Dear all,

recently, I finished a study on clustering building blocks and combining blocks 
to city districts of similar urban morphology.
The basis was 3D CityGML building data and additional 2d cadastral data from 
Germany and the application of unsupervised (and supervised) machine learning 
algorithms to this GIS data.
After importing a CityGML data set to a PostgreSQL/PostGIS database via 
3DCity-Importer-Exporter (https://github.com/3dcitydb) and pre-processing it, 
the dataset consisted of 2D building footprint polygons and additional 
variables, e.g. the building height and the type a the roof. Some data 
processing was done directly in PostGIS, but the major part using R/PostGIS 
database connections (packages DBI, RPostgres and RPostgreSQL) and r packages 
for spatial analysis (packages sf, sp, foot, lwgeom) and non-spatial data 
analysis (stats, cluster, fcp, klaR)


However, at the moment I am looking for a possibility to derive some additional 
information from the 3D representations of the buildings by analyzing the 
surfaces (polygons or multipolygons) and solids.
PostGIS itself has at least a basic function for 3d area calculation: 
https://postgis.net/docs/ST_3DArea.html. Commercial software like FME from SAFE 
is allowing for CityGML reading, writing and analysis. ESRI delivers 
(commercial) possibilities for 3D data analyses as well.
Do you know packages which can handle 3D geospatial data in R or do you have 
any other suggestions on free / open source solutions which easily can be 
integrated into an R based data analysis?


Any feedback is appreciated.
Many thanks in advance an best regards
André

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André Müller

IWU - Institut Wohnen und Umwelt GmbH
Rheinstraße 65
64295 Darmstadt

Institute for Housing and Environment -
Research institution of the State of Hesse and the City of Darmstadt

Telefon: +49 6151 2904-18
E-Mail: a.muel...@iwu.de<mailto:a.muel...@iwu.de>
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