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• W4313372221 abstract "Today, with the innovations and advancements of technologies and affordability of digital devices there is an explosion of huge amounts of archived and real-time digital data. This also includes the subset of the “Big Earth Data” which is generated using multitudinous sources viz., satellites, sensor networks, Internet of Things systems, and the hyper-connectivity of our society. It is diversified containing rich information across different geographic scales and resolutions. However, a massive challenge also exists on how this data has been exploited and explored to understand and solve problems in urban areas and cities. Furthermore, data analytics is also used for the exploration and analysis of the data sources, what the data represents, and transforming the data into information for intelligence creation. The recent evolutionary shift from Geographic Information Systems (GIS) to data analytics, including Urban Data Analytics enables us to gain insight into urban processes and answers to new and complex questions related to cities and urban areas. Based on above discussions, aims of this chapter are to provide insights on the recent trends and approaches in Geospatial Big Earth Data sources, uses, and their integration with IoT-based Big Data systems for urban studies. It also provides a review on use of machine learning and AI as state-of-the-art technologies to analyze the big urban earth data for accurate information for better decisions. Furthermore, an attempt is also made to discuss the way forward and future research areas and applications." @default.
• W4313372221 created "2023-01-06" @default.
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• W4313372221 date "2022-01-01" @default.
• W4313372221 modified "2023-09-26" @default.
• W4313372221 title "Geospatial Big Earth Data and Urban Data Analytics" @default.
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• W4313372221 doi "https://doi.org/10.1007/978-3-031-14096-9_4" @default.
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