Detection of Opencast Mining Sites from Multispectral Satellite Images

    Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

    Resumen

    In this work, we consider the problem of detecting unauthorized opencast mining activities from satellite imagery, which is important for the adverse effect they cause in the environment and the regions where they occur. Detection by traditional methods is cumbersome and costly. For this reason, we propose a solution leveraging machine learning techniques using multispectral satellite imagery. We implemented these techniques and evaluated their performance using real-world examples and considering various important performance metrics. The results show that these techniques provide an accurate detection system and do not require costly computational resources.

    Idioma originalInglés
    Título de la publicación alojadaDevelopments and Advances in Defense and Security - Proceedings of MICRADS 2021
    EditoresÁlvaro Rocha, Carlos Hernan Fajardo-Toro, José María Riola Rodríguez
    EditorialSpringer Science and Business Media Deutschland GmbH
    Páginas161-171
    Número de páginas11
    ISBN (versión impresa)9789811648830
    DOI
    EstadoPublicada - 2022
    EventoMultidisciplinary International Conference of Research Applied to Defense and Security, MICRADS 2021 - Cartagena, Colombia
    Duración: 18 ago. 202120 ago. 2021

    Serie de la publicación

    NombreSmart Innovation, Systems and Technologies
    Volumen255
    ISSN (versión impresa)2190-3018
    ISSN (versión digital)2190-3026

    Conferencia

    ConferenciaMultidisciplinary International Conference of Research Applied to Defense and Security, MICRADS 2021
    País/TerritorioColombia
    CiudadCartagena
    Período18/08/2120/08/21

    Nota bibliográfica

    Publisher Copyright:
    © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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