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Open AccessArticle

A Workflow for Automatic Quantification of Structure and Dynamic of the German Building Stock Using Official Spatial Data

Leibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, Dresden 01217, Germany
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(8), 142;
Received: 18 May 2016 / Revised: 25 July 2016 / Accepted: 29 July 2016 / Published: 9 August 2016
Knowledge of the German building stock is largely based on census data and annual construction statistics. Despite the wide range of statistical data, they are constrained in terms of temporal, thematic and spatial resolution, and hence do not satisfy all requirements of spatial planning and research. In this paper, we describe a new workflow for data integration that allows the quantification of the structure and dynamic of national building stocks by analyzing authoritative geodata. The proposed workflow has been developed, tested and demonstrated exemplarily for the whole country of Germany. We use nationwide and commonly available authoritative geodata products such as building footprint and address data derived from the real estate cadaster and land use information from the digital landscape model. The processing steps are (1) data preprocessing; (2) the calculation of building attributes; (3) semantic enrichment of the building using a classification tree; (4) the intersection with spatial units; and finally (5) the quantification and cartographic visualization of the building structure and dynamic. Applying the workflow to German authoritative geodata, it was possible to describe the entire building stock by 48 million polygons at different scale levels. Approximately one third of the total building stock are outbuildings. The methodological approach reveals that 62% of residential buildings are detached, 80% semi-detached and 20% terraced houses. The approach and the novel database will be very valuable for urban and energy modeling, material flow analysis, risk assessment and facility management. View Full-Text
Keywords: building stock; building classification; authoritative geodata building stock; building classification; authoritative geodata
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Hartmann, A.; Meinel, G.; Hecht, R.; Behnisch, M. A Workflow for Automatic Quantification of Structure and Dynamic of the German Building Stock Using Official Spatial Data. ISPRS Int. J. Geo-Inf. 2016, 5, 142.

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