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dc.contributor.author
Demir, Nusret
dc.contributor.author
Poli, Daniela
dc.contributor.author
Baltsavias, Emmanuel
dc.contributor.editor
Stilla, Uwe
dc.contributor.editor
Rottensteiner, Franz
dc.contributor.editor
Paparoditis, Nicolas
dc.date.accessioned
2019-10-09T10:41:16Z
dc.date.available
2017-06-08T21:55:09Z
dc.date.available
2019-10-09T10:41:16Z
dc.date.issued
2009
dc.identifier.issn
1682-1750
dc.identifier.issn
2194-9034
dc.identifier.issn
1682-1777
dc.identifier.uri
http://hdl.handle.net/20.500.11850/15910
dc.identifier.doi
10.3929/ethz-b-000015910
dc.description.abstract
In this work, we focus on the detection of buildings, by combining information from aerial images and Lidar data. We applied four different methods on a dataset located at Zurich Airport, Switzerland. The first method is based on DSM/DTM comparison in combination with NDVI analysis (Method 1). The second one is a supervised multispectral classification refined with a normalized DSM (Method 2). The third approach uses voids in Lidar DTM and NDVI classification (Method 3), while the last method is based on the analysis of the density of the raw Lidar DTM and DSM data (Method 4). An improvement has been achieved by fusing the results of the different methods, taking into account their advantages and disadvantages. Edge information from images has alsobeen used for quality improvement of the detected buildings. The accuracy of the building detection was evaluated by comparing the results with reference data, resulting in 94% detection and 7% omission errors for the building area.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
ISPRS
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/3.0/
dc.subject
DTMs/DSMs
en_US
dc.subject
Lidar Data Processing
en_US
dc.subject
Multispectral Classification
en_US
dc.subject
Image Matching
en_US
dc.subject
Information Fusion
en_US
dc.subject
Object Detection
en_US
dc.subject
Buildings
en_US
dc.title
Extraction of Buildings using Images & Lidar Data and a Combination of Various Methods
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution 3.0 Unported
ethz.journal.title
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
ethz.journal.volume
XXXVIII
en_US
ethz.journal.issue
3/W4
en_US
ethz.journal.abbreviated
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.
ethz.pages.start
71
en_US
ethz.pages.end
76
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.event
ISPRS Workshop on Object Extraction for 3D City Models, Road Databases and Traffic Monitoring - Concepts, Algorithms and Evaluation 2009 (CMRT09)
en_US
ethz.event.location
Paris, France
en_US
ethz.event.date
September 3-4, 2009
en_US
ethz.identifier.wos
ethz.identifier.nebis
004958079
ethz.publication.place
Lemmer
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
03220 - Grün, Armin
en_US
ethz.leitzahl.certified
03220 - Grün, Armin
ethz.identifier.url
https://www.isprs.org/proceedings/XXXVIII/3-W4/
ethz.date.deposited
2017-06-08T21:55:15Z
ethz.source
ECIT
ethz.identifier.importid
imp59364c5b36ad182145
ethz.ecitpid
pub:27742
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-26T20:42:27Z
ethz.rosetta.lastUpdated
2019-10-09T10:41:31Z
ethz.rosetta.versionExported
true
ethz.COinS
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