{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T09:53:32Z","timestamp":1774950812527,"version":"3.50.1"},"reference-count":109,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Internal Research Plan of the University of Castilla-La Mancha, co-financed by the European Social Fund","award":["2020-PREDUCLM-16032"],"award-info":[{"award-number":["2020-PREDUCLM-16032"]}]},{"name":"Internal Research Plan of the University of Castilla-La Mancha, co-financed by the European Social Fund","award":["RTA2017-0042-C05-05"],"award-info":[{"award-number":["RTA2017-0042-C05-05"]}]},{"name":"Internal Research Plan of the University of Castilla-La Mancha, co-financed by the European Social Fund","award":["SBPLY\/19\/180501\/000130\/1"],"award-info":[{"award-number":["SBPLY\/19\/180501\/000130\/1"]}]},{"name":"Internal Research Plan of the University of Castilla-La Mancha, co-financed by the European Social Fund","award":["PID2020-116494RR-C43"],"award-info":[{"award-number":["PID2020-116494RR-C43"]}]},{"name":"Spanish Institute for Agricultural Research and Technology (INIA)","award":["2020-PREDUCLM-16032"],"award-info":[{"award-number":["2020-PREDUCLM-16032"]}]},{"name":"Spanish Institute for Agricultural Research and Technology (INIA)","award":["RTA2017-0042-C05-05"],"award-info":[{"award-number":["RTA2017-0042-C05-05"]}]},{"name":"Spanish Institute for Agricultural Research and Technology (INIA)","award":["SBPLY\/19\/180501\/000130\/1"],"award-info":[{"award-number":["SBPLY\/19\/180501\/000130\/1"]}]},{"name":"Spanish Institute for Agricultural Research and Technology (INIA)","award":["PID2020-116494RR-C43"],"award-info":[{"award-number":["PID2020-116494RR-C43"]}]},{"name":"Junta Comunidades Castilla-La Mancha","award":["2020-PREDUCLM-16032"],"award-info":[{"award-number":["2020-PREDUCLM-16032"]}]},{"name":"Junta Comunidades Castilla-La Mancha","award":["RTA2017-0042-C05-05"],"award-info":[{"award-number":["RTA2017-0042-C05-05"]}]},{"name":"Junta Comunidades Castilla-La Mancha","award":["SBPLY\/19\/180501\/000130\/1"],"award-info":[{"award-number":["SBPLY\/19\/180501\/000130\/1"]}]},{"name":"Junta Comunidades Castilla-La Mancha","award":["PID2020-116494RR-C43"],"award-info":[{"award-number":["PID2020-116494RR-C43"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033 \u201cERDF a way of making Europe\u201d","award":["2020-PREDUCLM-16032"],"award-info":[{"award-number":["2020-PREDUCLM-16032"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033 \u201cERDF a way of making Europe\u201d","award":["RTA2017-0042-C05-05"],"award-info":[{"award-number":["RTA2017-0042-C05-05"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033 \u201cERDF a way of making Europe\u201d","award":["SBPLY\/19\/180501\/000130\/1"],"award-info":[{"award-number":["SBPLY\/19\/180501\/000130\/1"]}]},{"name":"MCIN\/AEI\/10.13039\/501100011033 \u201cERDF a way of making Europe\u201d","award":["PID2020-116494RR-C43"],"award-info":[{"award-number":["PID2020-116494RR-C43"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The modification of fire regimes and their impact on vegetation recovery, soil properties, and fuel structure are current key research areas that attempt to identify the thresholds of vegetation\u2019s susceptibility to wildfires. This study aimed to evaluate the vulnerability of Mediterranean pine forests (Pinus halepensis Mill. and Pinus pinaster Aiton) to wildfires, analyzing two major forest fires that occurred in Yeste (Spain) in 1994 and 2017, affecting over 14,000 and 3200 hectares, respectively. Four recovery regions were identified based on fire severity\u2014calculated using the delta Normalized Burn Ratio (dNBR) index\u2014and recurrence: areas with high severity in 2017 but not in 1994 (UB94-HS17), areas with high severity in 1994 but not in 2017 (HS94-UB17), areas with high severity in both fires (HS94-HS17), and areas unaffected by either fire (UB94-UB17). The analysis focused on examining the recovery patterns of three spectral indices\u2014the Normalized Difference Vegetation Index (NDVI), Normalized Moisture Index (NDMI), and Normalized Burn Ratio (NBR)\u2014using the Google Earth Engine platform from 1990 to 2023. Additionally, the Relative Recovery Indicator (RRI), the Ratio of Eighty Percent (R80P), and the Year-on-Year average (YrYr) metrics were computed to assess the spectral recovery rates by region. These three spectral indices showed similar dynamic responses to fire. However, the Mann\u2013Kendall and unit root statistical tests revealed that the NDVI and NDMI exhibited distinct trends, particularly in areas with recurrence (HS94-HS17). The NDVI outperformed the NBR and NDMI in distinguishing variations among regions. These results suggest accelerated vegetation spectral regrowth in the short term. The Vegetation Recovery Capacity After Fire (VRAF) index showed values from low to moderate, while the Vulnerability to Fire (V2FIRE) index exhibited values from medium to high across all recovery regions. These findings enhance our understanding of how vegetation recovers from fire and how vulnerable it is to fire.<\/jats:p>","DOI":"10.3390\/rs16101718","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T08:33:03Z","timestamp":1715589183000},"page":"1718","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Fire Vulnerability, Resilience, and Recovery Rates of Mediterranean Pine Forests Using a 33-Year Time Series of Satellite Imagery"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9962-9914","authenticated-orcid":false,"given":"Esther","family":"Pe\u00f1a-Molina","sequence":"first","affiliation":[{"name":"Forest Ecology Research Group (ECOFOR), High Technical School of Agricultural and Forestry Engineering and Biotechnology, University of Castilla-La Mancha, University Campus, s\/n, 02071 Albacete, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1909-1200","authenticated-orcid":false,"given":"Daniel","family":"Moya","sequence":"additional","affiliation":[{"name":"Forest Ecology Research Group (ECOFOR), High Technical School of Agricultural and Forestry Engineering and Biotechnology, University of Castilla-La Mancha, University Campus, s\/n, 02071 Albacete, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2397-5543","authenticated-orcid":false,"given":"Eva","family":"Marino","sequence":"additional","affiliation":[{"name":"AGRESTA Sociedad Cooperativa, c\/Duque de Fern\u00e1n N\u00fa\u00f1ez 2, 28012 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2298-9115","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"Tom\u00e9","sequence":"additional","affiliation":[{"name":"AGRESTA Sociedad Cooperativa, c\/Duque de Fern\u00e1n N\u00fa\u00f1ez 2, 28012 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9966-1869","authenticated-orcid":false,"given":"\u00c1lvaro","family":"Fajardo-Cantos","sequence":"additional","affiliation":[{"name":"Forest Ecology Research Group (ECOFOR), High Technical School of Agricultural and Forestry Engineering and Biotechnology, University of Castilla-La Mancha, University Campus, s\/n, 02071 Albacete, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0065-5838","authenticated-orcid":false,"given":"Javier","family":"Gonz\u00e1lez-Romero","sequence":"additional","affiliation":[{"name":"Department of Forestry and Environmental Engineering and Management, Technical University of Madrid, 28040 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6270-8408","authenticated-orcid":false,"given":"Manuel Esteban","family":"Lucas-Borja","sequence":"additional","affiliation":[{"name":"Forest Ecology Research Group (ECOFOR), High Technical School of Agricultural and Forestry Engineering and Biotechnology, University of Castilla-La Mancha, University Campus, s\/n, 02071 Albacete, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2374-7097","authenticated-orcid":false,"given":"Jorge","family":"de las Heras","sequence":"additional","affiliation":[{"name":"Forest Ecology Research Group (ECOFOR), High Technical School of Agricultural and Forestry Engineering and Biotechnology, University of Castilla-La Mancha, University Campus, s\/n, 02071 Albacete, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s42408-019-0062-8","article-title":"Changing Wildfire, Changing Forests: The Effects of Climate Change on Fire Regimes and Vegetation in the Pacific Northwest, USA","volume":"16","author":"Halofsky","year":"2020","journal-title":"Fire Ecol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tedim, F., Leone, V., and McGee, T.K. (2020). Extreme Wildfire Events and Disasters, Elsevier.","DOI":"10.1016\/B978-0-12-815721-3.00001-1"},{"key":"ref_3","unstructured":"Castellnou, M. (2023, March 13). Los Incendios de Sexta Generaci\u00f3n Son M\u00e1s Dif\u00edciles de Controlar y Afectan a Medio Planeta. Available online: https:\/\/www.lavanguardia.com\/ciencia\/planeta-tierra\/20180817\/451324516370\/incendios-sexta-generacion-marc-castellnou-cambio-climatico-regenarar-ecosistemas.html."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Varga, K., Jones, C., Trugman, A., Carvalho, L.M.V., McLoughlin, N., Seto, D., Thompson, C., and Daum, K. (2022). Megafires in a Warming World: What Wildfire Risk Factors Led to California\u2019s Largest Recorded Wildfire. Fire, 5.","DOI":"10.3390\/fire5010016"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1071\/WF22046","article-title":"Rivers up in Smoke: Impacts of Australia\u2019s 2019\u20132020 Megafires on Riparian Systems","volume":"31","author":"Fryirs","year":"2022","journal-title":"Int. J. Wildland Fire"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Malandra, F., Vitali, A., Morresi, D., Garbarino, M., Foster, D.E., Stephens, S.L., and Urbinati, C. (2022). Burn Severity Drivers in Italian Large Wildfires. Fire, 5.","DOI":"10.3390\/fire5060180"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1898","DOI":"10.1111\/geb.13588","article-title":"Increasing Threat of Wildfires: The Year 2020 in Perspective: A Global Ecology and Biogeography Special Issue","volume":"31","author":"Nolan","year":"2022","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Costafreda-Aumedes, S., Cardil, A., Molina, D.M., Daniel, S.N., Mavsar, R., and Vega-Garcia, C. (2015). Analysis of Factors Influencing Deployment of Fire Suppression Resources in Spain Using Artificial Neural Networks. iForest-Biogeosci. For., 9.","DOI":"10.3832\/ifor1329-008"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"117707","DOI":"10.1016\/j.jenvman.2023.117707","article-title":"Incorporating Fire-Smartness into Agricultural Policies Reduces Suppression Costs and Ecosystem Services Damages from Wildfires","volume":"337","author":"Sil","year":"2023","journal-title":"J. Environ. Manag."},{"key":"ref_10","unstructured":"WWF (2023, March 13). Informe Incendios Forestales 2020: El Planeta en Llamas. Available online: https:\/\/www.wwf.es\/?54921\/Informe-incendios-forestales-2020-El-planeta-en-llamas."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"art14","DOI":"10.1890\/ES10-00102.1","article-title":"A Sensitive Slope: Estimating Landscape Patterns of Forest Resilience in a Changing Climate","volume":"1","author":"Johnstone","year":"2010","journal-title":"Ecosphere"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/ele.12889","article-title":"Evidence for Declining Forest Resilience to Wildfires under Climate Change","volume":"21","author":"Kemp","year":"2018","journal-title":"Ecol. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.gloplacha.2016.11.012","article-title":"A Review of the Combination among Global Change Factors in Forests, Shrublands and Pastures of the Mediterranean Region: Beyond Drought Effects","volume":"148","author":"Alonso","year":"2017","journal-title":"Glob. Planet. Chang."},{"key":"ref_14","unstructured":"Vaz, P. (2009). Wildfire Resilience in Mediterranean Landscapes: A Review, Technical University of Lisbon."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dell, B., Hopkins, A.J.M., and Lamont, B.B. (1986). Resilience in Mediterranean-Type Ecosystems, Springer. Tasks for Vegetation Science.","DOI":"10.1007\/978-94-009-4822-8"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2293","DOI":"10.1890\/0012-9658(2002)083[2293:SEODRI]2.0.CO;2","article-title":"Satellite Evidence of Decreasing Resilience in Mediterranean Plant Communities after Recurrent Wildfires","volume":"83","author":"Lloret","year":"2002","journal-title":"Ecology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.rse.2016.06.015","article-title":"Burn Severity Influence on Post-Fire Vegetation Cover Resilience from Landsat MESMA Fraction Images Time Series in Mediterranean Forest Ecosystems","volume":"184","author":"Quintano","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_18","unstructured":"Commission, F. (2014). Building Wildfire Resilience into Forest Management Planning."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Olson, R.L., Bengston, D.N., DeVaney, L.A., and Thompson, T.A.C. (2015). Wildland Fire Management Futures: Insights from a Foresight Panel, General Technical Report NRS-152.","DOI":"10.2737\/NRS-GTR-152"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1093\/biosci\/biv182","article-title":"The Science of Firescapes: Achieving Fire-Resilient Communities","volume":"66","author":"Smith","year":"2016","journal-title":"BioScience"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1146\/annurev.es.04.110173.000245","article-title":"Resilience and Stability of Ecological Systems","volume":"4","author":"Holling","year":"1973","journal-title":"Annu. Rev. Ecol. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.foreco.2012.07.031","article-title":"Exploring the Occurrence of Mega-Fires in Portugal","volume":"294","author":"Tedim","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1057\/s41291-020-00133-z","article-title":"Bouncing Back, If Not beyond: Challenges for Research on Resilience","volume":"20","author":"Hoegl","year":"2021","journal-title":"Asian Bus. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1111\/j.0361-3666.2006.00331.x","article-title":"The Concept of Resilience Revisited","volume":"30","author":"Manyena","year":"2006","journal-title":"Disasters"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.gloenvcha.2008.07.013","article-title":"A Place-Based Model for Understanding Community Resilience to Natural Disasters","volume":"18","author":"Cutter","year":"2008","journal-title":"Glob. Environ. Chang."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1007\/s10464-007-9156-6","article-title":"Community Resilience as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness","volume":"41","author":"Norris","year":"2008","journal-title":"Am. J. Community Psychol."},{"key":"ref_27","unstructured":"Reghezza-Zitt, M., Rufat, S., Djament-Tran, G., Le Blanc, A., and Lhomme, S. (2024, March 21). What Resilience Is Not: Uses and Abuses Cybergeo: European Journal of Geography [Online], Environment, Nature, Landscape, Document 621, Online since 18 October 2012, Connection on 12 May 2024. Available online: http:\/\/journals.openedition.org\/cybergeo\/25554."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1111\/gec3.12154","article-title":"Resilience for Whom? Emerging Critical Geographies of Socio-Ecological Resilience","volume":"8","author":"Cretney","year":"2014","journal-title":"Geogr. Compass"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1111\/geoj.12012","article-title":"Resilience and Responsibility: Governing Uncertainty in a Complex World","volume":"180","author":"Welsh","year":"2014","journal-title":"Geogr. J."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1177\/0002764215591187","article-title":"Resilience and the Neoliberal Project: Discourses, Critiques, Practices\u2014And Katrina","volume":"59","author":"Tierney","year":"2015","journal-title":"Am. Behav. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1177\/0309132513518834","article-title":"Geographies of Resilience: Challenges and Opportunities of a Descriptive Concept","volume":"39","author":"Weichselgartner","year":"2015","journal-title":"Prog. Hum. Geogr."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"25338","DOI":"10.3402\/ejpt.v5.25338","article-title":"Resilience Definitions, Theory, and Challenges: Interdisciplinary Perspectives","volume":"5","author":"Southwick","year":"2014","journal-title":"Eur. J. Psychotraumatol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/j.foreco.2009.09.023","article-title":"Climate Change Impacts, Adaptive Capacity, and Vulnerability of European Forest Ecosystems","volume":"259","author":"Lindner","year":"2010","journal-title":"For. Ecol. Manag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1007\/s00267-012-9933-3","article-title":"Modelling the Ecological Vulnerability to Forest Fires in Mediterranean Ecosystems Using Geographic Information Technologies","volume":"50","author":"Duguy","year":"2012","journal-title":"Environ. Manag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1007\/s00267-016-0719-x","article-title":"Evaluating the Characteristics of Social Vulnerability to Wildfire: Demographics, Perceptions, and Parcel Characteristics","volume":"58","author":"Paveglio","year":"2016","journal-title":"Environ. Manag."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Ghorbanzadeh, O., Blaschke, T., Gholamnia, K., and Aryal, J. (2019). Forest Fire Susceptibility and Risk Mapping Using Social\/Infrastructural Vulnerability and Environmental Variables. Fire, 2.","DOI":"10.3390\/fire2030050"},{"key":"ref_37","first-page":"312","article-title":"The Vegetation Resilience After Fire (VRAF) Index: Development, Implementation and an Illustration from Central Italy","volume":"10","author":"Bisson","year":"2008","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_38","first-page":"103","article-title":"Assessing fire severity in semi-arid environments: Application in Donceles 2012 wildfire (SE Spain)","volume":"49","author":"Moya","year":"2017","journal-title":"Rev. Teledetecci\u00f3n"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-Scale Geospatial Analysis for Everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_40","first-page":"e59929","article-title":"Google Earth Engine (GEE): Una poderosa herramienta que vincula el potencial de los datos masivos y la eficacia del procesamiento en la nube","volume":"101","author":"Perilla","year":"2020","journal-title":"Investig. Geogr\u00e1ficas"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-Resolution Global Maps of 21st-Century Forest Cover Change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.scitotenv.2018.11.049","article-title":"The Background Context Matters: Local-Scale Socioeconomic Conditions and the Spatial Distribution of Wildfires in Italy","volume":"654","author":"Ferrara","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"104797","DOI":"10.1016\/j.landurbplan.2023.104797","article-title":"Social Drivers of Vulnerability to Wildfire Disasters: A Review of the Literature","volume":"237","author":"Lambrou","year":"2023","journal-title":"Landsc. Urban Plan."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1093\/biosci\/biz030","article-title":"Integrating Subjective and Objective Dimensions of Resilience in Fire-Prone Landscapes","volume":"69","author":"Higuera","year":"2019","journal-title":"BioScience"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Marey-Perez, M., Loureiro, X., Corbelle-Rico, E.J., and Fern\u00e1ndez-Filgueira, C. (2021). Different Strategies for Resilience to Wildfires: The Experience of Collective Land Ownership in Galicia (Northwest Spain). Sustainability, 13.","DOI":"10.3390\/su13094761"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1071\/WF12203","article-title":"Forest Fuel Management for Wildfire Prevention in Spain: A Quantitative SWOT Analysis","volume":"23","author":"Marino","year":"2014","journal-title":"Int. J. Wildland Fire"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1071\/WFv28n7_FO","article-title":"Fire Regime and Ecosystem Responses: Adaptive Forest Management in a Changing World (Part 2)","volume":"28","author":"Moya","year":"2019","journal-title":"Int. J. Wildland Fire"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1127\/0941-2948\/2006\/0130","article-title":"World Map of the K\u00f6ppen-Geiger Climate Classification Updated","volume":"15","author":"Kottek","year":"2006","journal-title":"Meteorol. Z."},{"key":"ref_49","unstructured":"(2022, November 30). SIGA. Available online: https:\/\/sig.mapama.gob.es\/siga\/."},{"key":"ref_50","unstructured":"Soil Survey Staff (2022). Keys to Soil Taxonomy."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/LGRS.2005.857030","article-title":"A Landsat Surface Reflectance Dataset for North America, 1990\u20132000","volume":"3","author":"Masek","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary Analysis of the Performance of the Landsat 8\/OLI Land Surface Reflectance Product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.isprsjprs.2017.06.013","article-title":"Change Detection Using Landsat Time Series: A Review of Frequencies, Preprocessing, Algorithms, and Applications","volume":"130","author":"Zhu","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_54","unstructured":"PNOA (2022, October 13). Geoportal Web Del Plan Nacional de Ortofotograf\u00eda A\u00e9rea. Available online: https:\/\/pnoa.ign.es\/."},{"key":"ref_55","unstructured":"MFE (2023, March 17). Foto Fija del Mapa Forestal de Espa\u00f1a. Available online: https:\/\/www.miteco.gob.es\/es\/biodiversidad\/temas\/inventarios-nacionales\/mapa-forestal-espana\/foto_fija_mfe.aspx."},{"key":"ref_56","unstructured":"USGS (2023, March 17). Landsat Surface Reflectance-Derived Spectral Indices|U.S. Geological Survey, Available online: https:\/\/www.usgs.gov\/landsat-missions\/landsat-surface-reflectance-derived-spectral-indices."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s42408-018-0021-9","article-title":"Examining Post-Fire Vegetation Recovery with Landsat Time Series Analysis in Three Western North American Forest Types","volume":"15","author":"Bright","year":"2019","journal-title":"Fire Ecol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"127911","DOI":"10.1016\/j.physa.2022.127911","article-title":"Informational Analysis of MODIS NDVI and EVI Time Series of Sites Affected and Unaffected by Wildfires","volume":"604","author":"Ba","year":"2022","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Lasaponara, R., Abate, N., Fattore, C., Aromando, A., Cardettini, G., and Di Fonzo, M. (2022). On the Use of Sentinel-2 NDVI Time Series and Google Earth Engine to Detect Land-Use\/Land-Cover Changes in Fire-Affected Areas. Remote Sens., 14.","DOI":"10.3390\/rs14194723"},{"key":"ref_60","unstructured":"Rouse, W., Haas, R.H., Schell, J.A., and Deering, D.W. (1974). Monitoring Vegetation Systems in the Great Plains with ERTS."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.rse.2004.10.012","article-title":"Comparison of Time Series Tasseled Cap Wetness and the Normalized Difference Moisture Index in Detecting Forest Disturbances","volume":"94","author":"Jin","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_62","unstructured":"(2021, February 25). Normalized Burn Ratio (NBR)|UN-SPIDER Knowledge Portal. Available online: https:\/\/un-spider.org\/advisory-support\/recommended-practices\/recommended-practice-burn-severity\/in-detail\/normalized-burn-ratio."},{"key":"ref_63","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, General Technical Report RMRS-GTR-164-CD.","DOI":"10.2737\/RMRS-GTR-164"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/S0034-4257(01)00318-2","article-title":"Detection of Forest Harvest Type Using Multiple Dates of Landsat TM Imagery","volume":"80","author":"Wilson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_65","unstructured":"(2022, June 16). Normalized Difference Moisture Index|U.S. Geological Survey, Available online: https:\/\/www.usgs.gov\/landsat-missions\/normalized-difference-moisture-index."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1071\/WF07049","article-title":"Fire Intensity, Fire Severity and Burn Severity: A Brief Review and Suggested Usage","volume":"18","author":"Keeley","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_67","unstructured":"(2023, March 17). GEE Objects and Methods Overview|Google Earth Engine|Google Developers. Available online: https:\/\/developers.google.com\/earth-engine\/guides\/objects_methods_overview."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.rse.2017.11.007","article-title":"Analyzing Spatial and Temporal Variability in Short-Term Rates of Post-Fire Vegetation Return from Landsat Time Series","volume":"205","author":"Frazier","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_69","unstructured":"Rothermel, R.C. (1972). A Mathematical Model for Predicting Fire Spread in Wildland Fuels, Research Paper. INT-115."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Chuvieco, E., Yebra, M., Martino, S., Thonicke, K., G\u00f3mez-Gim\u00e9nez, M., San-Miguel, J., Oom, D., Velea, R., Mouillot, F., and Molina, J.R. (2023). Towards an Integrated Approach to Wildfire Risk Assessment: When, Where, What and How May the Landscapes Burn. Fire, 6.","DOI":"10.3390\/fire6050215"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Zhai, J., Ning, Z., Dahal, R., and Yang, S. (2023). Wildfire Susceptibility of Land Use and Topographic Features in the Western United States: Implications for the Landscape Management. Forests, 14.","DOI":"10.3390\/f14040807"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"153672","DOI":"10.1016\/j.scitotenv.2022.153672","article-title":"The Resilience of Soil Erosion Rates under Historical Land Use Change in Agroecosystems of Southern Spain","volume":"822","author":"Milazzo","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1111\/geb.12095","article-title":"Integration of Ecological and Socio-Economic Factors to Assess Global Vulnerability to Wildfire","volume":"23","author":"Chuvieco","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.ecolmodel.2014.09.017","article-title":"Mapping Ecological Vulnerability to Fire for Effective Conservation Management of Natural Protected Areas","volume":"295","author":"Aretano","year":"2015","journal-title":"Ecol. Model."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1007\/s12665-021-09731-2","article-title":"Influence of Topography on Sediment Dynamics and Soil Chemical Properties in a Mediterranean Forest Historically Affected by Wildfires: NE Iberian Peninsula","volume":"80","author":"Francos","year":"2021","journal-title":"Environ. Earth Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"150106","DOI":"10.1016\/j.scitotenv.2021.150106","article-title":"Soil Degradation in the European Mediterranean Region: Processes, Status and Consequences","volume":"805","author":"Ferreira","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Hewelke, E., Oktaba, L., Gozdowski, D., Kondras, M., Olejniczak, I., and G\u00f3rska, E.B. (2018). Intensity and Persistence of Soil Water Repellency in Pine Forest Soil in a Temperate Continental Climate under Drought Conditions. Water, 10.","DOI":"10.3390\/w10091121"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.iswcr.2022.08.002","article-title":"Exploring the Factors Influencing the Hydrological Response of Soil after Low and High-Severity Fires with Post-Fire Mulching in Mediterranean Forests","volume":"11","author":"Xu","year":"2023","journal-title":"Int. Soil Water Conserv. Res."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1252","DOI":"10.1016\/j.scitotenv.2015.09.121","article-title":"Temporal Changes in Soil Water Repellency after a Forest Fire in a Mediterranean Calcareous Soil: Influence of Ash and Different Vegetation Type","volume":"572","author":"Lozano","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"109731","DOI":"10.1016\/j.agrformet.2023.109731","article-title":"Elucidating Factors Driving Post-Fire Vegetation Recovery in the Mediterranean Forests Using Landsat Spectral Metrics","volume":"342","author":"Spatola","year":"2023","journal-title":"Agric. For. Meteorol."},{"key":"ref_81","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_82","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s42408-022-00156-1","article-title":"Resilience of Mediterranean Communities to Fire Depends on Burn Severity and Type of Ecosystem","volume":"18","author":"Huerta","year":"2022","journal-title":"Fire Ecol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1002\/ecm.1285","article-title":"Fire-Induced Deforestation in Drought-Prone Mediterranean Forests: Drivers and Unknowns from Leaves to Communities","volume":"88","author":"Karavani","year":"2018","journal-title":"Ecol. Monogr."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.ecolind.2015.06.043","article-title":"An Assessment of Soil Erosion Prevention by Vegetation in Mediterranean Europe: Current Trends of Ecosystem Service Provision","volume":"60","author":"Guerra","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"149218","DOI":"10.1016\/j.scitotenv.2021.149218","article-title":"The Role of Plant Species on Runoff and Soil Erosion in a Mediterranean Shrubland","volume":"799","author":"Novara","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Chatfield, C., and Xing, H. (2019). The Analysis of Time Series: An Introduction with R, CRC Press.","DOI":"10.1201\/9781351259446"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2307\/1907187","article-title":"Nonparametric Tests Against Trend","volume":"13","author":"Mann","year":"1945","journal-title":"Econometrica"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1093\/biomet\/71.3.599","article-title":"Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order","volume":"71","author":"Said","year":"1984","journal-title":"Biometrika"},{"key":"ref_89","unstructured":"(2024, January 31). Posit Team R Studio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. Available online: http:\/\/www.posit.co\/."},{"key":"ref_90","unstructured":"Wickham, H., Fran\u00e7ois, R., Henry, L., M\u00fcller, K., and Vaughan, D. (2024, January 31). Posit. PBC Dplyr: A Grammar of Data Manipulation 2023. R Package Version 1.1.4. Available online: https:\/\/github.com\/tidyverse\/dplyr; https:\/\/dplyr.tidyverse.org."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Wickham, H. (2016). Ggplot2: Elegant Graphics for Data Analysis, Springer.","DOI":"10.1007\/978-3-319-24277-4_9"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1002\/rse2.186","article-title":"Regional-Scale Forest Restoration Effects on Ecosystem Resiliency to Drought: A Synthesis of Vegetation and Moisture Trends on Google Earth Engine","volume":"7","author":"Sankey","year":"2021","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.apgeog.2014.02.006","article-title":"Quantifying Spatial and Temporal Vegetation Recovery Dynamics Following a Wildfire Event in a Mediterranean Landscape Using EO Data and GIS","volume":"50","author":"Petropoulos","year":"2014","journal-title":"Appl. Geogr."},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Hao, B., Xu, X., Wu, F., and Tan, L. (2022). Long-Term Effects of Fire Severity and Climatic Factors on Post-Forest-Fire Vegetation Recovery. Forests, 13.","DOI":"10.3390\/f13060883"},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Yu, L., Li, X., Peng, D., Zhang, Y., and Gong, P. (2021). Progress and Trends in the Application of Google Earth and Google Earth Engine. Remote Sens., 13.","DOI":"10.3390\/rs13183778"},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/j.ijforecast.2021.11.001","article-title":"Forecasting: Theory and Practice","volume":"38","author":"Petropoulos","year":"2022","journal-title":"Int. J. Forecast."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"102304","DOI":"10.1016\/j.ecoinf.2023.102304","article-title":"Remote Sensing Delineation of Wildfire Spatial Extents and Post-Fire Recovery along a Semi-Arid Climate Gradient","volume":"78","author":"Liu","year":"2023","journal-title":"Ecol. Inform."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Robinson, N.P., Allred, B.W., Jones, M.O., Moreno, A., Kimball, J.S., Naugle, D.E., Erickson, T.A., and Richardson, A.D. (2017). A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States. Remote Sens., 9.","DOI":"10.3390\/rs9080863"},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Hird, J.N., Kariyeva, J., and McDermid, G.J. (2021). Satellite Time Series and Google Earth Engine Democratize the Process of Forest-Recovery Monitoring over Large Areas. Remote Sens., 13.","DOI":"10.3390\/rs13234745"},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Meng, Y., Wei, C., Guo, Y., and Tang, Z. (2022). A Planted Forest Mapping Method Based on Long-Term Change Trend Features Derived from Dense Landsat Time Series in an Ecological Restoration Region. Remote Sens., 14.","DOI":"10.3390\/rs14040961"},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Viana-Soto, A., Aguado, I., Salas, J., and Garc\u00eda, M. (2020). Identifying Post-Fire Recovery Trajectories and Driving Factors Using Landsat Time Series in Fire-Prone Mediterranean Pine Forests. Remote Sens., 12.","DOI":"10.3390\/rs12091499"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"2911","DOI":"10.1016\/j.rse.2010.07.010","article-title":"Detecting Trends in Forest Disturbance and Recovery Using Yearly Landsat Time Series: 2. TimeSync\u2014Tools for Calibration and Validation","volume":"114","author":"Cohen","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.ecolind.2018.02.008","article-title":"Indicator-Based Assessment of Post-Fire Recovery Dynamics Using Satellite NDVI Time-Series","volume":"89","author":"Bruno","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_104","unstructured":"Pironkova, Z., Whaley, R., and Lan, K. (2018). Time Series Analysis of Landsat NDVI Composites with Google Earth Engine and R: User Guide\u2014Science and Research Technical Manual TM-06, Ontario Ministry of Natural Resources and Forestry, Science and Research Branch."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"2113","DOI":"10.3390\/rs5052113","article-title":"Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology","volume":"5","author":"Forkel","year":"2013","journal-title":"Remote Sens."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1177\/0309133314542956","article-title":"de la A Method for Regional-Scale Assessment of Vegetation Recovery Time after High-Severity Wildfires: Case Study of Spain","volume":"38","author":"Rodrigues","year":"2014","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"2981","DOI":"10.5194\/nhess-22-2981-2022","article-title":"Global Assessment and Mapping of Ecological Vulnerability to Wildfires","volume":"22","author":"Aguado","year":"2022","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Tavakkoli Piralilou, S., Einali, G., Ghorbanzadeh, O., Nachappa, T.G., Gholamnia, K., Blaschke, T., and Ghamisi, P. (2022). A Google Earth Engine Approach for Wildfire Susceptibility Prediction Fusion with Remote Sensing Data of Different Spatial Resolutions. Remote Sens., 14.","DOI":"10.3390\/rs14030672"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s10457-011-9423-2","article-title":"Landscape Vulnerability to Wildfires at the Forest-Agriculture Interface: Half-Century Patterns in Spain Assessed through the SISPARES Monitoring Framework","volume":"85","author":"Ortega","year":"2012","journal-title":"Agrofor. Syst."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1718\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:41:19Z","timestamp":1760107279000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/10\/1718"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":109,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["rs16101718"],"URL":"https:\/\/doi.org\/10.3390\/rs16101718","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,13]]}}}