TEAM 10: Location Intelligence from Multi-Variate Spatial Analysis

TEAM LEADERS: Runar Bergheim, Karel Charvat

TEAM MEMBERS: Petr Uhlir, Raitis Berzins, Dmitrij Kozuk, Milan Kalas


A lot of energy has gone into the development of precision data both with regards to fundamental geospatial data such as basemaps and thematic data serving a single purposes for specific and narrow target audiences.  This idea seeks to use such data to elaborate detailed characteristics about places based on the co-occurrence of certain features or phenomena.


An example of how such characteristics could be used, let us consider the following. The accessibility of a place may be described in terms of its proximity to transport hubs for air, train and road transport. That gives a snapshot of the current state of the area; however — by incorporating planned and future developments, it is possible to characterize a place by how it is likely to be two years from now. The climate of a place can be described in terms of monthly averages, averaged over 50 years of aggregated data for precipitation, air temperature, sea temperature, cloud cover, snow cover etc. The terrain can be characterized in terms of its ruggedness, whether it is a platou, a plane, coastal, mountaineous or otherwise. There is a near infinite number of characteristics that can be considered — in themselves they are not necessarily particularly useful — but combined the right way they may predict trends and offer location insights that are useful both to individuals, private enterprises and regional development bodies.


I.e. by identifying all places in the mountains that has rugged terrain and that has a long and steady period of snow cover with cold frequent sunny days — and with a new infrastructure hubs being developed within 75 minutes drive away — but scores low on availability of visitor oriented services we have established a dormant economic potential. This sort of location intelligence is thus far the material of reports.


This team will be operating in a mixed technical and non-technical manner. On the one hand we will expand upon the business cases in an exploratory manner through conversation; on the other we will try to identify practical sources and algorithms to determine key characteristics for places, taking as a starting point a seed database of about 20 000 locations and a bunch of climate, land-cover and landscape characteristics that have already been calculated.