Extraction of Buildings using Images & Lidar Data and a Combination of Various Methods
Open access
Date
2009Type
- Conference Paper
ETH Bibliography
yes
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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. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000015910Publication status
publishedExternal links
Journal / series
International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesVolume
Pages / Article No.
Publisher
ISPRSEvent
Subject
DTMs/DSMs; Lidar Data Processing; Multispectral Classification; Image Matching; Information Fusion; Object Detection; BuildingsOrganisational unit
03220 - Grün, Armin
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ETH Bibliography
yes
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