Integrating Models for Complex Planning Policy Analysis: Challenges and a Solution in Coupling Dissimilar Models
Authors: Harutyun Shahumyan, Rolf Moeckel
Report
Synopsis: It is an expensive and time consuming task to develop a new model. Besides, a single model often cannot provide answers required for integrated decision making. Therefore, coupling existing models is often used for model integration. The paper provides an overview of possible model integration approaches, briefly explains the models of a particular application and focuses on the integration methods applied in this research. While the initial attempt was to integrate all models as tightly as possible, the authors developed a much more agile integration approach. Python wrappers were developed to loosely couple land-use, transportation and emission models developed in different environments. ArcGIS Model Builder was used to provide a graphical user interface and to present the models’ workflow. The suggested approach is efficient when the models are developed in different programming languages, their source codes are not available or the licen! sing restrictions make other coupling approaches infeasible.
Authors: Harutyun Shahumyan, Rolf Moeckel
Report
Synopsis: It is an expensive and time consuming task to develop a new model. Besides, a single model often cannot provide answers required for integrated decision making. Therefore, coupling existing models is often used for model integration. The paper provides an overview of possible model integration approaches, briefly explains the models of a particular application and focuses on the integration methods applied in this research. While the initial attempt was to integrate all models as tightly as possible, the authors developed a much more agile integration approach. Python wrappers were developed to loosely couple land-use, transportation and emission models developed in different environments. ArcGIS Model Builder was used to provide a graphical user interface and to present the models’ workflow. The suggested approach is efficient when the models are developed in different programming languages, their source codes are not available or the licen! sing restrictions make other coupling approaches infeasible.