
Proceedings Paper
Classification and extraction of trees and buildings from urban scenes using discrete return LiDAR and aerial color imageryFormat | Member Price | Non-Member Price |
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Paper Abstract
Airborne Light Detection and Ranging (LiDAR) is used in many 3D applications, such as urban planning, city modeling,
facility management, and environmental assessments. LiDAR systems generate dense 3D point clouds, which provide a
distinct and comprehensive geometrical description of object surfaces. However, the challenge is that most of the
applications require correct identification and extraction of objects from LiDAR point clouds to facilitate quantitative
descriptions. This paper presents a feature-level fusion approach between LiDAR and aerial color (RGB) imagery to
separate urban vegetation and buildings from other urban classes/cover types. The classification method used structural
and spectral features derived from LiDAR and RGB imagery. Features such as flatness and distribution of normal vectors
were estimated from LiDAR data, while the non-calibrated normalized difference vegetation index (NDVI) was
calculated by combining LiDAR intensity at 1064 nm with the red channel from the RGB imagery. Building roof tops
have regular surfaces with smaller variation in surface normal, whereas tree points generate irregular surfaces. Tree
points, on the other hand, exhibit higher NDVI values when compared to returns from other classes. To identify
vegetation points an NDVI map was used, while a vegetation mask was also derived from the RGB imagery. Accuracy
was assessed by comparing the extraction result with manually digitized reference data generated from the high spatial
resolution RGB image. Classification results indicated good separation between building and vegetation and exhibited
overall accuracies greater than 85%.
Paper Details
Date Published: 20 May 2013
PDF: 9 pages
Proc. SPIE 8731, Laser Radar Technology and Applications XVIII, 873105 (20 May 2013); doi: 10.1117/12.2015890
Published in SPIE Proceedings Vol. 8731:
Laser Radar Technology and Applications XVIII
Monte D. Turner; Gary W. Kamerman, Editor(s)
PDF: 9 pages
Proc. SPIE 8731, Laser Radar Technology and Applications XVIII, 873105 (20 May 2013); doi: 10.1117/12.2015890
Show Author Affiliations
Madhurima Bandyopadhyay, Rochester Institute of Technology (United States)
Jan A. N. van Aardt, Rochester Institute of Technology (United States)
Jan A. N. van Aardt, Rochester Institute of Technology (United States)
Kerry Cawse-Nicholson, Rochester Institute of Technology (United States)
Published in SPIE Proceedings Vol. 8731:
Laser Radar Technology and Applications XVIII
Monte D. Turner; Gary W. Kamerman, Editor(s)
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