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Revista científica
versión impresa ISSN 0124-2253versión On-line ISSN 2344-8350
Resumen
VASQUEZ-MORALES, Felipe y CRAVERO-LEAL, Ania. Big Data Architecture for Forest Fire Management Support in the Region of Araucanía. Rev. Cient. [online]. 2021, n.42, pp.304-314. Epub 20-Oct-2021. ISSN 0124-2253. https://doi.org/10.14483/23448350.18349.
Wildfires have been a growing problem in the last decades. In recent years, Big Data technology has been used to process large volumes of data from sensors, photos, satellite and images, as well as valuable data from field experience. In Chile, there are no Big Data systems to support forest fire management. This work aims to propose a Big Data architecture for managing the volume of data provided by satellite images and supporting fire management in Chile. This architecture was tested through a prototype implemented with Cloud Computing tools, which processes satellite images and is focused on the analysis of controlled burns in the region of La Araucanía. The results show that the resulting images are valuable for decision-making in the management of burns within the region. Although there is much to improve, the results are encouraging in terms of the value generated by the resulting images and the improvement of this prototype and the architecture itself.
Palabras clave : architecture; big data; cloud computing; forest fire; prototype; satellite images..