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Remote Sens. 2016, 8(5), 415; doi:10.3390/rs8050415

Three-Dimensional Reconstruction of Building Roofs from Airborne LiDAR Data Based on a Layer Connection and Smoothness Strategy

1,2,3
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1,4,5,* , 1,4,5,6,* , 1,4,6
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Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
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Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210093, China
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State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210093, China
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Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210093, China
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Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University, Nanjing 210093, China
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Collaborative Innovation Center for the South Sea Studies, Nanjing University, Nanjing 210093, China
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Authors to whom correspondence should be addressed.
Academic Editors: Juha Hyyppä, Jie Shan, Guoqing Zhou and Prasad S. Thenkabail
Received: 17 January 2016 / Revised: 29 March 2016 / Accepted: 12 April 2016 / Published: 16 May 2016
(This article belongs to the Special Issue Airborne Laser Scanning)
View Full-Text   |   Download PDF [12875 KB, uploaded 16 May 2016]   |  

Abstract

A new approach for three-dimensional (3-D) reconstruction of building roofs from airborne light detection and ranging (LiDAR) data is proposed, and it includes four steps. Building roof points are first extracted from LiDAR data by using the reversed iterative mathematic morphological (RIMM) algorithm and the density-based method. The corresponding relations between points and rooftop patches are then established through a smoothness strategy involving “seed point selection, patch growth, and patch smoothing.” Layer-connection points are then generated to represent a layer in the horizontal direction and to connect different layers in the vertical direction. Finally, by connecting neighboring layer-connection points, building models are constructed with the second level of detailed data. The key contributions of this approach are the use of layer-connection points and the smoothness strategy for building model reconstruction. Experimental results are analyzed from several aspects, namely, the correctness and completeness, deviation analysis of the reconstructed building roofs, and the influence of elevation to 3-D roof reconstruction. In the two experimental regions used in this paper, the completeness and correctness of the reconstructed rooftop patches were about 90% and 95%, respectively. For the deviation accuracy, the average deviation distance and standard deviation in the best case were 0.05 m and 0.18 m, respectively; and those in the worst case were 0.12 m and 0.25 m. The experimental results demonstrated promising correctness, completeness, and deviation accuracy with satisfactory 3-D building roof models. View Full-Text
Keywords: airborne LiDAR; building roof; three-dimensional (3-D) reconstruction; layer-connection points; smoothness strategy airborne LiDAR; building roof; three-dimensional (3-D) reconstruction; layer-connection points; smoothness strategy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, Y.; Xu, H.; Cheng, L.; Li, M.; Wang, Y.; Xia, N.; Chen, Y.; Tang, Y. Three-Dimensional Reconstruction of Building Roofs from Airborne LiDAR Data Based on a Layer Connection and Smoothness Strategy. Remote Sens. 2016, 8, 415.

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