148198 20260217205525.0 doi 10.3390/rs16244738 sideral 141684 ART-2024-141684 eng Larraz-Juan, Sergio Universidad de Zaragoza (orcid)0009-0002-8815-660X A Methodological Approach for Assessing the Post-Fire Resilience of Pinus halepensis Mill. Plant Communities Using UAV-LiDAR Data Across a Chronosequence 2024 Access copy available to the general public Unrestricted The assessment of fire effects in Aleppo pine forests is crucial for guiding the recovery of burnt areas. This study presents a methodology using UAV-LiDAR data to quantify malleability and elasticity in four burnt areas (1970, 1995, 2008 and 2015) through the statistical analysis of different metrics related to height structure and diversity (Height mean, 99th percentile and Coefficient of Variation), coverage, relative shape and distribution strata (Canopy Cover, Canopy Relief Ratio and Strata Percent Coverage), and canopy complexity (Profile Area and Profile Area Change). In general terms, malleability decreases over time in forest ecosystems that have been affected by wildfires, whereas elasticity is higher than what has been determined in previous studies. However, a particular specificity has been detected from the 1995 fire, so we can assume that there are other situational factors that may be affecting ecosystem resilience. LiDAR metrics and uni-temporal sampling between burnt sectors and control aids are used to understand community resilience and to identify the different recovery stages in P. halepensis forests. info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2020-118886RB-I00-AEI-10.13039-501100011033 info:eu-repo/grantAgreement/ES/MCIU/FPU18-05027 info:eu-repo/grantAgreement/ES/MCIU/FPU22-04489 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 4.1 2024 GEOSCIENCES, MULTIDISCIPLINARY 47 / 258 = 0.182 2024 Q1 T1 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY 14 / 36 = 0.389 2024 Q2 T2 REMOTE SENSING 20 / 65 = 0.308 2024 Q2 T1 ENVIRONMENTAL SCIENCES 128 / 376 = 0.34 2024 Q2 T2 1.019 2024 Earth and Planetary Sciences (miscellaneous) 2024 Q1 8.6 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Pérez-Cabello, Fernando Universidad de Zaragoza (orcid)0000-0003-4831-4060 Hoffrén Mansoa, Raúl Universidad de Zaragoza (orcid)0000-0002-9123-304X Iranzo Cubel, Cristian Universidad de Zaragoza (orcid)0000-0002-3359-6213 Montorio, Raquel Universidad de Zaragoza (orcid)0000-0001-7403-1764 3006 435 Universidad de Zaragoza Dpto. Geograf. Ordenac.Territ. Área Geografía Humana 3006 010 Universidad de Zaragoza Dpto. Geograf. Ordenac.Territ. Área Análisis Geográfico Regi. 16, 24 (2024), 4738 [26 pp.] Remote sens. (Basel) Remote Sensing 2072-4292 10101269 http://zaguan.unizar.es/record/148198/files/texto_completo.pdf Versión publicada 2760697 http://zaguan.unizar.es/record/148198/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:148198 articulos driver 2026-02-17-20:30:08 ARTICLE