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Dokumenttyp:
Konferenzbeitrag 
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz 
Autor(en):
Biljecki, Filip; Sindram, Maximilian 
Titel:
Estimating Building Age with 3D GIS 
Seitenangaben Beitrag:
17-24 
Abstract:
Building datasets (e.g. footprints in OpenStreetMap and 3D city models) are becoming increasingly available worldwide. However, the thematic (attribute) aspect is not always given attention, as many of such datasets are lacking in completeness of attributes. A prominent attribute of buildings is the year of construction, which is useful for some applications, but its availability may be scarce. This paper explores the potential of estimating the year of construction (or age) of buildings from ot...    »
 
Stichworte:
3D city models; building age; year of construction; CityGML; machine learning; random forest regression; GISPro_SSD; GISTop_CityModeling; GISTop_SpatialModelingAndAlgorithms; LOCenter; LOCTop_Urban_Information_Modeling_Virtual_3D_City_Model 
Herausgeber:
Kalantari, Mohsen; Rajabifard, Abbas 
Kongress- / Buchtitel:
Proceedings of the 12th International 3D GeoInfo Conference 2017 
Band / Teilband / Volume:
IV-4/W5 
Ausrichter der Konferenz:
University of Melbourne 
Konferenzort:
Melbourne, Australia 
Verlag / Institution:
ISPRS 
Publikationsdatum:
26.10.2017 
Jahr:
2017 
Nachgewiesen in:
Scopus; Web of Science 
Serientitel:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 
Reviewed:
ja 
Sprache:
en 
Hinweise:
This paper received the Best Paper Award. 
TUM Einrichtung:
Lehrstuhl für Geoinformatik