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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
Biljecki, Filip; Sindram, Maximilian 
Title:
Estimating Building Age with 3D GIS 
Pages contribution:
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...    »
 
Keywords:
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 
Editor:
Kalantari, Mohsen; Rajabifard, Abbas 
Book / Congress title:
Proceedings of the 12th International 3D GeoInfo Conference 2017 
Volume:
IV-4/W5 
Organization:
University of Melbourne 
Publisher:
ISPRS 
Date of publication:
26.10.2017 
Year:
2017 
Covered by:
Scopus; Web of Science 
Bookseries title:
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 
Reviewed:
ja 
Language:
en 
Notes:
This paper received the Best Paper Award. 
TUM Institution:
Lehrstuhl für Geoinformatik