Big Data Architectures for the Climate Change Analysis: A Systematic Mapping Study


  • ANIA Lorena CRAVERO Universidad de La Frontera


Big Data, Climate Change, Architectures, systematic mapping


With the development of climate observation computer systems, in particular satellite meteorological observation and high resolution climate models, they have allowed rapid growth in the volume of climatic data. Analyzing the impacts caused by climate change varies according to the point of view, such as sea level rise, atmospheric and oceanic compositions, the appearance of new diseases, among others. However, despite the volume of data generated, scientists can not predict with absolute precision how climate change will manifest at the local level and what measures should be applied to mitigate it effectively. Big Data is a new technology that offers the challenge to collect, characterize and analyze a large amount of data, taking into account data from multiple sources, multiple variables and multiple scales with different spatial and temporal attributes. This article presents a Systematic Mapping on Big Data Architectures that help solve problems caused by climate change, such as health, agriculture, biodiversity, energy and water resources.


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