Building Zone Regulation Compliance Using LIDAR Data: Real-Life Tests in İstanbul
Abstract
Airborne Laser scanning systems with light detection and ranging (LIDAR) technology is one of the fast and
accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models
(DTM/DSM) is the main application of collecting LIDAR range data. The LIDAR technique facilitates the
rapid production of models which contain ground and above surface objects in 3D (Jaafar et al., 1999). Today
automatic / semi-automatic generation of 3D digital building models and other city furniture from LIDAR data
is a very active area of scientific research (Elaksher and Bethel, 2002) indicates that manual surface
reconstruction is very costly and time consuming, and the development of automated algorithms is of great
importance. Currently with this LIDAR data in place, it is possible to derive models and information (e.g. the
heights of the buildings).This paper focuses on and explains our efforts on automatically checking Buildings’
Zoning Regulation Compliance by integrating geometric information derived from 3D LIDAR data and
semantic information acquired from 2D Implementation Development Maps
Keywords
References
- Bailang,Y. Hongxing,L Jianping,W. Yingjie,H. and Li, ,Z. 2010, Automated derivation of urban building density information using airborne LiDAR data and object-based method. Landscape and Urban Planning. 98(3-4), 210-219.
- Elasksher, A. and Bethel, J. 2002. Building Extraction Using Lidar Data, ASORS-ACSM Annual Conference and FIG XXII Congress, Apr. 22-26, 2002.
- Jaafar, G. Priestnall, P. and P.M. Mather, 1999. The effects of LIDAR DSM grid resolution on categorising residential and industrial buildings. Proceedings of the ISPRS Workshop, 9-11 NOVEMBER 1999, La Jolla, USA.
- Prerna, R. and Singh, C.K. 2016, Evaluation of LiDAR and image segmentation based classification techniques for automatic building footprint extraction for a segment of Atlantic County, New Jersey, Geocarto International, Volume 31(6), pp.694-713.
- Zhang, K. Yan, J.; Chen, S-C. 2006 Automatic Construction of Building Footprints From Airborne LIDAR Data, Geoscience and Remote Sensing, IEEE Transactions on , Vol.44, No.9, pp.2523,2533.
- Zhao, Z., Duan, Y., Zhang, Y and Cao, R. 2015 Extracting buildings from and regularizing boundaries in airborne lidar data using connected operators, International Journal of Remote Sensing, Vol. 37(4), pp. 889-912.
- Yu, TT., Yang, M., Chen, CS, 2005, Automatic feature extraction and stereo image processing with genetic algorithms for LIDAR data, 2nd International Conference on Computer Graphics, Imaging and Vision (CGVIS 2005), Beijing,, China, 26-29 July 2005.
- Liu, X. 2008. Airborne LiDAR for DEM generation: some critical issues Progress in Physical Geography, Vol. 32, No. 1. pp. 31-49.
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Authors
Publication Date
March 7, 2016
Submission Date
January 18, 2016
Acceptance Date
March 3, 2016
Published in Issue
Year 2016 Volume: 3 Number: 1
Cited By
New Approach in Integrated Basin Modelling: Melen Airborne LIDAR
International Journal of Environment and Geoinformatics
https://doi.org/10.30897/ijegeo.530272Calculation of Volume Changes with 3D Point Clouds of Different Physical Environments
International Journal of Environment and Geoinformatics
https://doi.org/10.30897/ijegeo.667393Automatic Extraction of Trees by Using the Multiple Return Properties of the LIDAR Point Cloud
International Journal of Environment and Geoinformatics
https://doi.org/10.30897/ijegeo.667387
