Enabling spatial big data via CyberGIS: Challenges and opportunities

Recent years have seen the emergence of many new and valuable spatial datasets such as trajectories of cell-phones and Global Positioning System (GPS) devices, vehicle engine measurements, global climate models simulation data, volunteered geographic information (VGI), geo-social media, and tweets. The value of these datasets is already evident through many societal applications including disaster management and disease outbreak prediction. However, these location-aware datasets are of a volume, variety, and velocity that exceed the capability of current CyberGIS technologies. We refer to these datasets as Spatial Big Data. In this chapter, we define spatial big data in terms of its value proposition and user experience which depends on the computational platform, use-case, and dataset at hand. We compare spatial big data with traditional spatial data and with other types of big data. We then provide an overview of the current efforts, challenges and opportunities available when spatial big data is enabled via next-generation CyberGIS. Our discussion includes current accomplishments and opportunities from both an analytics and an infrastructure perspective.