GeoPython2019

»Data Location Enrichment. Get valuable results from spatial data analysis«
2019-06-26, 09:30–10:00, Room 1

Spatial analysis algorithms could be sensitive to the distribution area value or require the polygon of feature surrounding for correct calculations. The Enrichment is aimed to receive the original object geometry replacing the outdated and unsatisfying default bounding box approach.

While performing spatial data analysis it is a crucial task to define the area of features distributed. It may be used to clip the interpolation results or be as an input in calculations e.g. in Nearest Neighbour Analysis. Taking into account the diversity of possible input datasets, we have to cover all possible cases - return geometry of a city, country or even forest surrounding features. Therefore, we decided to use OpenStreetMap to reach global coverage and variety.

There is an API for interacting with data provided by OpenStreetMap, called Overpass. By request, you can get a geometry data with different labels. Overpass gives access to data in XML or JSON formats.

We have built a Python solution to obtain appropriate data from OpenStreetMap and process it to PostgreSQL with PostGIS.