{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T01:21:51Z","timestamp":1772673711140,"version":"3.50.1"},"reference-count":82,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,7]],"date-time":"2018-09-07T00:00:00Z","timestamp":1536278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study develops a site specific burn severity modelling using remote sensing techniques to develop severity patterns on vegetation and soil in the fire prone region of the Palo Verde National Park in Guanacaste, Costa Rica. Terrain physical features, soil cover, and scorched vegetation characteristics were examined to develop a fire risk model and to quantify probable burned areas. Spectral signatures of affected areas were captured through multi-spectral analysis; i.e., Normalized Burn Ratio (NBR), Landsat derived differenced Normalized Burn Ratio (dNBR) and relativized dNBR (RdNBR). A partial unmixing algorithm, Mixture Tuned Matched Filtering (MTMF) was used to isolate endmembers for scorched vegetation and soil. The performance of dNBR and RdNBR for predicting ground cover components was acceptable with an overall accuracy of 84.4% and Cohen\u2019s Kappa 0.82 for dNBR and an overall accuracy of 89.4% and Cohen\u2019s Kappa 0.82 for RdNBR. Landsat derived RdNBR showed a strong correlation with scorched vegetation (r2 = 0.76) and moderate correlation with soil cover (r2 = 0.53), which outperformed dNBR. The ecologically diverse and unique park area is threatened by wetland fires, which pose a potential threat to various species. Human induced fires by poachers are a common occurrence in such areas to gain access to these species. This paper aims to prioritize areas that are at a higher risk from fire and model spatial adaptations in relation to the direction of fire within the affected wetlands. This assessment will help wildlife personnel in managing disturbed wetland ecosystems.<\/jats:p>","DOI":"10.3390\/rs10091427","type":"journal-article","created":{"date-parts":[[2018,9,7]],"date-time":"2018-09-07T11:47:41Z","timestamp":1536320861000},"page":"1427","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Remote Sensing Approach to Detect Burn Severity Risk Zones in Palo Verde National Park, Costa Rica"],"prefix":"10.3390","volume":"10","author":[{"given":"Papia F.","family":"Rozario","sequence":"first","affiliation":[{"name":"Department of Environmental Studies, Carleton College, Northfield, MN 55057, USA"}]},{"given":"Buddhika D.","family":"Madurapperuma","sequence":"additional","affiliation":[{"name":"Department of Forestry &amp; Wildland Resources and Department of Environmental Science &amp; Management, Humboldt State University, Arcata, CA 95521, USA"}]},{"given":"Yijun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Geology, Carleton College, Northfield, MN 55057, USA"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,7]]},"reference":[{"key":"ref_1","unstructured":"AL-Dhief, F.T., Sabri, N., Fouad, S., Latiff, N.A., and Albader, M.A.A. (2017). A review of forest fire surveillance technologies: Mobile ad-hoc network routing protocols perspective. J. King Saud Univ.-Comput. Inf. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.1126\/science.284.5421.1782a","article-title":"Forest on Fire","volume":"284","author":"Goldammer","year":"1999","journal-title":"Science"},{"key":"ref_3","unstructured":"Goldammer, J.G., and Jenkins, M.J. (1990). Fire in Ecosystem Dynamics, Mediterranean and Northern Perspectives, SPB Academic Publishing."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1038\/19066","article-title":"Large-scale impoverishment of Amazonian forests by logging and fire","volume":"398","author":"Nepstad","year":"1999","journal-title":"Nature"},{"key":"ref_5","first-page":"50","article-title":"Detecting land-cover change using mappable vegetation related indices: A case study from Sinharaja Man and the Biosphere Reserve","volume":"4","author":"Madurapperuma","year":"2014","journal-title":"J. Trop. For. Environ."},{"key":"ref_6","unstructured":"Agee, J.K. (1993). Fire Ecology of Pacific Northwest Forests, Island Press."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1890\/06-1658.1","article-title":"Conversion or conservation? Understanding wetland change in Northwest Costa Rica","volume":"18","author":"Daniels","year":"2008","journal-title":"Ecol. Appl."},{"key":"ref_8","unstructured":"Millennium Ecosystem Assessment (2005). Ecosystems and Human Well-Being: Wetlands and Water Synthesis, World Resources Institute."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Leblon, B., Bourgeau-Chavez, L., and San-Miguel-Ayanz, J. (2012). Use of remote sensing in wildfire management. Sustainable Development-Authoritative and Leading Edge Content for Environmental Management, IntechOpen.","DOI":"10.5772\/45829"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chuvieco, E., and Kasischke, E.S. (2007). Remote sensing information for fire management and fire effects assessment. J. Geophys. Res., 112.","DOI":"10.1029\/2006JG000230"},{"key":"ref_11","first-page":"42","article-title":"Multiscale mapping of burn area and severity using multisensor satellite data and spatial autocorrelation analysis","volume":"20","author":"Lanorte","year":"2013","journal-title":"Int. J Appl. Earth Obs."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.rse.2017.01.016","article-title":"Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem","volume":"191","author":"Meng","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.rse.2005.03.002","article-title":"Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+","volume":"96","author":"Epting","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez-Garc\u00eda, V., Quintano, C., Taboada, A., Marcos, E., Calvo, L., and Fern\u00e1ndez-Manso, A. (2018). Remote sensing applied to the study of fire regime attributes and their influence on post-fire greenness recovery in Pine ecosystems. Remote Sens., 10.","DOI":"10.3390\/rs10050733"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.rse.2003.12.015","article-title":"Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity","volume":"92","author":"Root","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1071\/WF9960125","article-title":"Remote sensing of forest fire severity and vegetation recovery","volume":"6","author":"White","year":"1996","journal-title":"Int. J. Wildland Fire"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lutes, D.C., Keane, R.E., Caratti, J.F., Key, C.H., Benson, N.C., Sutherland, S., and Gangi, L.J. (2006). FIREMON: Fire Effects Monitoring and Inventory System, US Department of Agriculture Forest Service, Rocky Mountain Research Station. Tech. Rep. RMRS-GTR-164-CD.","DOI":"10.2737\/RMRS-GTR-164"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2006.12.006","article-title":"Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)","volume":"109","author":"Miller","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.3390\/rs6031827","article-title":"A new metric for quantifying burn severity: The relativized burn ratio","volume":"6","author":"Parks","year":"2014","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1016\/j.rse.2008.11.009","article-title":"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","volume":"113","author":"Miller","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_21","unstructured":"Zhu, Z., Key, C., Ohlen, D., and Benson, N. (2006). Evaluate Sensitivities of Burn-Severity Mapping Algorithms for Different Ecosystems and Fire Histories in the United States, Final Report to the Joint Fire Science Program; Project: JFSP 01-1-4-12."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"456","DOI":"10.3390\/rs4020456","article-title":"How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods","volume":"4","author":"Cansler","year":"2012","journal-title":"Remote Sens."},{"key":"ref_23","first-page":"357","article-title":"Characterizing sub-pixel Landsat ETM+ fire severity on experimental fires in the Kruger National Park, South Africa","volume":"99","author":"Landmann","year":"2003","journal-title":"S. Afr. J. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.rse.2005.04.014","article-title":"Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African Savannahs","volume":"97","author":"Smith","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_25","unstructured":"Boardman, J.W. (1998, January 12\u201316). Leveraging the high dimensionality of AVIRIS data for improved subpixel target unmixing and rejection of false positives: Mixture tuned matched filtering. Proceedings of the Summaries of the Seventh Annual JPL Airborne Earth Science Workshop, Pasadena, CA, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1109\/36.298007","article-title":"Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach","volume":"32","author":"Harsanyi","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","unstructured":"Green, R.O. (1995, January 23\u201326). Mapping target signatures via partial unmixing of AVIRIS data. Proceedings of the Summaries of the Fifth Annual JPL Airborne Earth Science Workshop, Pasadena, CA, USA."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.rse.2005.01.003","article-title":"Hyperspectral data processing for repeat detection of small infestations of leafy spurge","volume":"95","author":"Glenn","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.rse.2005.10.024","article-title":"Mapping the effects of water stress on Sphagnum: Preliminary observations using airborne remote sensing","volume":"100","author":"Harris","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1016\/j.rse.2005.04.004","article-title":"Discrimination of hoary cress and determination of its detection limits via hyperspectral image processing and accuracy assessment techniques","volume":"96","author":"Mundt","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/S0034-4257(02)00061-5","article-title":"Estimation of leafy spurge cover from hyperspectral imagery using mixture tuned matched filtering","volume":"82","author":"Williams","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(90)90074-V","article-title":"Vegetation in deserts: I. A regional measure of abundance from multi-spectral images","volume":"31","author":"Smith","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_33","unstructured":"Boardman, J.W., and Kruse, F.A. (1994, January 9\u201312). Automated spectral analysis: A geological example using AVIRIS data, North Grapevine Mountains, Nevada. Proceedings of the Tenth Thematic Conference on Geological Remote Sensing, San Antonio, TX, USA."},{"key":"ref_34","first-page":"23","article-title":"Living with parasites in Palo Verde national park","volume":"1","author":"Kirksey","year":"2012","journal-title":"Environ. Hum."},{"key":"ref_35","unstructured":"Lindner, M., Garcia-Gonzalo, J., Kolstr\u00f6m, M., Geen, T., Reguera, R., Maroschek, M., Seidl, R., Lexer, M.J., Netherer, S., and Schopf, A. (2018, September 06). Impacts of Climate Change on European Forests and Options for Adaptation. Available online: https:\/\/ec.europa.eu\/agriculture\/external-studies\/euro-forests_en."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1071\/WF07151","article-title":"Are wildfires a disaster in the Mediterranean basin?\u2014A review","volume":"17","author":"Pausas","year":"2008","journal-title":"Int. J. Wildland Fires"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1016\/j.scitotenv.2016.03.115","article-title":"Resilience of Mediterranean Terrestrial ecosystems and fire severity in semiarid areas: Responses of Aleppo pine forests in the short, mid and long term","volume":"573","author":"Moya","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1111\/avsc.12053","article-title":"Burning season effects on the short-term post-fire vegetation dynamics of a Mediterranean heathland","volume":"17","author":"Luna","year":"2014","journal-title":"Appl. Veg. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1111\/nph.12921","article-title":"Evolutionary ecology of resprouting and seeding in fireprone ecosystems","volume":"204","author":"Pausas","year":"2014","journal-title":"New Phytol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.catena.2015.06.004","article-title":"Influence of wildfire severity on soil physical degradation in two pine forest stands of NW Spain","volume":"133","author":"Varela","year":"2015","journal-title":"Catena"},{"key":"ref_41","unstructured":"Boere, G.C., Galbraith, C.A., and Stroud, D.A. (2006). The importance of Costa Rica for resident and migratory waterbirds. Waterbirds around the World, The Stationery Office."},{"key":"ref_42","unstructured":"Jime\u00b4nez, J.A., and Gonzalez, E. (2001). Caracteristicasgenerales de la Cuenca del Rio Tempisque. La Cuenca del Rio Tempisque, Perspectivas para un ManejoIntegrado, Organizacio\u00b4n para EstudiosTropicales. Available online: http:\/\/www.wetlands.org\/Reports\/SiteReports\/CostaRica\/6CR001\/6CR001_ManPlansp.pdf."},{"key":"ref_43","unstructured":"Adair, C., Mora, N.B., Laing, J., and Rogers, Z. (2012). Restoration of the Wetlands in Palo Verde National Park: A Legal and Ecological Analysis, University of Florida and University of Costa Rica. Available online: https:\/\/www.law.ufl.edu\/_pdf\/academics\/academic-programs\/study-abroad\/costa-rica\/Ramsar-Report.pdf."},{"key":"ref_44","unstructured":"Luger, P., and Guinn, J. (2009, January 17\u201320). Geospatial analysis of effects of human-induced wetland fire on semi-fossorial turtles in Palo Verde, Costa Rica. Proceedings of the First Americans Land-Grant Consortium (Falcon), Poster Presentations, NIFA Waterfront Centre, Washington, DC, USA."},{"key":"ref_45","unstructured":"Arias, L. (2018, April 20). Wildfire Destroys 5 Hectares of Costa Rica\u2019s Palo Verde National Park. Available online: http:\/\/www.ticotimes.net\/2015\/02\/11\/wildfire-destroys-5-hectares-of-costa-ricas-palo-verde-national-park."},{"key":"ref_46","unstructured":"GLCF (2018, May 01). Global Land Cover Facility. Available online: http:\/\/glcfapp.glcf.umd.edu:8080\/esdi\/index.jsp."},{"key":"ref_47","first-page":"182","article-title":"Transition modeling of land-use dynamics in the Pipestem Creek, North Dakota, USA","volume":"5","author":"Rozario","year":"2017","journal-title":"J. Geosci. Environ. Prot."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Gomes, R., and Straub, J. (2017, January 5). Genetic algorithm for flood detection and evacuation route planning. Proceedings of the Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII, Anaheim, CA, USA.","DOI":"10.1117\/12.2266474"},{"key":"ref_49","first-page":"173","article-title":"LANDSAT-based detection and severity analysis of burned sugarcane plots in Tarlac, Philippines using differenced normalized burn ratio (dNBR)","volume":"XLII-4\/W1","author":"Baloloy","year":"2016","journal-title":"ISPRS Int. Arch. Photogramm."},{"key":"ref_50","unstructured":"Key, C.H., and Benson, N.C. (2006). Landscape assessment: Remote sensing of severity, the Normalized Burn Ratio; and ground measure of severity, the Composite Burn Index. FIREMON: Fire Effects Monitoring and Inventory System, RMRS-GTR, USDA Forest Service, Rocky Mountain Research Station."},{"key":"ref_51","unstructured":"Howard, S., Ohlen, D., McKinley, R., Zhu, Z., and Kitchen, J. (2002, January 10\u201315). Historical fire severity mapping from Landsat data. Proceedings of the Pecora 15\/Land Satellite Information IV\/ISPRS Commission I\/FIEOS Conference, Denver, CO, USA."},{"key":"ref_52","first-page":"31","article-title":"Mapping burns and natural reforestation using Thematic Mapper data","volume":"1","author":"Caselles","year":"1991","journal-title":"Geocarto Int."},{"key":"ref_53","unstructured":"McGrew, J.C., and Monroe, C.B. (2009). An Introduction to Statistical Problem Solving in Geography, Waveland Press."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.rse.2012.09.017","article-title":"An accuracy assessment of forest disturbance mapping in the western Great Lakes","volume":"128","author":"Zimmerman","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_55","unstructured":"Jensen, J.R. (2007). Remote Sensing of the Environment: An Earth Resource Perspective 2\/e, Pearson Prentice Hall."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"480","DOI":"10.2136\/sssaj2001.652480x","article-title":"Near-infrared reflectance spectroscopy\u2013principal components regression analyses of soil properties","volume":"65","author":"Chang","year":"2001","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"109","DOI":"10.4996\/fireecology.0301109","article-title":"Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in Southern California","volume":"3","author":"Lewis","year":"2007","journal-title":"Fire Ecol."},{"key":"ref_58","unstructured":"Amraoui, M., DaCamara, C.C., and Pereira, J.M. (2008, January 8\u201312). Fire detection and monitoring over Africa. Proceedings of the 2008 EUMETSAT Meteorological Satellite Conference, Darmstadt, Germany."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"563","DOI":"10.3856\/vol45-issue3-fulltext-6","article-title":"Secondary nesting beaches for leatherback turtles on the Pacific coast of Costa Rica","volume":"45","author":"Robinson","year":"2017","journal-title":"Lat. Am. J. Aquat. Res."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1109\/36.3001","article-title":"A transformation for ordering multispectral data in terms of image quality with implications for noise removal","volume":"26","author":"Green","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.rse.2017.12.029","article-title":"Burn severity metrics in fire-prone pine ecosystems along a climatic gradient using Landsat imagery","volume":"206","author":"Santamarta","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1109\/36.843007","article-title":"Constrained subpixel target detection for remotely sensed imagery","volume":"38","author":"Chang","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2006.11.027","article-title":"Postfire soil burn severity mapping with hyperspectral image unmixing","volume":"108","author":"Robichaud","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.rse.2006.02.025","article-title":"Assessing spatial patterns of forest fuel using AVIRIS data","volume":"102","author":"Jia","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to Kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1109\/TGRS.2005.843569","article-title":"Use of the Bradley-Terry model to quantify association in remotely sensed images","volume":"43","author":"Stein","year":"2005","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Walz, Y., Maier, S.W., Dech, S.W., Conrad, C., and Colditz, R.R. (2007). Classification of burn severity using Moderate Resolution Imaging Spectroradiometer (MODIS): A case study in the jarrah-marri forest of southwest Western Australia. J. Geophys. Res. Biogeosci., 112.","DOI":"10.1029\/2005JG000118"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.isprsjprs.2018.04.002","article-title":"A review of accuracy assessment for object-based image analysis: From per-pixel to per-polygon approaches","volume":"141","author":"Ye","year":"2018","journal-title":"ISPRS J. Photogramm."},{"key":"ref_69","unstructured":"Jensen, J.R. (2005). Introductory Digital Image Processing: A Remote Sensing Perspective, Prentice-Hall, Inc.. [3rd ed.]."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1080\/014311600210858","article-title":"Using Landsat TM data to estimate carbon release from burned biomass in an Alaskan spruce forest complex","volume":"21","author":"Michalek","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1023\/A:1020221123884","article-title":"Using remote sensing to assess Russian forest fire carbon emissions","volume":"55","author":"Isaev","year":"2002","journal-title":"Clim. Chang."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1080\/01431160210144732","article-title":"Influence of fire severity on plant regeneration by means of remote sensing imagery","volume":"24","author":"Lloret","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1071\/WF04010","article-title":"Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data","volume":"14","author":"Cocke","year":"2005","journal-title":"Int. J. Wildland Fire"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1071\/WF08013","article-title":"Remote sensing of burn severity: Experience from western Canada boreal fires","volume":"17","author":"Hall","year":"2008","journal-title":"Int. J. Wildland Fire"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"5159","DOI":"10.1080\/01431160701395161","article-title":"Evaluation of linear spectral unmixing and \u0394NBR for predicting post-fire recovery in a North American ponderosa pine forest","volume":"28","author":"Smith","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.rse.2006.08.006","article-title":"Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing","volume":"106","author":"Kokaly","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1071\/WF05051","article-title":"Remote sensing of fire severity in the Blue Mountains: Influence of vegetation type and inferring fire intensity","volume":"15","author":"Hammill","year":"2006","journal-title":"Int. J. Wildland Fire"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1080\/01431160600979115","article-title":"MERIS Full Resolution data for mapping level-of-damage caused by forest fires: The Valencia de Alc\u00e1ntara event in August 2003","volume":"28","author":"Cuevas","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"4219","DOI":"10.1080\/01431160500113492","article-title":"Using MODIS to evaluate heterogeneity of biomass burning in southern African savannahs: A case study in Etosha","volume":"26","author":"Alleaume","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"3188","DOI":"10.1038\/srep03188","article-title":"Deep cognitive imaging systems enable estimation of continental-scale fire incidence from climate data","volume":"3","author":"Dutta","year":"2013","journal-title":"Sci. Rep."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/S0034-4257(03)00070-1","article-title":"Fire radiative energy for quantitative study of biomass burning: Derivation from the BIRD experimental satellite and comparison to MODIS fire products","volume":"86","author":"Wooster","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_82","first-page":"2806","article-title":"Development and validation of fire damage-severity indices in the framework of the PREFER project","volume":"9","author":"Laneve","year":"2016","journal-title":"IEEE J. Sel. Top. Appl."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/9\/1427\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:19:19Z","timestamp":1760195959000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/9\/1427"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,7]]},"references-count":82,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2018,9]]}},"alternative-id":["rs10091427"],"URL":"https:\/\/doi.org\/10.3390\/rs10091427","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,7]]}}}