Damage Assessment and Recovery Mapping for the "Las Peñuelas" Wildfire, Moguer (Huelva). Satellite Imagery. Year 2017
DOI:
https://doi.org/10.4995/raet.2020.13082Keywords:
forest fire, INFOCA, burned area, fire severity, recovery of the vegetation, RBR, NDVIAbstract
Deep knowledge of the regeneration processes after a forest fire is key to addressing their adverse environmental impacts, these are especially evident in the vegetation. In the post-fire environment context, the fire severity constitutes a critical variable that affects the ecosystem response in terms of vegetation recovery and hydrogeomorphological dynamics after the fire. Therefore, the severity accurate assessment is essential for the burned areas management because of it allows the identification of priority areas and, therefore, it helps to carry out recovery strategies and measures. The area of interest is located in the natural place of Las Peñuelas (Huelva), where a large fire took place on June 24, 2017 that affected almost 10 000 ha. The methodology was based on the calculation of the RBR (Relativized Burn Ratio) spectral index to estimate the severity of the fire, and the NDVI (Normalized Difference Vegetation Index) index to evaluate the recovery of vegetal vigor. For the work, images from the Sentinel-2 and Pleiades satellites, images acquired by UAV (Unmanned Aerial Vehicle) and field samplings were used. The result was a cartography showing the levels of recovery or degradation of the affected vegetation.
Downloads
References
Bastarrika, A., Chuvieco, E., Martín, M.P. 2011. Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: balancing omission and commission errors. Remote Sens. Environ., 115, 1003-1012. https://doi.org/10.1016/j.rse.2010.12.005
Blackburn, G.A., Milton, E.J. 1995. Seasonal variations in the spectral reflectance of deciduous tree canopies. International Journal of Remote Sensing, 16, 709-720. https://doi.org/10.1080/01431169508954435
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(12), 456-483. https://doi.org/10.3390/rs4020456
Carpintero, I., Montoya, G., Granado, L., Méndez, E., Pino, I., Prieto, R., Vales, J.J., Salas, F.J.,Venegas, J., Cáceres, F., Moreira, J.M., Giménez de Azcárate, F. 2017. Cartografía de la afección del incendio en Huesa, Quesada y Cabra de Santo Cristo (Jaén) con imágenes satelitales. Nuevas plataformas y sensores aplicados a la gestión del Agua, la Agricultura y el Medio Ambiente. XVII Congreso de la Asociación Española de Teledetección, 181-184.
Chavez, P.S. Jr. 1996. Image-based atmospheric corrections—revisited and revised. Photogrammetric Engineering and Remote Sensing, 62(9):1025-1036.
Chuvieco, E., Riaño, D., Danson, F.M., Martin, P. 2006. Use of radiactive tranfer model to simulate the postfire spectral response to burn severity. Journal of Geophysical Research, 111. https://doi.org/10.1029/2005JG000143
Consejería de Agricultura, Ganadería, Pesca y Desarrollo Sostenible. Informe ejecutivo del incendio de Las Peñuelas Moguer (Huelva).
De Santis, A. et al. 2007. Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models. Remote Sensing of Environment, 108(4), 422-435. https://doi.org/10.1016/j.rse.2006.11.022
Dedios-Mimbela N.J. 2006. Análisis de diferentes métodos de clasificación de una imagen de satélite para caracterizar la superficie afectada por incendio forestal en ecosistemas de bosque. Servicio Nacional de Meteorología e Hidrología SENAMHI.
Díaz-Delgado, R., Pons, X. 2003. Análisis comparativo de diferentes cartografías de incendios forestales. Revista de Teledetección, 20, 11-15.
Doblas-Miranda, E., Martínez-Vilalta, J., Lloret, F., Álvarez, A., Ávila, A., Bonet, F.J., Brotons, L., Castro, J., Curiel Yuste, J., Díaz, M., Ferrandis, P., García-Hurtado, E., Iriondo, J.M., Keenan, T.F., Latron, J., Llusià, J., Loepfe, L., Mayol, M., Moré, G., Moya, D., Peñuelas, J., Pons, X., Poyatos, R., Sardans, J., Sus, O., Vallejo, V.R., Vayreda, J., Retana, J. 2015. Reassessing global change research priorities in mediterranean terrestrial ecosystems: how far have we come and where do we go from here? Global Ecology and Biogeography, 24(1), 25-43. https://doi.org/10.1111/geb.12224
Escuin, S., Navarro, R., Fernández, P. 2008. Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images, International Journal of Remote Sensing, 29(4), 1053-1073. https://doi.org/10.1080/01431160701281072
Fleiss, J.L., Cohen, J., Everitt, B.S. 1969. Large sample standard errors of kappa and wighted kappa. Psychologycal Bulletin, 72, 323-327.https://doi.org/10.1037/h0028106
Gamon, J.A., Field, C.B., Goulden, M.L., Griffin, K.L., Hartley, A.E., Joel, G., Peñuelas, J., Valentini, R. 1995. Relationships between NDVI, canopy, structure and photosynthesis in three Californian vegetation types. Ecological Applications, 5, 28-41. https://doi.org/10.2307/1942049
García-Martínez, E., Pérez-Cabello, F. 2015. Análisis de la regeneración vegetal mediante imágenes Landsat-8 y el producto MCD15A2 de MODIS: el caso del incendio de O Pindo (Galicia). En Análisis espacial y representación geográfica: innovación y aplicación. Universidad de Zaragoza - AGE (2015): 621-630.
Granado, L., Pino, I., Vales, J.J., Prieto, R., Méndez, E., Rodríguez, M., Giménez de Azcárate, F., Ortega, E., Moreira, J.M. 2019. Cartografía de la recuperación vegetal del incendio de Las Peñuelas en Moguer (Huelva) con imágenes satelitales. En Hacia una visión del cambio climático. XVIII Congreso de la Asociación Española de Teledetección. Valladolid, España, 24-27 septiembre. pp. 155-158. ISBN: 978-84-1320-038-5.
Justice, C.O., Townshend, J.R.G., Holben, B.N., Tucker, E.C. 1985. Analysis of the phenology of global vegetation using meteorological satellite data. International Journal of Remote Sensing, 6, 1271-1318. https://doi.org/10.1080/01431168508948281
Junta de Andalucía. Boletin Oficial de la Junta de Andalucía. Ley 5/1999, de 29 de junio, de Prevención y Lucha contra los Incendios Forestales. https://juntadeandalucia.es/boja/1999/82/1
Key, C.H., Benson, N. 2005. Landscape assessment: ground measure of severity, the Composite Burn Index; and remote sensing of severity, the Normalized Burn Ratio. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station.
Key, C.H. 2006. Ecological and sampling constraints on defining landscape fire severity. Fire Ecology, 2, 34-59. https://doi.org/10.4996/fireecology.0202034
Malak, D.A., Pausas, J.G., Pardo-Pascual, J.E., Ruiz, L.A. 2015. Fire Recurrence and the Dynamics of the Enhanced Vegetation Index in a Mediterranean Ecosystem. International Journal of Applied Geospatial Research, 6(2), 18-35. https://doi.org/10.4018/ijagr.2015040102
Manzo-Delgado, L., López-García, J. 2013. Detección de áreas quemadas en el sureste de México, utilizando índices pre y post-incendio NBR y BAI, derivados de compuestos MODIS”, GeoFocus, 13(2), 66-83. ISSN: 1578- 5157.
Miller, J.D., Yool, S.R. 2002. Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of Envairoment, 82, 481-496. https://doi.org/10.1016/S0034-4257(02)00071-8
Montorio, R., Pérez-Cabello, F., García-Martín, A., Vlassova, L., de la Riva-Fernández, J. 2014. La severidad del fuego: Revisión de conceptos, métodos y efectos ambientales. En: José Arnáez, Penélope González-Sampériz, Teodoro Lasanta y Blas L. Valero Garcés (eds.). Geoecología, cambio ambiental y paisaje: homenaje al profesor José María García Ruiz. Logroño: Instituto Pirenaico de Ecología (CSIC): Universidad de La Rioja, España.
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
Pereira, J.M.C., Sa, A.C.L., Sousa, A.M.O., Silva, J.M.N., Santos, T.N., Carreiras, J.M.B. 1999. Spectral characterisation and discrimination of burnt areas. In: E. Chuvieco (Ed.). Remote Sensing of Large Wildfires in the European Mediterranean Basin. Springer-Verlag, Berlin. 123-138. https://doi.org/10.1007/978-3-642-60164-4_7
Plan de restauración de los montes públicos afectados por el incendio forestal de Las Peñuelas 2017: sector occidental del Parque Natural de Doñana, Coto Mazagón y ordenados de Moguer. Consejería de Agricultura, Ganadería, Pesca y Desarrollo Sostenible. Junta de Andalucía. Septiembre 2019.
Quintano, C., Fernández-Manso, A., Roberts, D.A. 2013. Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sensing of Environment, 136, 76-88. https://doi.org/10.1016/j.rse.2013.04.017
Roughgarden, J.S.W., Running, S.W., Matson, P.A. 1991. What does remote sensing do for ecology? Ecology, 72, 1918-1922. https://doi.org/10.2307/1941546
Stehman, S. V, Czaplewski, R.L. 1998. Design and Analysis for Thematic Map Accuracy Assessment - an application of satellite imagery. Remote Sensing of Environment, 64, 331-344. https://doi.org/10.1016/S0034-4257(98)00010-8
Downloads
Published
Issue
Section
License
This journal is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
