Live fuel moisture content and ignition probability in the Iberian Peninsular territory of Spain

  1. Jurdao Knecht, Sara
  2. Yebra Álvarez, Marta
  3. Bastarrika, Aitor
  4. Chuvieco, Emilio
Revista:
Geofocus: Revista Internacional de Ciencia y Tecnología de la Información Geográfica

ISSN: 1578-5157

Año de publicación: 2013

Título del ejemplar: “In Memoriam: Sergio Opazo Saldivia”

Número: 13

Tipo: Artículo

Otras publicaciones en: Geofocus: Revista Internacional de Ciencia y Tecnología de la Información Geográfica

Resumen

This paper presents an operational algorithm to produce Live Fuel Moisture Content (LFMC) at national scale from MODIS data. The algorithm is based on the inversion of Radiative Transfer Models (RTM) that estimate moisture content based on different simulation scenarios. In addition, logistic regression models were calibrated to convert the derived LFMC values into Ignition Probability (IP) maps. The areas under the curve obtained by the Receiver Operating Characteristic (ROC) plot method provided by the models were close to 0.6. Several statistical analyses were performed in order to ascertain whether the variables proposed to be included in the fire danger model were significantly related to forest fires. A non parametric U-Mann-Withney test confirmed significant differences between fire and non-fire pixels (p

Referencias bibliográficas

  • Andrews, P. L., D. O. Loftsgaarden y L. S. Bradshaw (2003): "Evaluation of fire danger rating indexes using logistic regression and percentile analysis", International Journal of Wildland Fire, 12, pp. 213-226.
  • Budiko, M. I. (1974): Climate and Life. New York, Academic Press.
  • Caccamo, G., L. A., Chisholm, R. A., Bradstock y M. L. Puotinen (2011): “Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems", Remote Sensing of Environment, 115, 20, pp. 2626-2639.
  • Chuvieco, E., I. Aguado y A. Dimitrakopoulos (2004): “Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment”, Canadian Journal of Forest Research-Revue Canadienne de Recherche Forestiere, 34, 11, pp. 2284-2293.
  • Chuvieco, E., I. González, F. Verdú, I. Aguado y M. Yebra (2009): "Prediction of fire occurrence from live fuel moisture content measurements in a Mediterranean ecosystem", International Journal of Widland Fire, 18, pp. 430-441.
  • Chuvieco, E., M. Yebra, S. Jurdao, I. Aguado, J. Salas, M. García, H. Nieto, A. de Santis, D. Cocero, D. Riaño, S. Martínez, E. Zapico, C. Recondo, J. Martínez-Vega, M. P. Martín, J. Riva, F. Pérez y F. Rodríguez-Silva (2011): "Field fuel moisture measurements on Spanish study sites. Department of Geography, University of Alcalá." http://www.geogra.uah.es/emilio/FMC_UAH.html.
  • Combal, B., F., Baret, M., Weiss, A., Trubuil, D. Mace, A. Pragne`re, R. Myneni, Y. Knyazikhin y L. Wang (2002): "Retrieval of canopy biophysical variables from bidirectional reflectance Using prior information to solve the ill-posed inverse problem", Remote Sensing of Environment, 84, pp. 1-15.
  • Crapper, P. F. y K. C. Hynson (1983): "Change detection using Landsat photographic imagery", Remote Sensing of Environment, 13, pp. 291-300.
  • de Santis, A., G. P. Asner, P. J. Vaughan y D. E. Knapp (2010): "Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery", Remote Sensing of Environment, 114, 7.
  • Dennison, P. E. y M. A. Moritz (2009): "Critical live fuel moisture in chaparral ecosystems: a threshold for fire activity and its relationship to antecedent precipitation", Interational Journal of Wildland Fire, 18, pp. 1021-1027.
  • Dimitrakopoulos, A. P., I. D. Mitsopoulos y K. Gatoulas (2010): "Assessing ignition probability and moisture of extinction in a Mediterranean grass fuel", International Journal of Wildland Fire, 19, pp. 29-34.
  • Fielding, A. H. y J. F. Bell (1997): "A review of methods for the assessment of prediction errors in conservation presence/absence models", Environmental Conservation, 24, pp. 38-49.
  • Garcia, M., I. Aguado y E. Chuvieco (2008): "Combining AVHRR and meteorological data for estimating live fuel moisture content in forest fire danger rating", Remote Sensing of Environment, 112, pp. 3618-3627.
  • Giglio, L., J., Descloitres, C. O. Justice y J. B. Kauffmam (2003): "An Enhanced Contextual Fire Detection Algorithm for MODIS", Remote Sensing of Environment, 87, pp. 273-282.
  • Gobron, N., B. Pinty, M. M. Verstraete, J. V. Martonchik, Y. Knyazikhin y D. J. Diner (2000): "Potential of multiangular spectral measurements to characterize land surfaces: Conceptual approach and exploratory application", Journal of Geophysical Research, 105, D13, pp. 17539-17549.
  • González-Alonso, F., J. M. Cuevas, J. L., Casanova, A. Calle y P. Illera (1997): "A forest fire risk assessment using NOAA-AVHRR images in the Valencia area, Eastern Spain", International Journal of Remote Sensing, 18, pp. 2201-2207.
  • Huemmrich, K. F. (2001): "The GeoSail model: a simple addition to the SAIL model to describe discontinuous canopy reflectance", Remote Sensing of Environment, 75, pp. 423-431.
  • Hunt, E. R. y B. N. Rock (1989): "Detection of changes in leaf water content using near and middle-infrared reflectances", Remote Sensing of Environment, 30, pp. 43-54.
  • Jacquemoud, S. (1990): "PROSPECT: a model to leaf optical properties spectra", Remote Sensing of Environment, 34, pp. 74-91.
  • Jurdao, S. (2012): "Remotely sensed Live Fuel Moisture retrieval using Radiative Transfer Models", Geography, Alcalá de Henares, Alcalá University, 168.
  • Jurdao, S., E. Chuvieco y J. M. Arevalillo (2012): "Modelling fire ignition probability from satellite estimates of live fuel moisture content", Fire Ecology, 8, 1, pp. 77-97.
  • Jurdao, S., M. Yebra, E. Chuvieco y J. P. Guerschman (2013): "Regional estimation of woodland moisture content by inverting Radiative Transfer Models", Remote Sensing of Environment, 132, pp. 59-70.
  • Kötz, B., M. Schaepmanb, F. Morsdorf, P. Bowyer, K. Ittena y B. Allgöwer (2004): "Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties", Remote Sensing of Environment, 92, pp. 332-344.
  • Kruse, F. A., A. B. Lefkoff, J. B. Boardman, K. B. Heidebrecht, A. T. Shapiro, P. J. Barloon y A. F. H. Goetz (1993): "The Spectral Image Processing (SIPS) - Interactive Visualization and Analysis of Imaging Specrometer Data", Remote Sensing of Environment, 44, pp. 145-163.
  • López, S., F. González, R. Llop y J. M. Cuevas (1991): "An evaluation of the utility of NOAA AVHRR images for monitoring forest fire risk in Spain", International Journal of Remote Sensing, 12, 9, pp. 1841-1851.
  • Saich, P., P. Lewis y M. I. Disney (2003): "Biophysical parameter retrieval from forest and crop canopies in the optical and microwave domains using 3D models of canopy structure", Geoscience and Remote Sensing Symposium, IGARSS '03, Toulouse, IEEE International.
  • Schaaf, C. B., F. Gao, A. H. Strahler, W. Lucht, X. Li, T. Tsang, N. C. Strugnell, X. Zhang, Y. Jin, J.-P. Muller, P. Lewis, M. Barnsley, P. Hobson, M. Disney, G. Roberts, M. Dunderdale, C. Doll, R. P. d’Entremont, B. Hug, S. Liang, J. L. Privette y D. Roy (2002): "First operational BRDF, albedo nadir reflectance products from MODIS", Remote Sensing of Environment, 83, pp. 135–148.
  • Trombetti, M., D. Riano, M. A. Rubio, Y. B. Cheng y S. L. Ustin (2008): "Multi-temporal vegetation canopy water content retrieval and interpretation using artificial neural networks for the continental USA", Remote Sensing of Environment, 112, pp. 203-215.
  • Verhoef, W. (1984): "Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model", Remote Sensing of Environment, 16, pp. 125-141.
  • Viegas, D. X., T. P. Viegas y A. D. Ferreira (1992): "Moisture content of fine forest fuels and fire occurrence in central Portugal", The International Journal of Wildland Fire, 2, 2, pp. 69-85.
  • Yebra, M. y E. Chuvieco (2009): "Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem", Remote Sensing of Environment, 113, pp. 2403-2411.
  • Yebra, M., E. Chuvieco y I. Aguado (2008a): "Comparación de modelos empíricos y de transferencia radiativa para estimar contenido de humedad en pastizales: Poder de generalización", Revista de Teledetección, 29, pp. 73-90.
  • Yebra, M., E. Chuvieco y D. Riaño (2008b): "Estimation of live fuel moisture content from MODIS images for fire risk assessment", Agricultural and Forest Meteorology, 148, 4, pp. 523-536.