An approach to urban building height and floor estimation by using LiDAR data
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1ST CAJG 2018
An approach to urban building height and floor estimation by using LiDAR data Arzu Erener 1 & Gulcan Sarp 2 & Muhammet Ibrahim Karaca 1 Received: 16 July 2019 / Accepted: 11 September 2020 / Published online: 22 September 2020 # Saudi Society for Geosciences 2020
Abstract Assessment of precise, fast, and up-to-date building and building floor data are essential for urban design, planning, and management and urban environmental studies. These maps are frequently required for tracking building construction speed, monitoring horizontal and vertical urban growth and illegal constructions, updating building records, preparing reasonable urban plans, assessing hazard and risk, and generating infrastructure plans. In this study, a combination of aerial photographs and LiDAR data are used to produce individual building heights and then estimate building the floor. The two recorded laser pulse reflections of LiDAR point cloud data: First pulse (FP) and last pulse (LP) reflections were used to obtain the digital surface model (DSM) and the digital terrain model (DTM), respectively. The normalized digital surface model (nDSM) is calculated to obtain the height values of each building. The accuracy of the proposed algorithm is assessed for each building floor using ground truth data and has shown an overall accuracy of 79% and a kappa equal to 0.74 which is a promising result. Keywords LiDAR technique . Building floor estimation . 3D maps . Urban areas
Introduction In recent years, the three-dimensional (3D) urban modeling in a geographic information system (GIS) environment is attracting more attention in engineering and non-engineering applications due to their extensive use in numerous fields of spatial planning. Because planning is not possible without data inventories (Prerna and Singh 2016), the 3D modeling and visualization of buildings in the computer environment have become more convenient with the large memory, processing, handling, and graphics power of today’s hardware (Parish and Müller 2001). These methods play a critical role in saving time and resources in the creation, analysis, and This paper was selected from the 1st Conference of the Arabian Journal of Geosciences (CAJG), Tunisia 2018 Responsible Editor: Hesham El-Askary * Gulcan Sarp [email protected] 1
Department of Geomatic Engineering, Kocaeli University, 41380 Kocaeli, Turkey
2
Department of Geography, Süleyman Demirel University, 32260 Isparta, Turkey
visualization of 3D objects (Kiran 2015). With the advance of detection techniques, there are many data sources used to investigate on building extraction and reconstruction in urban areas such as aerial photography, high-resolution satellite imagery, and LiDAR data. Up-to-date, the passive remote sensing technologies are used to extract 2D urban features and to prepare land cover maps. In high-resolution remote sensing images, build-up objects can be easily differentiated from each other in urban areas due to their spatial pattern and shape. However, passive systems have some l
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