It is all good to have access to large volume of data generated with high velocity which normally spans variety of domains and usually comes with levels of veracity. However, the importance of data becomes visible only when we turn it into a value. In particular, in the domain of “Big Spatial Data”, we deal with massive amounts of real-time spatial and spatio-temporal data obtained from billions of sensors, location-aware devices, remoting sensing satellites, and various models of the physical world. The use of Big Spatial Data spans a variety of applications including social networks, earth sciences, transportation, communication networks, online maps, smart cities and urban planning, remote sensing, and crisis and evacuation management, to name but a few. Turning Big Spatial Data into value is challenging and requires introduction of fundamentally new spatio-temporal algorithms, methods, and systems that can process, mine, and analyze massive amounts of fast and heterogeneous spatio-temporal data in a timely manner.