Articles | Volume 13, issue 11
Development and technical paper
27 Nov 2020
Development and technical paper |  | 27 Nov 2020

Geospatial input data for the PALM model system 6.0: model requirements, data sources and processing

Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch

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Cited articles

Arbeitsgemeinschaft der Vermessungsverwaltungen der Länder der Bundesrepublik Deutschland: 3D-Gebäudemodelle LoD1: Produktblatt, available at: (last access: 30 August 2020), 2019a. a
Arbeitsgemeinschaft der Vermessungsverwaltungen der Länder der Bundesrepublik Deutschland: 3D-Gebäudemodelle LoD2: Produktblatt, available at: (last access: 30 August 2020), 2019b. a
Baghdadi, N. and Zribi, M.: Optical remote sensing of land surfaces: Techniques and methods, Remote Sensing Observations of Continential Surfaces Set, Elsevier and ISTE Press, Oxford and London,, 2016. a
Belda, M., Resler, J., Geletič, J., Krč, P., Maronga, B., Sühring, M., Kurppa, M., Kanani-Sühring, F., Fuka, V., Eben, K., Benešová, N., and Auvinen, M.: Sensitivity analysis of the PALM model system 6.0 in the urban environment, Geosci. Model Dev. Discuss.,, in review, 2020. a, b
Bocher, E., Petit, G., Bernard, J., and Palominos, S.: A geoprocessing framework to compute urban indicators: The MApUCE tools chain, Urban Climate, 24, 153–174,, 2018. a, b, c
Short summary
For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.