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Titel:

Bavaria Building Dataset (BBD)

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
27.10.2023
Verantwortlich:
Werner, Martin
Autorinnen / Autoren:
Werner, Martin; Li, Hao; Zollner Max, Teuscher, Balthasar
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Identifikator:
doi:10.14459/2023mp1709451
Enddatum der Datenerzeugung:
15.05.2023
Fachgebiet:
BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; GEO Geowissenschaften; UMW Umweltwissenschaften
Quellen der Daten:
Experimente und Beobachtungen / experiments and observations; Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
Datentyp:
Bilder / images; mehrdimensionale Visualisierungen oder Modelle / models; Datenbanken / data bases
Methode der Datenerhebung:
The data was processed using a geospatial data processing engine in order to bring the original datasets into an analysis-ready representation suitable for adoption by communities and computational environments that do not model the geospatial aspects. Concretely speaking, images have been manually processed, the cartographic rendered mapnik has been used to transform geodatabases into georeferenced images, and Ohsome API was used to create a snapshot of OpenStreetMap information from a suitable...     »
Beschreibung:
The Bavarian Building Dataset (BBD) is an analysis-ready dataset providing an openly available 40cm image dataset over Bavaria (CC-BY4.0, Digitales Ortophoto 40cm - DOP40, https://geodatenonline.bayern.de/) combined with building footprint information as GIS data (Shapefiles) and co-registered imagery. This data has been taken from official building footprints as published openly (CC-BY 4.0, Hausumringe, https://geodaten.bayern.de/). In addition, our dataset contains building footprint geometry...     »
Links:

Further information: https://www.bgd.ed.tum.de/datasets/bbd

Schlagworte:
Image Analysis; Building Detection; Geospatial Information Science; Urban Computing; Benchmark Dataset
Technische Hinweise:
View and download (353 GB total, 16 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1709451):
rsync rsync://m1709451@dataserv.ub.tum.de/m1709451/
Sprache:
en
Rechte:
by, http://creativecommons.org/licenses/by/4.0
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