Methodologies for synthetic spatial building stock modelling: data-availability-adapted approaches for the spatial analysis of building stock energy demand

HIGHLIGHTS

  • who: Claudio Nu00e4geli et al. from the Architecture and Civil Engineering Department, Chalmers University of Technology, AIT Austrian Institute of Technology, Vienna, Austria have published the article: Methodologies for Synthetic Spatial Building Stock Modelling: Data-Availability-Adapted Approaches for the Spatial Analysis of Building Stock Energy Demand, in the Journal: Energies 2022, 15, x FOR PEER REVIEW of /2022/
  • what: The aim of the article is therefore to: Develop and describe data-adapted approaches for generating spatially distributed synthetic building stocks that can be used in building stock modelling in data-scarce circumstances. The authors . . .

     

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