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CS

Geospatial Statistics

Project title
Selected SDG indicators processed using modern approaches with subsequent provision of output descriptive and geospatial data in the Czech and European scope (GEOS)

Project code
101260155 – 2025-CZ-GEOS

Call
SMP-ESS-2025-GEOS-IBA— Geospatial Statistics

Beneficiary
The Czech Statistical Office

Place of implementation
The Czech Republic

Project date
01/2026 – 12/2027

Total eligible costs
127,510.08 EUR

Maximum grant amount
113,889.89 EUR

Project summary
The aim of the project is to create and implement a process for processing selected geospatial indicators of the 2030 Agenda and ensure its automation. The main benefits include the analysis of suitable national and transnational data sources, finding and selecting appropriate models and processing methods in GIS and their automation using the Python programming language. The results, including methodological procedures, scripts, output datasets and cartographic outputs will be publicly shared with other member countries.

Disclaimer:
Funded by the European Union. Views and opinions expressed are however those of the author only and do not necessarily reflect those of the European Union or Eurostat. Neither the European Union nor the granting authority can be held responsible for them.

Results of the First Phase of the Project:
In the first half of this year, the first milestone focused on the modernization of geospatial data processing and the development of a new methodology for defining urbanized space in the Czech Republic was successfully achieved within the GEOS project.

A key achievement was the development of a new methodology for delineating urbanized areas in the Czech Republic, providing a significantly more accurate and realistic representation of settlement patterns. Unlike traditional approaches, which often overestimate the extent of urban areas due to geometric distortions, the new model is based directly on the actual spatial distribution of population and built-up areas. The results show that urbanized space is more concentrated and structured than previously indicated, while also capturing the gradual transition between urban and rural areas. The methodology combines advanced spatial operations, reflects real functional relationships between settlements, and prevents the unintended merging of unrelated municipalities. Key outputs include a more precise delineation of urbanized areas, a clearer distinction between local centres and satellite settlements, improved identification of compact and dispersed development patterns, and the creation of a robust data foundation for further analyses in fields such as transport, accessibility of services, regional development, and landscape research.

All outputs are fully compatible with the international DEGURBA classification and can be used for both statistical purposes and practical planning and analytical modelling. The results have been made available through the CZSO Geoportal, including an interactive map application, a dashboard with visualized statistical indicators, and open geospatial datasets published through the GIS Data Portal and the National Open Data Catalogue.