Arellano, S., Vega, J.A., Rodríguez, F., Fernández, C., Vega-Nieva, D., Ruiz-González, A.D. 2017. Validación de los índices de teledetección dNBR y RdNBR para determinar la severidad del fuego en el incendio forestal de Oia-O Rosal (Pontevedra) en 2013. Revista de Teledetección, (49), 49-61. https://doi.org/10.4995/raet.2017.7137
Balocchi, F., Flores, N., Neary, D., White, D.A., Silberstein, R., de Arellano, P.R. 2020. The effect of the 'Las Maquinas' wildfire of 2017 on the hydrologic balance of a high conservation value Hualo (Nothofagus glauca (Phil.) Krasser) forest in central Chile. Forest Ecology and Management, 477, 118482. https://doi.org/10.1016/j.foreco.2020.118482
Barbosa, P.M., Stroppiana, D., Grégoire, J.M., Cardoso Pereira, J.M. 1999. An assessment of vegetation fire in Africa (1981-1991): Burned areas, burned biomass, and atmospheric emissions.Global Biogeochemical Cycles, 13(4), 933-950. https://doi.org/10.1029/1999GB900042
[+]
Arellano, S., Vega, J.A., Rodríguez, F., Fernández, C., Vega-Nieva, D., Ruiz-González, A.D. 2017. Validación de los índices de teledetección dNBR y RdNBR para determinar la severidad del fuego en el incendio forestal de Oia-O Rosal (Pontevedra) en 2013. Revista de Teledetección, (49), 49-61. https://doi.org/10.4995/raet.2017.7137
Balocchi, F., Flores, N., Neary, D., White, D.A., Silberstein, R., de Arellano, P.R. 2020. The effect of the 'Las Maquinas' wildfire of 2017 on the hydrologic balance of a high conservation value Hualo (Nothofagus glauca (Phil.) Krasser) forest in central Chile. Forest Ecology and Management, 477, 118482. https://doi.org/10.1016/j.foreco.2020.118482
Barbosa, P.M., Stroppiana, D., Grégoire, J.M., Cardoso Pereira, J.M. 1999. An assessment of vegetation fire in Africa (1981-1991): Burned areas, burned biomass, and atmospheric emissions.Global Biogeochemical Cycles, 13(4), 933-950. https://doi.org/10.1029/1999GB900042
Botella-Martínez, M.A., Fernández-Manso, A. 2017. Estudio de la severidad post-incendio en la Comunidad Valenciana comparando los índices dNBR, RdNBR y RBR a partir de imágenes Landsat 8. Revista de Teledetección, (49), 33-47. https://doi.org/10.4995/raet.2017.7095
Bowman, D.M., Moreira-Muñoz, A., Kolden, C.A., Chávez, R.O., Muñoz, A.A., Salinas, F.,... Johnston, F.H. 2019. Human-environmental drivers and impacts of the globally extreme 2017 Chilean fires. Ambio, 48(4), 350-362. https://doi.org/10.1007/s13280-018-1084-1
Cai, L., Wang, M. 2022. Is the RdNBR a better estimator of wildfire burn severity than the dNBR? A discussion and case study in southeast China. Geocarto International, 37(3), 758-772. https://doi.org/10.1080/10106049.2020.1737973
Castillo-Soto, M.E. 2012. The identification and assessment of areas at risk of forest fire using fuzzy methodology. Applied Geography, 35(1-2), 199-207. https://doi.org/10.1016/j.apgeog.2012.07.001
Chuvieco, E., Mouillot, F., Van der Werf, G.R., San Miguel, J., Tanase, M., Koutsias, N.,... Giglio, L. 2019. Historical background and current developments for mapping burned area from satellite Earth observation. Remote Sensing of Environment, 225, 45-64. https://doi.org/10.1016/j.rse.2019.02.013
Chuvieco, E., Congalton, R.G. 1988. Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 3(4), 41-53. https://doi.org/10.1080/10106048809354180
Corporación Nacional Forestal (CONAF) 2017. Análisis de la Afectación y Severidad de los Incendios Forestales ocurridos en enero y febrero de 2017 sobre los usos de suelo y los ecosistemas naturales presentes entre las regiones de Coquimbo y Los Ríos de Chile. Informe Técnico. 56 p. Santiago, Chile.
Curtis, P.G., Slay, C.M., Harris, N.L., Tyukavina, A., Hansen, M.C. 2018. Classifying drivers of global forest loss. Science, 361(6407), 1108-1111. https://doi.org/10.1126/science.aau3445
Delegido, J., Pezzola, A., Casella, A., Winschel, C., Urrego, P., Jimenez-Munoz, J.C.,... & Moreno, J. 2018. Estimación del grado de severidad de incendios en el sur de la provincia de Buenos Aires, Argentina, usando Sentinel-2 y su comparación con Landsat-8. Revista de Teledetección, (51), 47-60. https://doi.org/10.4995/raet.2018.8934
Dice, L.R. 1945. Measures of the amount of ecologic association between species. Ecology, 26(3), 297-302. https://doi.org/10.2307/1932409
Duncan, B.N., Martin, R.V., Staudt, A.C., Yevich, R., Logan, J.A. 2003. Interannual and seasonal variability of biomass burning emissions constrained by satellite observations. Journal of Geophysical Research: Atmospheres, 108(D2), ACH-1. https://doi.org/10.1029/2002JD002378
Fassnacht, F.E., Schmidt-Riese, E., Kattenborn, T., Hernández, J. 2021. Explaining Sentinel 2-based dNBR and RdNBR variability with reference data from the bird's eye (UAS) perspective. International Journal of Applied Earth Observation and Geoinformation, 95, 102262. https://doi.org/10.1016/j.jag.2020.102262
Garreaud, R.D., Alvarez-Garreton, C., Barichivich, J., Boisier, J.P., Christie, D., Galleguillos, M.,... Zambrano-Bigiarini, M. 2017. The 2010- 2015 megadrought in central Chile: Impacts on regional hydroclimate and vegetation. Hydrology and earth system sciences, 21(12), 6307-6327. https://doi.org/10.5194/hess-21-6307-2017
Giglio, L., Randerson, J.T., Van der Werf, G.R., Kasibhatla, P.S., Collatz, G.J., Morton, D.C., DeFries, R.S. 2010. Assessing variability and longterm trends in burned area by merging multiple satellite fire products. Biogeosciences, 7(3), 1171-1186. https://doi.org/10.5194/bg-7-1171-2010
Giglio, L., Randerson, J.T., Van Der Werf, G.R. 2013. Analysis of daily, monthly, and annual burned area using the fourth-generation global fire emissions database (GFED4). Journal of Geophysical Research: Biogeosciences, 118(1), 317-328. https://doi.org/10.1002/jgrg.20042
Giglio, L., Boschetti, L., Roy, D.P., Humber, M.L., Justice, C.O. 2018. The Collection 6 MODIS burned area mapping algorithm and product. Remote sensing of environment, 217, 72-85. https://doi.org/10.1016/j.rse.2018.08.005
González, M.E., Sapiains, R., Gómez-González, S., Garreaud, R., Miranda, A., Galleguillos, M.,... & Castillo, I. 2020. Incendios forestales en Chile: causas, impactos y resiliencia. Centro de Ciencia del Clima y la Resiliencia (CR), 2.
Key, C.H., Benson, N.C. 2006. Landscape assessment (LA). In: Lutes, Duncan C., Keane, Robert E., Caratti, John F., Key, Carl H., Benson, Nathan C., Sutherland, Steve, Gangi, Larry J. 2006. FIREMON: Fire effects monitoring and inventory system. Gen. Tech. Rep. RMRS-GTR-164-CD. Fort Collins, CO: US Department of Agriculture, Forest Service, Rocky Mountain Research Station. p. LA-1-55, 164.
Handke, M. 2019. La (des) contextualización del conocimiento geográfico en el manejo del riesgo de incendios forestales en Chile como un desafío para la gobernanza. Revista de Geografía Norte Grande, (74), 65-91. https://doi.org/10.4067/S0718-34022019000300065
Heredia, Á., Martínez, S., Quintero, E., Piñeros, W., Chuvieco, E. 2003. Comparación de distintas técnicas de análisis digital para la cartografía de áreas quemadas con imágenes Landsat ETM+. GeoFocus. Revista Internacional de Ciencia y Tecnología de la Información Geográfica, (3), 216-234.
Ito, A., Penner, J.E. 2004. Global estimates of biomass burning emissions based on satellite imagery for the year 2000. Journal of Geophysical Research: Atmospheres, 109(D14). https://doi.org/10.1029/2003JD004423
Lentile, L.B., Holden, Z.A., Smith, A.M., Falkowski, M.J., Hudak, A.T., Morgan, P.,... Benson, N.C. 2006. Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire, 15(3), 319-345. https://doi.org/10.1071/WF05097
Llorens, R., Sobrino, J.A., Fernández, C., FernándezAlonso, J.M., Vega, J.A. 2021. A methodology to estimate forest fires burned areas and burn severity degrees using Sentinel-2 data. Application to the October 2017 fires in the Iberian Peninsula. International Journal of Applied Earth Observation and Geoinformation, 95, 102243. https://doi.org/10.1016/j.jag.2020.102243
Michalijos, M.P., Uboldi, J. 2013. Propuesta metodológica para la evaluación de áreas afectadas por incendios mediante el uso de imágenes satelitales (Sierra de la Ventana, Argentina). Revista de Geografía Norte Grande, (56), 223-234. https://doi.org/10.4067/S0718-34022013000300012
Milne, A.K. 1986. The use of remote sensing in mapping and monitoring vegetational change associated with bushfire events in Eastern Australia. Geocarto International, 1(1), 25-32. https://doi.org/10.1080/10106048609354022
Miranda, A., Mentler, R., Moletto-Lobos, Í., Alfaro, G., Aliaga, L., Balbontín, D.,... Urrutia, V. 2022. The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile. Earth System Science Data, 14(8), 3599-3613. https://doi.org/10.5194/essd-14-3599-2022
Mouillot, F., Field, C.B. 2005. Fire history and the global carbon budget: a 1× 1 fire history reconstruction for the 20th century. Global Change Biology, 11(3), 398-420. https://doi.org/10.1111/j.1365-2486.2005.00920.x
Mouillot, F., Narasimha, A., Balkanski, Y., Lamarque, J.F., Field, C.B. 2006. Global carbon emissions from biomass burning in the 20th century.Geophysical Research Letters, 33(1). https://doi.org/10.1029/2005GL024707
Mouillot, F., Schultz, M.G., Yue, C., Cadule, P., Tansey, K., Ciais, P., Chuvieco, E. 2014. Ten years of global burned area products from spaceborne remote sensing-A review: Analysis of user needs and recommendations for future developments. International Journal of Applied Earth Observation and Geoinformation, 26, 64-79. https://doi.org/10.1016/j.jag.2013.05.014
Peña, M.A., Martinez, G. 2021. Mapping damage on forests burnt in Central Chile by modelling ex-ante and ex-post spectral indices. BOSQUE, 42(2), 205-215. https://doi.org/10.4067/S0717-92002021000200205
Pérez Mato, J. 2017. Autonomous wildfire geolocation system based on thermographic and synthetic vision techniques. Doctoral dissertation. https://accedacris.ulpgc.es/jspui/handle/10553/26207).
Perilla, G.A., Mas, J.F. 2020. Google Earth Engine (GEE): una poderosa herramienta que vincula el potencial de los datos masivos y la eficacia del procesamiento en la nube. Investigaciones geográficas, (101). https://doi.org/10.14350/rig.59929
Roy, D.P., Boschetti, L., Smith, A.M. 2013. Satellite remote sensing of fires. Fire phenomena and the Earth system: An interdisciplinary guide to fire science, 77-93. https://doi.org/10.1002/9781118529539.ch5
Sánchez, A. 2003. Geografía de Chile. Editorial Bibliográfica Internacional, Santiago de Chile.
Santana, O.J., Hernández-Sosa, D., Martz, J., Smith, R.N. 2020. Neural network training for the detection and classification of oceanic mesoscale eddies. Remote Sensing, 12(16), 2625. https://doi. org/10.3390/rs12162625
Schroeder, W., Oliva, P., Giglio, L., Csiszar, I.A. 2014. The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment. Remote Sensing of Environment, 143, 85-96. https://doi.org/10.1016/j.rse.2013.12.008
Smith, R.B., Woodgate, P.W. 1985. Appraisal of fire damage and inventory for timber salvage by remote sensing in mountain ash forests in Victoria. Australian Forestry, 48(4), 252-263. https://doi.org/10.1080/00049158.1985.10674453
Úbeda, X., Sarricolea, P. 2016. Wildfires in Chile: A review. Global and Planetary Change, 146, 152-161. https://doi.org/10.1016/j.gloplacha.2016.10.004
van der Werf, G.R., Randerson, J.T., Giglio, L., Collatz, G.J., Kasibhatla, P.S., Arellano Jr, A.F. 2006. Interannual variability in global biomass burning emissions from 1997 to 2004. Atmospheric Chemistry and Physics, 6(11), 3423-3441. https://doi.org/10.5194/acp-6-3423-2006
Villagra, P., Paula, S. 2021. Wildfire management in Chile: Increasing risks call for more resilient communities. Environment: Science and Policy for Sustainable Development, 63(3), 4-14. https://doi.org/10.1080/00139157.2021.1898891
[-]