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    Título
    Transferability of vegetation recovery models based on remote sensing across different fire regimes
    Autor
    Fernández-Guisuraga, José Manuel
    Suárez Seoane, SusanaAutoridad Buleria
    Calvo Galván, María LeonorAutoridad Buleria ORCID
    Facultad/Centro
    Facultad de Ciencias Biologicas y Ambientales
    Área de conocimiento
    Ecologia
    Título de la revista
    Applied Vegetation Science
    Número de la revista
    3
    Editor
    Wiley
    Fecha
    2020-07
    ISSN
    1402-2001
    Descripción física
    P. 441-451
    Abstract
    Aim To evaluate the transferability between fire recurrence scenarios of post‐fire vegetation cover models calibrated with satellite imagery data at different spatial resolutions within two Mediterranean pine forest sites affected by large wildfires in 2012. Location The northwest and east of the Iberian Peninsula. Methods In each study site, we defined three fire recurrence scenarios for a reference period of 35 years. We used image texture derived from the surface reflectance channels of WorldView‐2 and Sentinel‐2 (at a spatial resolution of 2 m × 2 m and 20 m × 20 m, respectively) as predictors of post‐fire vegetation cover in Random Forest regression analysies. Percentage vegetation cover was sampled in two sets of field plots with a size roughly equivalent to the spatial resolution of the imagery. The plots were distributed following a stratified design according to fire recurrence scenarios. Model transferability was assessed within each study site by applying the vegetation cover model developed for a given fire recurrence scenario to predict vegetation cover in other scenarios, iteratively. Results For both wildfires, the highest model transferability between fire recurrence scenarios was achieved for those holding the most similar vegetation community composition regarding the balance of species abundance according to their plant‐regenerative traits (root mean square error [RMSE] around or lower than 15%). Model transferability performance was highly improved by fine‐grained remote‐sensing data. Conclusions Fire recurrence is a major driver of community structure and composition so the framework proposed in this study would allow land managers to reduce efforts in the context of post‐fire decision‐making to assess vegetation recovery within large burned landscapes with fire regime variability.
    Materia
    Ecología. Medio ambiente
    Palabras clave
    Image texture
    Megafire
    Model transferability
    Random forest regression
    Satellite imagery
    Sentinel-2
    Vegetation cover
    WorldView-2
    Idioma
    eng
    Tipo documental
    info:eu-repo/semantics/article
    Peer review
    SI
    URI
    http://hdl.handle.net/10612/12290
    DOI
    https://doi.org/10.1111/avsc.12500
    Versión del editor
    Guisuraga, JM, Suárez‐Seoane, S, Calvo, L. Transferability of vegetation recovery models based on remote sensing across different fire regimes. Appl Veg Sci. 2020; 23: 441– 451. https://doi.org/10.1111/avsc.12500
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