Mark van Rijmenam of Big Data Startups recently wrote, "Geospatial data is data that identifies a geographic location on Earth, such as natural or constructed features, oceans, and more. The data is generally stored as coordinates and topology and can be mapped. Geospatial data is all around us and it is growing at a staggering pace of 20% per year. McKinsey Global Institute estimated that location data level stood at 1 petabyte in 2009, excluding data from RFID tags. Geospatial data is created by a vast array of different applications such as satellites, digital cameras, wearables, smartphones, radars, sensor networks, cars, trucks, trains and other transportation. With trends such as the quantified-self, the Internet of Things and the Industrial Internet the amount of geospatial data will grow exponentially in the coming years and you can harness this data to better serve your customers."
He continues, "Geospatial data are used in a Geographic Information System (GIS), which can be defined as an information system that is used to input, store, retrieve, manipulate, analyse and output the geographically referenced data. There are several important elements to a GIS and these include Attribute data, which means the information that is linked to the spatial data. Data Layers, which is the result of combining spatial data and attribute data and it means for example the attribute data shown on a map. Layer types refer to how attribute data and spatial data are connected. There are two possibilities: vector, meaning a graphical representation with points, lines or polygons. The second is raster, meaning representing data using a grid where each cell in a grid has a certain resolution (from sub-meter to kilometres). Finally, Topology, which is a key element and is a set of rules and behaviours that model how points, lines, and polygons share coincident geometry. Topology is used to ensure data quality as well as for analysing spatial relationships."
Image: Courtesy Flickr/ NASA Goddard Space Flight Center