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7. CONCLUSION AND OUTLOOK
The result shows that the method is able to deliver similar
values like a heat atlas and can be used for regions that do not
have a heat atlas.
Currently, we are trying to improve our method in several
ways. Firstly, we are extending the set of attributes for the
individual buildings, by also taking relations into account, e.g.
the distance to the street, or the distance to neighbouring
buildings.
At the moment the building typology only considers residential
buildings. In future we will use other training datasets which
also have building types for other buildings, e.g. schools or
industrial buildings.
The next step is to analyze the settlement types with regard to
find suitable regions for local and district heating. To this end,
not only the individual settlement areas of similar type have to
be analyzed, but also other factors have to be taken into
account, e.g. existing pipelines, or the size of the area and
distribution of the buildings, which directly is linked to the
costs for installing the pipelines.
ACKNOWLEDGEMENTS
We gratefully acknowledge the funding by the AGFW
(Arbeitsgemeinschaft Fernwürme, e.V.) The laser scanning
data was provided by the Landesvermessungsamt Baden-
Württemberg, building ground plans by the Stadtmessungsamt
Stuttgart.
REFERENCES
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Anders, K.-H., 2002: Parameterfreies hierarchisches Graph-
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Baltsavias, E. P., Gruen, A., van Gool, L., 2001: Automatic
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Brenner, C., 2000: Dreidimensionale Gebäuderekonstruktion
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Briese, Ch., Pfeifer , N., Dorninger, P., 2002: Applications of
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Masaharu, H., Ohtsubo, K., 2002: A Filtering Method of
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Neidhart, H., Brenner,C., 2003: Automatic Calculation of
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