A Hybrid Approach for Three-Dimensional Building Reconstruction in Indianapolis from LiDAR Data

Abstract

3D building models with prototypical roofs are more valuable in many applications than 2D building footprints. This research proposes a hybrid approach, combining the data-and model-driven approaches for generating LoD2-level building models by using medium resolution (0.91 m) LiDAR nDSM, the 2D building footprint and the high resolution orthophoto for the City of Indianapolis, USA. The main objective is to develop a GIS-based procedure for automatic reconstruction of complex building roof structures in a large area with high accuracy, but without requiring high-density point data clouds and computationally-intensive algorithms. A multi-stage strategy, which combined step-edge detection, roof model selection and ridge detection techniques, was adopted to extract key features and to obtain prior knowledge for 3D building reconstruction. The entire roof can be reconstructed successfully by assembling basic models after their shapes were reconstructed. This research finally created a 3D city model at the Level of Detail 2 (LoD2) according to the CityGML standard for the downtown area of Indianapolis (included 519 buildings).The reconstruction achieved 90.6% completeness and 96% correctness for seven tested buildings whose roofs were mixed by different shapes of structures. Moreover, 86.3% of completeness and 90.9% of correctness were achieved for 38 commercial buildings with complex roof structures in the downtown area, which indicated that the proposed method had the ability for large-area building reconstruction. The major contribution of this paper lies in designing an efficient method to reconstruct complex buildings, such as those with irregular footprints and roof structures with flat, shed and tiled sub-structures mixed together. It overcomes the limitation that building reconstruction using coarse resolution LiDAR nDSM cannot be based on precise horizontal ridge locations, by adopting a novel ridge detection method.

The Effects of Green Roofs on Outdoor Thermal Comfort, Urban Heat Island Mitigation and Energy Savings

“…Zheng et al [9] developed an extremely accurate GIS-based 3D city model for the representation of the buildings roofs using LiDAR nDSM. This hybrid approach was able to identify flat, tiled and pavilion roofs.…”

“…GIS-based methodology to evaluate green roofs and green urban areas 9 [4][5][6][7][8][9][10][11][12] Outdoor thermal comfort: UHI mitigation strategies and thermal comfort indexes 20 [2,4,[13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] Energy savings and Indoor thermal comfort from Green roofs 5 [1,[31][32][33][34] 2.…”

“…From a literature review [9,17,19,20,41], it has emerged that three main categories of indexes may be used to assess outdoor thermal comfort: energy balance models, empirical indexes and indexes based on linear equations.…”

A Heuristic Method for Power Pylon Reconstruction from Airborne LiDAR Data

“…Firstly, a candidate value x * of the current value x is sampled in space X according to q(x * |x) . Then, the acceptance probability A(x, x * ) is calculated by Equation (9). If the acceptance probability is bigger than the predefined threshold, then, the Markov chain will move towards x * ; otherwise, it rejects and remains at x.…”

“…Although there are many varieties of object reconstruction methods, the most reported methods can be divided into three general categories [9]: data-driven, model-driven and hybrid-driven.…”