A Spatial Data Analysis Approach for Public Policy Simulation in Thermal Energy Transition Scenarios

Lina Stanzel, Johannes Scholz, Franz Mauthner

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


The paper elaborates on an approach to simulate the effect of public policies regarding thermal energy transition pathways in urban communities. The paper discusses the underlying methodologies of calculating Heating Energy demand of buildings and the rationale for potential zones for thermal energy systems. In order to simulate the effects of public policies on communities the authors developed a spatial Agentbased Model, where the buildings are the main objects that are subject to change, based on a number of both technically and socio-demographic parameters. In order to fill a spatial Agentbased Model with data a number of open source and commercially available datasets need to be spatially analyzed and merged. The initial results of the spatial Agent-based Model simulation show that public policies for thermal energy transition can be simulated accordingly.
Original languageEnglish
Title of host publicationData Science - Analytics and Applications
Subtitle of host publicationProceedings of the 2nd International Data Science Conference – iDSC2019
EditorsPeter Haber, Thomas Lampoltshammer, Manfred Mayr
Place of PublicationWiesbaden
PublisherSpringer Vieweg
Number of pages6
ISBN (Print)978-3-658-27494-8
Publication statusPublished - 2019
Event2nd International Data Science Conference - Salzburg, Austria
Duration: 22 May 201924 May 2019


Conference2nd International Data Science Conference
Abbreviated titleiDSC2019

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