GIS Project – Dissertation 2009 Comparative Study of Regional Urban Growth (RUG) Model Projections for new EU members in Central Europe and the Baltic States. Pawel Langner Institute of Geography School of GeoSciences University of Edinburgh Supervisors: Dr. Sophie Rickebusch and Prof. Mark Rounsevell

Aim of the project Predict future urban growth based on different IPCC SRES scenarios ( Intergovernmental Panel on Climate Change Special Report on Emission Scenarios) Investigate results for scenarios and find out main drivers How EU/national policies can moderate urban growth

Study area

Population: ~71 million Area: ~ km 2 NUTS2*: 38 *Nomenclature des unités territoriales statistiques the nomenclature of territorial units for statistics (EuroStat) Country Total area Population (2008) Population Density (2008) km 2 peoplePeople per km 2 Poland Hungary Czech Rep Lithuania Latvia Slovakia Estonia

RUG Model Regional urban growth has been developed from Tyndall East Anglia model. Modelling space by measuring proportional change to baseline (2005). Model was used to predict changes caused by environmental changes in GHG levels in East Anglia and North West England - based on IPCC SRES emission scenarios.

IPCC Scenarios Economic values / private enterprise Environmental and social values / Public Regional / Local and bottom up dynamic Global / Macro and top down dynamic A1 (hyper – tech): Fast economic growth High global population Expansion of cities and shrinking rural areas Rapid development of ICT A2 (extreme water): Regional-oriented economic development Rise of global population Increase of extreme natural events B1 (sustainability): Sustainable development Environmental protection Population concentrates in cities and towns Decline of oil production and rise of energy prices B2 (environmental enclaves): Fragmented society Increasing migration of working-age population Social exclusion and pandemic events

Data used in the project Data is in a grid format with 1 x 1 km cell size as comma separated values (.csv files). Datasets: 1)Distance to cities 2)Distance to the coastline 3)Flood zones 4)Proportion of artificial surface 5)Distance to main roads Data is collected from Eurostat and European Environmental Agency.

Spatial Analysis and Sensitivity ROC (Receiver Operating Characteristics) – sensitivity analysis; measure magnitude of effects and error rates. Other statistics: regression, correlation, dispersion, chi 2 and other.

Results for Central Europe and the Baltic States.

What the projections show  Using MatLab the model was run for all scenarios, with ArcMap outputs were visualised and reclassified and with SPSS were analysed.  For the scenarios we received various urban growth results and spatial distributions.  Visualised clusters and regions with similar urban growth.  Some group of countries may develop the same way in the scenarios.  Different EU/national policies can moderate future urban growth and shape the landscape of Central Europe and the Baltic States

Summary RUG model implemented to Central Europe and the Baltic States. Different scenarios with various assumptions and their implication to urban space in the region. Comparative studies between regions and countries. How the modelling can be used as a tool to support policy decisions on different levels.

GIS Project – Wolverhampton 25 th Sept Thank you. Pawel Langner Complet report: