How are geospatial “big data”

How are geospatial “big data”

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Geospatial data (DG) – this information is somehow tied to a specific location of objects. Typically, such information is stored in the form of geographical coordinates and topologies. The number of data is growing at an astonishing pace, as they mostly are not people, and a wide range of devices. Generate their smartphones, tablets, satellites, digital cameras, as well as radar, sensor networks and different types of transport. As the trend of “Internet of Things” and the Internet are gaining industrial growth, the amount of geospatial data will grow even more intense than it is now.

Such information is used in GIS – geographical information systems for input, storage, retrieval, analysis and display geographically referenced data. The most important elements are the attributes of a GIS that is, additional information related to the DG. There is also the concept of “data layers” – a combination of attributes and coordinates. For example, the layer can act as a map onto which the objects. Analysis of geospatial data is also called spatial analytics. It is used to answer questions about the real world – for example, on the current situation at a given point, vector changes due to various factors, with modeling and forecasts.

What gives geospatial analysis organizations? For example, because it can visualize the social network activity during global events – say, the ecological crisis. Comparison of tweets, posts or blogerskoy activity with geographic location can help rescuers. Obviously, just like data sources to monitor forces operators unrealistic: during any large-scale incident by repost, posts, and simply false news rolls. Therefore, for rescue operations required sophisticated analytical tools – about the same as that used by marketers in an attempt to empty the pockets of customers. By the way, this kind of analysis helps in the fight against fraud: many are willing to take this opportunity to announce that were in the disaster area, whereas this is not true …

Another example. Telecoms can use geospatial data in order to regulate outflow of users. The same social networks provide information on what the client has moved to another area. In this case, the system is monitoring the availability of the services of the operator in the field and manages to offer a new mobile phone or even a miniature mobile station before the disgruntled customer decides to change service provider. Greatly from DG extracts energy. Performing spatial analysis, companies expect what may be the peak power consumption, based on the geographical location and equipment of an area. And the most developed area of ‚Äč‚Äčapplication of geospatial data – this, of course, advertising and marketing. The ability to offer certain services to the consumer at a time when he is in close proximity to the store – a tidbit for marketers. Such advertising is already actively using many shopping malls. Unless, of course, be able to afford such exotic, still too resource-intensive task for an ordinary boutique. Why worry about the fact that your phone will ringing you about every shop within walking distance, yet.

Thus, the demand for processing “large geospatial data” is quite large. Service offerings in this area, too, is not standing still. One of the most interesting startups involved in today flows DG, yavleetsya SpaceCurve. The company developed a radically new ways of parallel information processing. This makes it possible to index complex geospatial polygons in real time, and analyze the social and semantic graphs on large parallel systems, allowing organizations to make more informed decisions. Theoretically SpaceCurve technology available to anyone who can collect any data on the position of mobile devices: customers have the ability to create its software, integrating it with the capabilities SpaceCurve.

Another startup, Loqate, developed software for parsing, standardization, inspection and cleaning of address data from around the world. Each address assigned to your latitude and longitude, which enables it to be used in GIS. This capability is provided by a 2012 as a cloud service, and developers can also integrate this data into their own applications.

Thus, analytical tools, and partly based on statistical techniques for analysis of GIS data – the topology of the terrain and the coordinates of objects – up to complex algorithms that provide a range of different applications. Today Geographic Information Systems in conjunction with numerous data from user devices are a powerful tool for marketers, business analysts, technology companies and many other organizations.

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