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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/52336

    Título
    Evaluation of Prescribed Fires from Unmanned Aerial Vehicles (UAVs) Imagery and Machine Learning Algorithms
    Autor
    Pérez Rodríguez, Luis A.
    Quintano Pastor, María del CarmenAutoridad UVA Orcid
    Marcos Porras, Elena María
    Suarez Seoane, Susana
    Calvo, Leonor
    Fernández Manso, Alfonso
    Año del Documento
    2020
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Remote Sensing, 2020, vol. 12, n. 8, 1295
    Resumo
    Prescribed fires have been applied in many countries as a useful management tool to prevent large forest fires. Knowledge on burn severity is of great interest for predicting post-fire evolution in such burned areas and, therefore, for evaluating the efficacy of this type of action. In this research work, the severity of two prescribed fires that occurred in “La Sierra de Uría” (Asturias, Spain) in October 2017, was evaluated. An Unmanned Aerial Vehicle (UAV) with a Parrot SEQUOIA multispectral camera on board was used to obtain post-fire surface reflectance images on the green (550 nm), red (660 nm), red edge (735 nm), and near-infrared (790 nm) bands at high spatial resolution (GSD 20 cm). Additionally, 153 field plots were established to estimate soil and vegetation burn severity. Severity patterns were explored using Probabilistic Neural Networks algorithms (PNN) based on field data and UAV image-derived products. PNN classified 84.3% of vegetation and 77.8% of soil burn severity levels (overall accuracy) correctly. Future research needs to be carried out to validate the efficacy of this type of action in other ecosystems under different climatic conditions and fire regimes.
    Palabras Clave
    Unmanned aerial vehicles
    Vehículos aéreos no tripulados
    ISSN
    2072-4292
    Revisión por pares
    SI
    DOI
    10.3390/rs12081295
    Patrocinador
    Ministerio de Economía, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (project AGL2017-86075-C2-1-R)
    Junta de Castilla y León (project LE001P17)
    Version del Editor
    https://www.mdpi.com/2072-4292/12/8/1295
    Propietario de los Derechos
    © 2020 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/52336
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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    Universidad de Valladolid

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