Earth-Science Reviews · 2023 · 64 citations · 73 references
ComputingGeographyGeoinformaticsData VisualizationGeographic Information ScienceGeomaticsDigital MappingGeospatial Data VisualizationGeospatial Machine LearningGeovisual AnalyticsSpatial Data AnalyticsVisual Analytics For Spatial DataAi CapabilitiesGeographic Data VisualizationGeospatial Big DataGeospatial ModelingGeospatial TechnologiesReal-time Geographic VisualizationSpatial ComputingTemporal Dimensions
In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which have gradually, yet fundamentally influenced the way people interact with and in the digital and physical world. Many human activities now not only operate in geographical (physical) space but also in cyberspace. Such changes have triggered a paradigm shift in geographic information science (GIScience), as cyberspace brings new perspectives for the roles played by spatial and temporal dimensions, e.g., the dilemma of placelessness and possible timelessness. As a discipline at the brink of even bigger changes made possible by machine learning and artificial intelligence, this paper highlights the challenges and opportunities associated with geographical space in relation to cyberspace, with a particular focus on data analytics and visualization, including extended AI capabilities and virtual reality representations. Consequently, we encourage the creation of synergies between the processing and analysis of geographical and cyber data to improve sustainability and solve complex problems with geospatial applications and other digital advancements in urban and environmental sciences.
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Machine Learning With Big Data: Challenges and Approaches
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