International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-4/W16
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 303–308, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-303-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 303–308, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-303-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  01 Oct 2019

01 Oct 2019

AUTOMATED EXTRACTION OF BUILDINGS FROM AERIAL LIDAR POINT CLOUDS AND DIGITAL IMAGING DATASETS

A. Jamali1, P. Kumar2, and A. Abdul Rahman3 A. Jamali et al.
  • 1Faculty of Surveying Engineering, Apadana Institute of Higher Education, Shiraz, Iran
  • 2School of Natural and Built Environment, University of South Australia, Adelaide, Australia
  • 3Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia (UTM), Malaysia

Keywords: LiDAR, digital imaging, buildings extraction, OBIA, NGBDI

Abstract. To acquire 3D geospatial information, LiDAR technology provides the rapid, continuous and cost-effective capability. In this paper, two automated approaches for extracting building features from the integrated aerial LiDAR point cloud and digital imaging datasets are proposed. The assumption of the two approaches is that the LiDAR data can be used to distinguish between high- and low-rise objects while the multispectral dataset can be used to filter out vegetation from the data. Object-based image analysis techniques are applied to the extracted building objects. The two automated buildings extraction approaches are tested on a fusion of aerial LiDAR point cloud and digital imaging datasets of Istanbul city. The object-based automated technique presents better results compared to the threshold-based technique for extraction of building objects in term of visual interpretation.