Servicios Personalizados
Revista
Articulo
texto en 
Inglés (pdf)
Artículo en XML
Referencias del artículo
Traducción automática
Enviar artículo por emailIndicadores
-
Citado por SciELO -
Accesos
Links relacionados
-
Similares en
SciELO
Compartir
Permalink
Agrociencia
versión On-line ISSN 2521-9766versión impresa ISSN 1405-3195
Agrociencia vol.41 no.6 Texcoco ago./sep. 2007
Recursos Naturales Renovables
Índice de peligro de incendios forestales de largo plazo
1 Centro de Investigación y Docencia Económicas. División de Economía. Carretera México-Toluca Núm. 3655. Colonia Lomas de Santa Fé, México D.F. 01210. (juanmanuel.torres@cide.edu) y (grodecz.ramirez@cide.edu).
2 Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias. C. E. Valle de México (magana.octavio@inifap.gob.mx)
En este documento se describe un índice de peligro de incendios forestales de largo plazo. El índice se basa en el principio de que los incendios forestales siguen un comportamiento crítico auto organizado, el cual establece que bajo una amplia variedad de circunstancias, los incendios forestales mantienen una relación exponencial sobre varias órdenes de magnitud entre la frecuencia de ocurrencia y el área quemada. Se describe el principio de un comportamiento crítico auto organizado de los incendios forestales y, con base en los registros de superficie y número de incendios forestales por Estado en México de 1970 a 2005, se comprueba empíricamente que el número total de incendios forestales ocurridos por año en cada Estado guarda una relación exponencial con el área quemada. Este comportamiento se usa para definir un índice de peligro de incendios forestales a largo plazo. El análisis de los resultados muestra que los incendios ocurridos en cada Estado exhiben distribuciones de frecuenciatamaño que se aproximan a una distribución de potencia. La importancia de este resultado es que permite calcular índices de peligro de incendios forestales de largo plazo para cada entidad, índices que pueden tener una amplia variedad de aplicaciones en la planeación y ejecución de las actividades de prevención y combate de dichos siniestros.
Palabras clave: Comportamiento crítico auto organizado; distribución frecuencia-tamaño; fractales; índice de peligro
A description is made of a long run forest fire danger index. The index is based on the principle that forest fires follow a selforganized critical behavior, which establishes that under a wide variety of circumstances, forest fires maintain an exponential relationship over various orders of magnitude between frequency of occurrence and the burned area. A description is made of the principle of self-organized critical behavior of forest fires and, based on the records of surface and number of forest fires per State in Mexico from 1970 to 2005, it is proved empirically that the total number of forest fires occurred per year in each State maintains an exponential relationship with the burned area. This behavior is used to define a long run forest fire danger index. The analysis of the results shows that the fires occurring in each State exhibit frequency-size distributions which approximate a power distribution. The importance of this result is that it permits the calculation of long run forest fire danger indices for each entity, indices that can have a wide variety of applications in the planning and application of the activities of prevention and control of forest fires.
Key words: Self organized critical behavior; frequency-size distribution; fractals; danger index
Literatura citada
Alcázar, J., C. V. García, P. J. Grauet, and A. Fernández. 1998. Human risk and fire danger estimation through multicriteria analysis evaluation methods for forest fire prevention in Barcelona, Spain. In: Forest Fires: Ecology and Control III International Conference on Forest Fire Research. University of Coimbra, ADAI. Viegas, X. (ed.). pp: 2379-2387. [ Links ]
Andrews, P. L., D. O. Loftsgaarden, and L. S. Bradshaw. 2003. Evaluation of fire danger rating indexes using logistic regression and percentile analysis. Int. J. Wildland Fire 12(2): 213-226. [ Links ]
Bak, P., K. Chen, and C. Tang. 1990. A forest-fire model and some thoughts on turbulence. Phys. Lett. A 147: 297-300. [ Links ]
Bell, E. F., D. A. Cleaves, H. Croft, S. Husari, E. Schuster, and D. Truesdales. 1995. Fire economics assessment report. Albany, CA. Pacific Southwest Res. Stn. USDA For. Serv. 67 p. [ Links ]
Benavides S., J. D. and L. H. MacDonald. 2005. Measurement and prediction of post-fire erosion at the hillslope scale, Colorado Front Range. Int. J. Wildland Fire 14(4): 457-474. [ Links ]
Blanchi, R., M. Jappiot, and D. Alexandrian. 2002. Forest fire risk assessment and cartography A methodological approach. 4th International Conference on Forest Fire Research, Coimbra, Portugal. pp: 2-9. [ Links ]
Bonazountas, M., D. Kallidromitou, P.A. Kassomenos, and N. Passas. 2005. Forest fire risk analysis. Human and Ecol. Risk Ass. 11: 617-626. [ Links ]
Burgan, R. E., R. W. Klaver, and J.M. Klaver. 1998. Fuel models and fire potential from satellite and surface observation. Int. J. Wildland Fire 8:159-170. [ Links ]
Castro, R., and E. Chuvieco. 1998. Modeling forest danger from GIS. Geocarto Int. 13: 15-23. [ Links ]
Cedeño-Sánchez, O. 2001 Situación actual sobre los incendios forestales y sus principales causas. In: Memoria del II Foro Internacional sobre los Aprovechamientos Forestales en Selvas y su Relación con el Ambiente. SEMARNAT-FAO-Gob. Estado de Veracruz. pp: 235-252. [ Links ]
Chou, Y. H. 1992. Management of wild fires with a geographical information system. Int. J. Geo. Inf. Sys. 6: 123-140. [ Links ]
Christensen, K., H. Flyvbjerg, and Z. Olami. 1993, Self-organized critical forest-fire model: Meanfield theory and simulation results in 1 to 6 dimensions. Phys. Rev. Lett. 71: 2737-2740. [ Links ]
Chuvieco, E., and R. G. Congalton. 1989. Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote Sensing Environ. 29: 147-159. [ Links ]
Chuvieco E., F. J. Salas, L. Carvacho, and F. Rodríguez-Silva. 1999. Integrated fire risk mapping. In: Remote Sensing of Large Wildfires. New York: Springer-Verlag. Chuvieco, E. (ed). pp: 65-84. [ Links ]
Clar, S., B. Drossel, and F. Schwabl. 1996. Forest fires and other examples of self-organized criticality. J. Phys. Cond. Mat. 8: 6803-6824. [ Links ]
Drossel, B., and F. Schwabl. 1993, Forest-fire model with immune trees. Physica A 199:183-197. [ Links ]
Frankenberg, E., D. McKee, and D. Thomas. 2005. Health consequences of forest fires in Indonesia. Demography 42(1):109-129. [ Links ]
Fried, J. S., G. J. Winter, and J. K. Gilless. 1999. Assessing the benefits of reducing fire risk in the wildland-urban interface: a contingent valuation approach. Int. J. Wildland Fire 9 (1): 9-20. [ Links ]
González C., A. 1993. The economic impact of fire on forest resources. Wildfire 1: 16-21. [ Links ]
Henley, C. L. 1993. Statics of a “self-organized” percolation model. Phys. Rev. Lett. 71: 2741-2744. [ Links ]
Jain, A, S. A. Ravan, R. K. Singh, K. K. Das, and P. S. Roy. 1996. Forest fire risk modelling using remote sensing and geographic information system. Research Com. Current Sci. 10: 928-933. [ Links ]
Johansen, A. 1994. Spatio-temporal self-organization in a model of disease spreading. Physica D 78: 186-193. [ Links ]
Loftsgaarden, D. O., and P. L. Andrews. 1992. Constructing and testing logistic regression models for binary data: applications to the national fire danger rating system. Gen. Tech. Rep. INT286, Ogden, UT, USDA For. Serv. 36 p. [ Links ]
Malamud, B. D., and D. L. Turcotte. 1999. Self-organized criticality applied to natural hazards. Natural Hazards 20: 93-116. [ Links ]
Malamud, B. D., G. Morein, and D. L. Turcotte. 1998. Forest fires: an example of self-organized critical behavior. Science 281: 1840-1842 [ Links ]
Mills, W. L., and R. S. Meldad. 1987. Measuring wildfire impacts: methods and case study. Northern J. App. For. 11(3): 143-147. [ Links ]
Rodríguez-Trejo, D. A. 1996. Incendios Forestales. Universidad Autónoma Chapingo-MundiPrensa. México, D. F. 630 p. [ Links ]
Sebastian-López, A., J. San-Miguel-Ayanz, and G. Libertà. 2000, An integrated forest fire risk index for Europe, 20th EARSeL Symp: Remote sensing in the 21st century: a decade of transEuropean remote sensing cooperation, Dresden, Germany. pp: 137-142. [ Links ]
SEMARNAT (Secretaría del Medio Ambiente y Recursos Naturales). 2005. Sistema Nacional de Información Ambiental y de Recursos Naturales. Base de Datos Estadísticos. Secretaría de Medio Ambiente y Recursos Naturales. http://www.semarnat.gob.mx/informacionambiental/Pages/sniarn.aspx [ Links ]
Tabara, D., D. Sauri, and R. Cerdan. 2003. Forest fire risk management and public participation in changing socioenvironmental conditions: a case study in a Mediterranean region. Risk Analysis 22(2): 249-260. [ Links ]
Truesdale, D. 1995. Fire suppression costs on large fires: A review of the 1994 fire season. Washington, D.C. USDA For. Serv. 60 p. [ Links ]
Vega-García, C, B. S. Lee, P. M. Woodard, and S. J. Titus. 1996. Applying neural network technology to human caused wildfire occurrence prediction. AI Applications 10: 9-18. [ Links ]
Vega-García, C., P. M. Woodard, S. J. Titus, W. L. Adamowicz, and B. S. Lee. 1995. A logit model for predicting the daily occurrence of human caused forest fires. Int. J. Wildland Fire 5: 101-111. [ Links ]
Viegas, D. X., G. Bovio, A. Ferreira, A. Nosenzo, and B. Sol. 1999. Comparative study of various methods of fire danger en southern Europe. Int. J. Wildland Fire 9(4): 235-246. [ Links ]
Winter G. J., and J. S. Fried. 2001. Estimating contingent values for protection from wildland fire using a two-stage decision framework. For. Sci. 47(3): 349-360. [ Links ]
Recibido: Marzo de 2006; Aprobado: Abril de 2007
Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons
