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Geographic Information System and Big Spatial Data: A Review and Challenges
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Author(s): Raja Sher Afgun Usmani (Taylor's University, Malaysia), Ibrahim Abaker Targio Hashem (Taylor's University, Malaysia), Thulasyammal Ramiah Pillai (Taylor's University, Malaysia), Anum Saeed (Center for Advanced Studies in Engineering, Pakistan)and Akibu Mahmoud Abdullahi (Taylor's University, Malaysia)
Copyright: 2020
Volume: 16
Issue: 4
Pages: 45
Source title:
International Journal of Enterprise Information Systems (IJEIS)
Editor(s)-in-Chief: Gianluigi Viscusi (Linköping University, Sweden)
DOI: 10.4018/IJEIS.2020100106
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Abstract
Geographic information system (GIS) is designed to generate maps, manage spatial datasets, perform sophisticated “what if” spatial analyses, visualize multiple spatial datasets simultaneously, and solve location-based queries. The impact of big data is in every industry, including the GIS. The location-based big data also known as big spatial data has significant implications as it forces the industry to contemplate how to acquire and leverage spatial information. In this study, a comprehensive taxonomy is created to provide a better understanding of the uses of GIS and big spatial data. The taxonomy is made up of big data technologies, GIS data sources, tools, analytics, and applications. The authors look into the importance of big spatial data and its implications, review the data sources, and GIS analytics, applications, and GIS tools. Furthermore, in order to guide researchers interested in GIS, the challenges that require substantial research efforts are taken into account. Lastly, open issues in GIS that require further observation are summarized.
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