Moran’s I and LISA statistics. We also conduct an econometric analysis modelling both, the number of fires and the relative size of afflicted woodland area as dependent variables, which depend on the climatic, land cover variables, and socio-economic characteristics of the affected areas. Fixed effects and random effect models are estimated in order to control for the heterogeneity between the Forest Districts in Galicia.
Main results: Moran’s I and LISA statistics show that there is spatial dependence in the occurrence of Galician wildfires. Econometrics models show that climatology, socioeconomic variables, and temporal trends are also important to study both, the number of wildfires and the burned-forest ratio.
Research highlights: We conclude that in addition to direct forest actions, other agricultural or social public plans, can help to reduce wildfires in rural areas or wildland-urban areas. Based on these conclusions, a number of guidelines are provided that may foster the development of better forest management policies in order to reduce the occurrence of wildfires.
Keywords: Cause-effect relationship; climatology; spatial and temporal indicators; fixed effects; random effects; socio-economic factors.
Download data is not yet available.
Jesús Barreal, Departamento de Fundamentos da Análise Económica, Facultad de C. Económicas de Santiago de Compostela
PhD student with the Department of Economic Theory at the University of Santiago de Compostela, Spain
Anselin L, Syabri I, Kho Y, 2006. GeoDa: An Introduction to Spatial Data Analysis. Geographical Analysis 38 (1): 5-22. http://dx.doi.org/10.1111/j.0016-7363.2005.00671.x
Barreal J, Loureiro M, Picos J, 2011. Estudio de la incidencia de los incendios en Galicia: una perspectiva socioeconómica. Revista Galega de Economía 20 (special issue): 227-246.
Barreiro JB, Hermosilla T, 2013. Socio-geographic analysis of the causes of the 2006's wildfires in Galicia (Spain).Forest Systems 22(3): 497-509. http://dx.doi.org/10.5424/fs/2013223-04165
Brillinger DR, Preisler HK, Benoit JW, 2006. Probabilistic risk assessment for wildfires. Environmetric 17: 623–633. http://dx.doi.org/10.1002/env.768
Butry DT, 2009. Fighting fire with fire: estimating the efficacy of wildfire mitigation programs using propensity scores. Environmental and Ecological Statistics 16(2): 291-319. http://dx.doi.org/10.1007/s10651-007-0083-3
Cabrera AD, 1989. Metodología de estudio de los incendios forestales: el caso de la provincia de Córdoba. ERIA: 139-146.
Cameron AC, Trivedi PK, 2005. Microeconometrics. Methods and applications. Cambridge University Press, Cambridge, England. 1034 pp. http://dx.doi.org/10.1017/CBO9780511811241
Cameron AC, Trivedi PK, 2009. Microeconometrics using Stata. Stata Press, Texas, USA. 692 pp.
Carroll MS, Higgins LL, Cohn PJ, Burchfield J, 2006. Community Wildfire Events as a Source of Social Conflict. Rural Sociology 71(2): 261-280. http://dx.doi.org/10.1526/003601106777789701
Chen X, Goodwin BK, Prestemon JP, 2014. Is Timber Insurable? A Study of Wildfire Risks in the US Forest Sector Using Spatio-Temporal Models.American Journal of Agricultural Economics 96(1): 213-231. http://dx.doi.org/10.1093/ajae/aat087
Chuvieco E, Aguado I, Yebra M, Nieto H, Salas J, Martína MP, Vilar L, Martínez J, Martín S, Ibarra P, De La Riva J, Baeza J, Rodríguez F, Molina JR, Herrera MA, Zamora R, 2009. Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling 221(1): 46-58. http://dx.doi.org/10.1016/j.ecolmodel.2008.11.017
Disdier AC, Head K, 2008. The puzzling persistence of the distance effect on bilateral trade. The Review of Economics and Statistics 90(1): 37–48. http://dx.doi.org/10.1162/rest.90.1.37
European Environment Agency, 2010. CORINE Land Cover. Available at: http://www.eea.europa.eu/.
Finney M, Grenfell IC, McHugh CW, 2009. Modeling Containment of Large Wildfires Using Generalized Linear Mixed-Model Analysis. Forest Science 55(3): 249-255.
Forest Europe, UNECE, FAO, 2011. State of Europe's Forests 2011. Status and Trends in Sustainable Forest. Ministerial Conference on the Protection of Forests in Europe, Aas, Norway. 342 pp.
Genton MG, Butry DT, Gumpertz ML, Prestemon, JP, 2006. Spatio-temporal analysis of wildfire ignitions in the St Johns River Water Management District, Florida. International Journal of Wildland Fire 15: 87-97. http://dx.doi.org/10.1071/WF04034
GeoDa, 2014. 1.6.6. GeoDa Center for Geospatial Analysis and Computation. Available at: https://geodacenter.asu.edu/
GvSig, 2014. 2.0. GvSig Desktop. Asociación GvSig. Available at: http://www.gvsig.org
Herrero-Corral G, Jappiot M, Bouillon C, Long-Fournel M, 2012. Application of a geographical assessment method for the characterization of wildland–urban interfaces in the context of wildfire prevention: A case study in western Madrid. Applied Geography 35(1): 60-70. http://dx.doi.org/10.1016/j.apgeog.2012.05.005
IGE, 2012a. Información Territorial de Galicia (Spain) [online]. Instituto Galego de Estadística, Available at: http://www.ige.eu/web/mostrar_actividade_estatistica.jsp?idioma=gl&codigo=0101001 [17 July 2012].
IGE, 2012b. Banco de datos municipal [online]. Instituto Galego de Estadística, available at: http://www.ige.eu/web/mostrar_paxina.jsp?paxina=002001&idioma=gl [17 July 2012].
IGN, 2011. Base Cartográfica Nacional. Instituto Geográfico Nacional. Available at: http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do#selectedSerie
IGN, 2011. Líneas Límite de la Base de datos de Límites Jurisdiccionales de España inscritas en el Área del Registro Central de Cartografía del IGN. Instituto Geográfico Nacional. Available at: http://centrodedescargas.cnig.es/CentroDescargas [17 July 2012].
INE, 2015. Estatisticas territoriais (online). Instituto Nacional de Estatísitca (Spain), Available at: http://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_unid_territorial&menuBOUI=13707095&contexto=ut&selTab=tab3 [02 March 2012].
INSEE, 2015. Données locales (online). Institut National de la Statistique et des Études Économiques (France). Available at: http://www.insee.fr/fr/bases-de-donnees/default.asp?page=statistiques-locales.htm [02 March 2012].
Jones K, 1991. Specifying and Estimating Multi-Level Models for Geographical Research. Transactions of the Institute of British Geographers 16(2): 148-159. http://dx.doi.org/10.2307/622610
King D, MacGregor C, 2000. Using Social indicators to measure community vulnerability to natural hazards. The Australian Journal of Emergency Management 15 (3): 52-57.
Lavorel S, Flannigan M, Lambin E, Scholes M, 2007. Vulnerability of land system to fire: Interactions among humans, climate, the atmosphere, and ecosystems. Mitigation and Adaptation Strategies for Global Change 12(1): 33-53. http://dx.doi.org/10.1007/s11027-006-9046-5
Lesage J, Kelley R, 2009. Introduction to Spatial Econometrics. CRC Press. Florida (EUA). http://dx.doi.org/10.1201/9781420064254
Long JS, Freese J, 2001. Regression models for categorical dependent variables using Stata. Stata Press Publication, Texas, USA. 288 pp.
Marey MF, Rodríguez V, Crecente R, 2007. Perfil del propietario forestal individual en Galicia: objetivos y prácticas de gestión en el noroeste de la comunidad. Revista Galega de Economía 16 (1): 1-24.
MARM, 2012. Avance Anuario de estadística 2011 [online]. Ministerio de Medio Ambiente y Medio Rural y Marino de España, available at: http://www.magrama.gob.es/estadistica/pags/anuario/2011/AE_2011_Avance.pdf [17 July 2012].
Martínez A, Castillo F, Pérez A, Valcárcel M, Blanco R, 1999. Atlas climático de Galicia. Xunta de Galicia, Santiago de Compostela, Spain. 277 pp.
Martínez J, Vega-García C, Chuvieco E, 2009. Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management 90(2): 1241-1252. http://dx.doi.org/10.1016/j.jenvman.2008.07.005
Mercer DE, Prestemon JE, 2005. Comparing production function models for wildfire risk analysis in the wildland-urban interface. Forest Policy and Economics 7: 782-795. http://dx.doi.org/10.1016/j.forpol.2005.03.003
Meteogalicia, 2012. Informes Meteorolóxicos [online]. Meteogalicia, available in: http://www.meteogalicia.es/observacion/informesclima/informesIndex.action [17 July 2012].
MAGRAMA, 2008. Tercer Inventario Forestal Nacional 1997-2007. Galicia. Ministerio de Medio Ambiente. Madrid, España.
MAGRAMA, 2010. Red Natura 2000. Ministerio de Agricultura, Alimentación y Medio Ambiente. Dirección General de Calidad y Evaluación Ambiental y Medio Natural. Subdirección General de Medio Natural. Available at: http://www.magrama.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible/rednatura2000_descargas.aspx [17 July 2012].
Molano F, Rodríguez C, Ponte JM, 2007. Informe sobre investigación de incendios en Galicia. Verano 2006. Diputación de Coruña, A Coruña, Spain. 270 pp.
Moran P, 1948. The interpretation of statistical maps. Biometrika 35: 255-260.
Moreno R, Vayá E, 2000. Técnicas econométricas para el tratamiento de datos espaciales: La econometría espacial. Edicións de la Universitat de Barcelona. Barcelona (Spain). 156 pp.
Moulton BR, 1986. Random group effects and the precision of regression estimates. Journal of Econometrics 32: 385-397. http://dx.doi.org/10.1016/0304-4076(86)90021-7
Neter J, Nachtsheim C, Kutner M, 1983. Applied linear regression models. Richard D. Irwin, Chicago, USA. 547 pp.
Pasalodos-Tato M, Pukkala T, Rigueiro-Rodríguez A, Fernández-Núñez E, Mosquera-Losada MR, 2009. Optimal management of Pinus radiata silvopastoral systems established on abandoned agricultural land in Galicia (north-western Spain). Silva Fenn 43(5): 831-845. http://dx.doi.org/10.14214/sf.176
Pérez J, Delgado JL, 1995. Análisis del riesgo de incendio forestal en Galicia (Spain). Revista Agricultura y Sociedad 77: 109-124.
Pew KL, Larsen CPS, 2001. GIS analysis of spatial and temporal patterns of human-caused wildfires in the temperate rain forest of Vancouver Island, Canada. Forest Ecology and Management 140(1): 1–18. http://dx.doi.org/10.1016/S0378-1127(00)00271-1
Prestemon JP, Pye JM, Butry D.T, Holmes TP, Mercer DE, 2002. Understanding broadscale wildfire risks in a human-dominated landscape. Forest Science 48(4): 685-693.
Preisler HK, Brillinger D.R, Burgan RE, Benoit JW, 2004. Probability based models for estimation of wildfire risk. International Journal of Wildland Fire 13(2): 133-142. http://dx.doi.org/10.1071/WF02061
PROMETHEE, 2015. Forest fires database for Mediterranean area in France. Promethee. Available at: http://www.promethee.com/ [02 March 2012].
Rigueiro A, Mosquera MR, Villari JJ, 2002. Reducción del riesgo de incendios forestales mediante el pastoreo del caballo gallego de monte. Cuadernos de la Sociedad Española de Ciencias Forestales 14.
Rogalski J, 1999. Decision-making and management of dynamic risk. Cognition, Technology & Work 1(4): 247-256. http://dx.doi.org/10.1007/s101110050021
Romero-Calcerrada R, Barrio-Parra F, Millington JDA, Novillo CJ, 2010. Spatial modelling of socioeconomic data to understand patterns of human-caused wildfire ignition risk in the SW of Madrid (central Spain). Ecological Modelling 221(1): 34-45. http://dx.doi.org/10.1016/j.ecolmodel.2009.08.008
SECF (Sociedad Española de Ciencias Forestales), 2010. Situación de los bosques y del sector forestal en España [online], available in: http://www.secforestales.org/web/images/inforestal2010.pdf [17 July 2012].
Sineiro F, 2006. As causas estructurais dos incendios forestais en Galica. In: Os incendios forestais en Galicia (Díaz-Fierros F, Baamonde P, eds). Consello da Cultura Galega, Santiago de Compostela, Spain. 77-92 pp.
Stata, 2010. 10. 1. Data analysis and statistical software. StataCorp LP. Available at: www.stata.com
Vega-García C, Chuvieco E, 2006. Applying local measures of spatial heterogeneity to Landsat-TM images for predicting wildfire occurrence in Mediterranean landscapes. Landscape Ecology 21: 595–605. http://dx.doi.org/10.1007/s10980-005-4119-5
Vega JA, 2007. Impacto de los incendios sobre suelo y vegetación forestales en Galicia y desarrollo de una selvicultura preventiva. In: Por unha nova cultura forestal fronte aos incendios (Díaz-Fierros F, Balboa X, Barreiro, XL, eds.). Consello da Cultura Galega y Fundación Caixa Galicia, Santiago de Compostela, Spain. 87-126 pp.
Vilar L, Martín MP, Martínez J, 2008. Empleo de técnicas de regresión logística para la obtención de modelos de riesgo humano de incendio forestal a escala regional. Boletín de la A.G.E. (Spain). 47: 5-29.
Wimberly MC, Cochrane MA, Baer AD, Pabst, K, 2009. Assessing fuel treatment effectiveness using satellite imagery and spatial statistics. Ecological Applications 19: 1377–1384. http://dx.doi.org/10.1890/08-1685.1
Xunta de Galicia, 2011. Pladiga 2011. Consellería de Medio Rural. Dirección Xeral de Montes, Santiago de Compostela, Spain. 123 pp.
BarrealJ., & LoureiroM. L. (2015). Modelling spatial patterns and temporal trends of wildfires in Galicia (NW Spain). Forest Systems, 24(2), e022. https://doi.org/10.5424/fs/2015242-05713
Vol. 24 No. 2 (2015)
© INIA. Manuscripts published are the property of the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, and quoting this source is a requirement for any partial or full reproduction.
Forest Systems is an Open Access Journal. All articles are distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the license CC-by must be expressly stated in this way when necessary.
Most downloads (60 days)
Using inventory variables for practical biodiversity assessment in plantation stands
Wild mushroom potential in Ethiopia: An analysis based on supplier and consumer preferences
Vegetation patches in semiabandoned olive groves: using generalised linear mixed models to determine the effect of area on community composition of woody plants
Susceptibility to Phytophthora cinnamomi of six holm oak (Quercus ilex) provenances: are results under controlled vs. natural conditions consistent?
Resource communication: New forestry tools for natural beech forests in northwestern Spain
Species composition and specific aspects of the Green Tree Retention structure in unmanaged mixed forests in Asturias (northern Spain)
Resource Communication: ForestAz - Using Google Earth Engine and Sentinel data for forest monitoring in the Azores Islands (Portugal)
Significant impact of allochthonous nutrient loads on microarthropods in forest soils
Prescribed burning in Pinus cubensis-dominated tropical natural forests: a myco-friendly fire-prevention tool
Fine-root chemical traits rather than morphological traits of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations vary along an altitudinal gradient in Eastern China
Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC)