Final Report Summary - GEOSINPO (Geo-Spatial Modelling Informing Policy)
Led by Marie Sklodowska-Curie Research Fellow Dr. Harutyun Shahumyan, the EC-supported GeoSInPo project aimed to achieve a thorough understanding of the dynamic processes involved in urban and environmental models and different approaches for their integration.
Developing a new integrated model linking multiple disciplines is a costly and time-consuming process. Usually, it takes years if not decades, and deep knowledge of several experts in the field to develop, calibrate and validate a single model for a region. Instead, the main objective of the GeoSInPo project was to integrate existing discipline-specific recognised models within a Spatial Decision Support System (SDSS) to inform decision makers through evidence-based scenario and policy analysis. The project also aimed to engage with the stakeholders involved in land use, transportation, urban planning and watershed management in the study regions to analyse policy options for regional development in response to different ‘what if’ scenarios in the context of population growth, urbanisation, climate change, and more.
THE WORK CARRIED OUT TO ACHIEVE THE PROJECT'S OBJECTIVES
The GeoSInPo project has focused on how to best combine existing discipline-specific tools and independent models to devise a quick and effective solution to generate integrated models for different urban regions. The model coupling approach developed in the project makes integration of existing models easier to achieve, overcoming challenges such as differences in programming languages, unavailability of the source codes or licensing restrictions. A loose model coupling was applied to build an integrated Spatial Decision Support System (SDSS). The implementation of the couplers is separated from the models’ source codes. This gives a flexibility, which can help in terms of portability, performance and maintenance of the model codes. The platform overcomes key model integration challenges to be able to make use of a wide variety of information and indicators from different models. It has been tested and applied by the National Center for Smart Growth (NCSG) University of Maryland in the US, where Dr. Shahumyan spent two years of the Marie Curie fellowship, and at the School of Architecture, Planning and Environmental Policy, University College Dublin in Ireland, where he has carried on his research in the final year of the project.
THE MAIN RESULTS
An unique toolset was developed, enabling disparate socio-economic and environmental models to be linked in order to project future trends and evaluate the impact of urban development decisions.
The approach was successfully implemented for:
- The Baltimore-Washington Region - coupling five independently developed models: Simple Integrated Land Use Orchestrator (SILO), Maryland State-wide Transport Model (MSTM), Building Emission Model (BEM), Mobile Emission Model (MEM), Chesapeake Bay Land Change Model (CBLCM) (See Fig. 1-BWR_Models.jpg);
- The Greater Dublin Region - coupling two independently developed models: Land use model MOLAND and Source Load Apportionment Model (SLAM) (See Fig. 2-GDR_Models.jpg).
The integrated suites are now being applied to simulate and explore alternative future scenarios for these regions. The SDSS outputs include several useful socio-economic indicators, covering: population and employment, transport flow, land use, building and mobile emissions, water quality and more.
The results of these two case studies are promising. The independently developed models smoothly exchange data in a single modelling platform, allowing non-technical users to focus on analysis and results.
CONCLUSIONS AND THEIR POTENTIAL IMPACT
The suggested approach allows for the addition of new models relatively easily. It is known that the changes in transportation, land use and human behaviour impact also on nutrient loading and water quality in a region. Translating the effect of socio-economic alterations into nutrient loading in Chesapeake Bay for example will help us to explore the changes in flow and nutrients loads into the Bay and design more effective public policies and restoration plans. Adding environmental models to the policy decision making process will help to assess how social-economic changes and policy decisions in the Baltimore-Washington Region ultimately impact water quality in the Chesapeake Bay or in the Greater Dublin Region on Liffey Catchment and Dublin Bay. To continue this work another project has been recently awarded to the NCSG by the US National Socio-Environmental Synthesis Center (SESYNC) to enhance the Baltimore-Washington Region modelling suite with water quality and habitat models. The attached figure (Fig1-BWR_Models.jpg) illustrates existing coupled models for the Washington-Baltimore Region and the models currently being added to the suite.
The source codes and supporting documentation generated by GeoSInPo are published publicly and available for other researchers, enabling the platform to easily be applied to other models for other regions. From a scientific perspective, the work is set to significantly contribute to global understanding of human activity and environmental linkages in urban areas, enabling improved policy development and decision-making focused on ensuring urban sustainability. The results can also contribute to and improve previous research in both study regions making the research outcomes more reliable and useful for both study regions’ spatial governance systems.
More information on the project outputs including publications and video podcasts are available in the project website at: http://geosinpo.shahumyan.org
Developing a new integrated model linking multiple disciplines is a costly and time-consuming process. Usually, it takes years if not decades, and deep knowledge of several experts in the field to develop, calibrate and validate a single model for a region. Instead, the main objective of the GeoSInPo project was to integrate existing discipline-specific recognised models within a Spatial Decision Support System (SDSS) to inform decision makers through evidence-based scenario and policy analysis. The project also aimed to engage with the stakeholders involved in land use, transportation, urban planning and watershed management in the study regions to analyse policy options for regional development in response to different ‘what if’ scenarios in the context of population growth, urbanisation, climate change, and more.
THE WORK CARRIED OUT TO ACHIEVE THE PROJECT'S OBJECTIVES
The GeoSInPo project has focused on how to best combine existing discipline-specific tools and independent models to devise a quick and effective solution to generate integrated models for different urban regions. The model coupling approach developed in the project makes integration of existing models easier to achieve, overcoming challenges such as differences in programming languages, unavailability of the source codes or licensing restrictions. A loose model coupling was applied to build an integrated Spatial Decision Support System (SDSS). The implementation of the couplers is separated from the models’ source codes. This gives a flexibility, which can help in terms of portability, performance and maintenance of the model codes. The platform overcomes key model integration challenges to be able to make use of a wide variety of information and indicators from different models. It has been tested and applied by the National Center for Smart Growth (NCSG) University of Maryland in the US, where Dr. Shahumyan spent two years of the Marie Curie fellowship, and at the School of Architecture, Planning and Environmental Policy, University College Dublin in Ireland, where he has carried on his research in the final year of the project.
THE MAIN RESULTS
An unique toolset was developed, enabling disparate socio-economic and environmental models to be linked in order to project future trends and evaluate the impact of urban development decisions.
The approach was successfully implemented for:
- The Baltimore-Washington Region - coupling five independently developed models: Simple Integrated Land Use Orchestrator (SILO), Maryland State-wide Transport Model (MSTM), Building Emission Model (BEM), Mobile Emission Model (MEM), Chesapeake Bay Land Change Model (CBLCM) (See Fig. 1-BWR_Models.jpg);
- The Greater Dublin Region - coupling two independently developed models: Land use model MOLAND and Source Load Apportionment Model (SLAM) (See Fig. 2-GDR_Models.jpg).
The integrated suites are now being applied to simulate and explore alternative future scenarios for these regions. The SDSS outputs include several useful socio-economic indicators, covering: population and employment, transport flow, land use, building and mobile emissions, water quality and more.
The results of these two case studies are promising. The independently developed models smoothly exchange data in a single modelling platform, allowing non-technical users to focus on analysis and results.
CONCLUSIONS AND THEIR POTENTIAL IMPACT
The suggested approach allows for the addition of new models relatively easily. It is known that the changes in transportation, land use and human behaviour impact also on nutrient loading and water quality in a region. Translating the effect of socio-economic alterations into nutrient loading in Chesapeake Bay for example will help us to explore the changes in flow and nutrients loads into the Bay and design more effective public policies and restoration plans. Adding environmental models to the policy decision making process will help to assess how social-economic changes and policy decisions in the Baltimore-Washington Region ultimately impact water quality in the Chesapeake Bay or in the Greater Dublin Region on Liffey Catchment and Dublin Bay. To continue this work another project has been recently awarded to the NCSG by the US National Socio-Environmental Synthesis Center (SESYNC) to enhance the Baltimore-Washington Region modelling suite with water quality and habitat models. The attached figure (Fig1-BWR_Models.jpg) illustrates existing coupled models for the Washington-Baltimore Region and the models currently being added to the suite.
The source codes and supporting documentation generated by GeoSInPo are published publicly and available for other researchers, enabling the platform to easily be applied to other models for other regions. From a scientific perspective, the work is set to significantly contribute to global understanding of human activity and environmental linkages in urban areas, enabling improved policy development and decision-making focused on ensuring urban sustainability. The results can also contribute to and improve previous research in both study regions making the research outcomes more reliable and useful for both study regions’ spatial governance systems.
More information on the project outputs including publications and video podcasts are available in the project website at: http://geosinpo.shahumyan.org