Validation of the remote sensing indices dNBR and RdNBR to assess fire severity in the Oia-O Rosal (Pontevedra) wildfire in 2013

S. Arellano, J.A. Vega, F. Rodríguez y Silva, C. Fernández, D. Vega-Nieva, J.G. Álvarez-González, A.D. Ruiz-González

Abstract

Fire severity evaluation and mapping following wildfire is an essential task for post-fire rehabilitation activities and forest management planning. For that purpose, some spectral indexes are used to quantify the changes caused by fire, being Landsat satellite one of the most frequently used. Even though Galicia is the Spanish region with the highest number of fires in the country, the information on fire severity estimation through satellite imagery is scarce. In the present study, the capacity of dNBR (differenced Normalized Burn Ratio) and RdNBR (Relative difference Normalized Burn Ratio), through Landsat 8 imagery processing, are compared for the first time in Galicia to test both indexes with field data following the methodology from CBI (Composite Burn Index) in Oia-O Rosal (Pontevedra) wildfire occurred in the summer of 2013. The results indicate that the models for dNBR and RdNBR estimation according to CBI were similar, explaining a 69 and 73% of variability, respectively. These models allow to obtain a new fire severity thresholds for dNBR and RdNBR for the burned area. Although, both indexes showed a similar and quite high overall accuracy in the classification of the different fire severity classes (75% y 83% for dNBR and RdNBR, respectively), RdNBR was slightly more accurate than dNBR. Additionally, the dNBR-based fire severity map significantly underestimated the high fire severity area, compared with RdNBR. Those preliminary results can be useful to evaluate fire severity spatial distribution, in wildfires in Galicia although new data will be necessary before an operational tool to be available.


Keywords

fire severity; spectral indexes; dNBR; RdNBR; Landsat 8; forest fires; Galicia 2013; CBI

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References

Álvarez, M.T., Rodríguez-Pérez, J.R., CastedoDorado, F., Vega, D. 2007. An operational protocol for post-fire evaluation at landscape scale in an object-oriented environment. In: Gitas & Carmona. Proceedings of the 6th International Workshop of the EARSEL FFSIG. European Commission, JRC, Ispra (Italy), 202-207.

Arellano, S. 2008. Índices meteorológicos de peligro de incendios forestales en Galicia: Evidencias de cambio climático y su relación con la frecuencia de fuegos y superficie afectada. Proyecto fin de carrera. Escuela Técnica de Ingeniería Forestal. Universidad de Vigo, 409 pp.

Cansler, C.A., McKenzie, D. 2012. How Robust Are Burn Severity Indices When Applied in a New Region? Evaluation of Alternate Field- Based and Remote-Sensing Methods. Remote Sensing, 4, 456- 483. https://doi.org/10.3390/rs4020456

Chuvieco, E. 2009. Earth Observation of Wildland Fires in Mediterranean Ecosystems. Alcalá de Henares, Spain: Springer. 257 pp. https://doi. org/10.1007/978-3-642-01754-4

Chuvieco, E., Riaño, D., Danson, F.M., Martín, M.P. 2006. Use of radiative transfer model to simulate the post-fire spectral response to burn severity. Journal of Geophysical Research, 111, G04S09. https://doi. org/10.1029/2005JG000143

Congalton, R.G., Green, K. 1999. Assessing the accuracy of remotely sensed data: Principles and practices. New York: Lewis Publishers, 137 pp.

De Santis, A., Chuvieco, E. 2009. GeoCBI: A modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data. Remote Sensing of Environment, 113(3), 554-562. https://doi. org/10.1016/j.rse.2008.10.011

Díaz-Delgado, R., Lloret, F., Pons, X. 2004 Statistical analysis of fire frequency models for Catalonia (NE Spain, 1975-1998) based on fire scar maps from Landsat MSS data. International Journal of Wildland Fire, 13, 89-99. https://doi.org/10.1071/ WF02051

Enríquez, E., Del Moral, L. 2012. Los Incendios Forestales en España. Decenio 2001-2010. Ministerio de Agricultura, Alimentación y Medio Ambiente: Madrid.

Epting, J., Verbyla, D., Sorbel, B. 2005. Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM an ETM+. Remote Sensing of Environment, 96, 328-339. https://doi.org/10.1016/j.rse.2005.03.002

Escuin, S., Fernández, P., Navarro, R.M., 2002. Aplicación de escenas Landsat a la asignación de grados de afectación producidos por incendios forestales. Revista de Teledetección, 17, 77-87. Último acceso: noviembre de 2017. http://www.aet. org.es/revistas/revista17/AET17-09.pdf

Fernández, C., Vega J.A., Fonturbel, M.T., Jiménez, E., Pérez-Gorostiaga, P. 2008. Wildfire, salvage logging and slash manipulation effects on Pinus pinaster Ait. recruitment in Orense (N.W. of Spain). For. Ecol. Manage., 255, 1294-1304. https://doi.org/10.1016/j. foreco.2007.10.034

Fernández-Manso, A., Quintano, C. 2015. Evaluating Landsat ETM+ emissivity-enhanced spectral indices for burn severity discrimination in Mediterranean forest ecosystems. Remote Sensing Letters, 6(4), 302–310. https://doi.org/10.1080/215070 4X.2015.1029093

García-Duro, J., Manso, A., Cruz, O., Basanta, M., Casal M., Reyes, O. 2016. Regeneración post-fuego en relación con la severidad del incendio en un área atlántica de Galicia. Bases para la restauración. Cuad. Soc. Esp. Cienc. For., 42, 129-140.

Hall, R.J., Freeburn, J.T., Groot, W.J.G., Pritchard, J.M., Lynham, T.J., Landry, R. 2008. Remote sensing of burn severity: Experience from western Canada boreal fires, International Journal of Wildland Fire, 17, 476-489. https://doi.org/10.1071/WF08013

Holden, Z.A., Morgan, P., Evans, J.S. 2009. A predictive model of burn severity based on 20-year satelliteinferred burn severity data in a large southwestern U.S. wilderness area. For. Ecol. Manage., 258(11), 2399-2406. https://doi.org/10.1016/j. foreco.2009.08.017

Hudak, A.T., Morgan, P., Bobbitt, M.J., Smith, A.M.S., Lewis, S.A., Lentile, L.B., Robichaud, P.R., Clark, J.T., McKinley, R.A. 2007. The relationship of multispectral satellite imagery to immediate fire effects. Fire Ecology, 3, 64-90. https://doi. org/10.4996/fireecology.0301064

Keeley, J. E. 2009. Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18(1), 116- 126. https://doi.org/10.1071/WF07049

Key, C.H., Benson, N.C. 2006. Landscape Assessment (LA). In: Lutes, D.C., Keane, R.E., Caratti, J.F., Key, C.H., Benson, N.C., Sutherland, S., & Gangi, L.J. (eds,). FIREMON: Fire effects monitoring and inventory system. USDA Forest Service, Rocky Mountain Research Station. Gen. Tech. Rep. RMRSGTR-164-CD, 1-55.

Lentile, L.B., Holden, Z.A, Smith, A.M.S., Falkowki, M.J., Hudak, A.T., Morgan, P., Lewis, S. A., Gessler, P.E., Benson, N.C. 2006. Remote sensing techniques to assess active fire characteristics and post-fire effects. Int. J. Wildland Fire, 15, 319-345. https:// doi.org/10.1071/WF05097

Lentile, L.B., Smith, A.M.S., Hudak, A.T., Morgan, P., Bobbitt, M.J., Lewis, S.A., Robichaud, P.R., 2009. Remote sensing for prediction of 1-year post-fire ecosystem condition. International Journal of Wildland Fire, 18, 594-608. https://doi. org/10.1071/WF07091

Martín, M.P., Chuvieco, E., Oliva, P., RodríguezVerdú, F., Nieto, H., Padrón, D. 2007. Un ejemplo práctico de aplicación operativa de la teledetección a la gestión de riesgos naturales: Cartografía y evaluación urgente de áreas quemadas en Galicia. Cuadernos de Investigación Geográfica, 33, 19-37. https://doi.org/10.18172/cig.1187

Miller, J.D., Thode, A.E. 2007. Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 109, 66- 80. https://doi.org/10.1016/j.rse.2006.12.006

Miller, J.D., Knapp, E.E., Key, C.H., Skinner, C.N., Isbell, C.J., Creasy, R.M., Sherlock, J.W. 2009. Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sensing, 113, 645-656. https://doi.org/10.1016/j. rse.2008.11.009

Montealegre, A. L., Lamelas, M. T., Tanase, M. A., de la Riva, J. 2014. Forest fire severity assessment using ALS data in a Mediterranean environment. Remote Sensing, 6(5), 4240-4265. https://doi. org/10.3390/rs6054240

Montorio Llovería, R., Pérez-Cabello, F., GarcíaMartín, A., Vlassova, L., de la Riva Fernández, J. 2014. La severidad del fuego: revisión de conceptos, métodos y efectos ambientales. En: Arnáez Vadillo, J., González Sampériz, P., Lasanta Martínez, T., Valero Garcés, B.L. (ed.) Geoecología, cambio ambiental y paisaje: homenaje al profesor José María García Ruiz. Consejo Superior de Investigaciones Científicas, CSIC, Instituto Pirenaico de Ecología: Universidad de La Rioja.

Morgan, P., Keane, R. E., Dillon, G. K., Jain, T. B., Hudak, A. T., Karau, E. C., Strand, E. K. 2014. Challenges of assessing fire and burn severity using field measures, remote sensing and modelling. International Journal of Wildland Fire, 23(8), 1045-1060. https://doi.org/10.1071/WF13058

Parks, S.A., Dillon, G.K., Miller, C. 2014. A New Metric for Quantifying Burn Severity: The Relativized Burn Ratio. Remote Sensing, 6, 1827- 1844. https://doi.org/10.3390/rs6031827

Pérez-Cabello, F., de la Riva Fernández, J., Montorio Llovería, R., García-Martín, A. 2006. Mapping erosion-sensitive areas after wildfires using fieldwork, remote sensing, and geographic information systems techniques on a regional scale. J. Geophys. Res., 111. https://doi. org/10.1029/2005JG000148

Picotte, J.J., Robertson K.M. 2011. Validation of remote sensing of burn severity in south-eastern US ecosystems. International Journal of Wildland Fire, 20(3), 453-464. https://doi.org/10.1071/ WF10013

Robichaud, P.R., Beyers, J.L., Neary, D.G. 2000. Evaluating the effectiveness of postfire rehabilitation treatments. USDA Forest Service. General Technical Report. RMRS-GTR.-63.

Soverel N.O., Perrakis, D.D.B., Coops N.C. 2010. Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada. Remote Sensing of Environment, 114, 1896-1909. https:// doi.org/10.1016/j.rse.2010.03.013

Van Wagtendok, J.V., Roo, R.R., Key, C.H. 2004. Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment, 92, 397-408. https://doi. org/10.1016/j.rse.2003.12.015

Vega, J.A., Fernández., C., Jiménez, E., Ruiz, A.D. 2009a. Evidencias de cambio climático en Galicia a través de la tendencia de los índices de peligro de incendios forestales. En: Análisis de Evidencias e Impactos del Cambio Climático en Galicia. Santiago de Compostela. Xunta de Galicia. 173- 194.

Vega, J.A., Fernández., C., Jiménez, E., Ruiz, A.D. 2009b. Impacto de un escenario de cambio climático sobre el peligro de incendios en Galicia. En: Análisis de Evidencias e Impactos del Cambio Climático en Galicia. Santiago de Compostela. Xunta de Galicia. 583-607.

Vega, J.A., Fonturbel, T., Fernández, C., Arellano, A., Díaz-Raviña, M., Carballas, M.T., Martín, A., González-Prieto, S., Merino A., Benito, E. 2013. Acciones urgentes contra la erosión en áreas forestales quemadas. Guía para su planificación en Galicia. Xunta de Galicia. pp. 139.

Vega, J.A., Fernández, C., Fonturbel, T. 2015. Comparing the effectiveness of seeding and mulching + seeding in reducing soil erosion after a high severity fire in Galicia (NW Spain). Ecological Engineering, 74, 206–212. https://doi. org/10.1016/j.ecoleng.2014.10.019

Veraverbeke, S., Harris, S., Hook, S. 2011. Evaluating Spectral Indices for Burned Area Discrimination using MODIS/ASTER (MASTER) Airborne Simulator Data. Remote Sensing of Environment, 115, 2702–2709. https://doi.org/10.1016/j. rse.2011.06.010

Veraverbeke, S., Hook, S., Hulley, G. 2012. An alternative spectral index for rapid fire severity assessments. Remote Sens. Environ., 123, 72-80. https://doi.org/10.1016/j.rse.2012.02.025

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