3dfier: automatic reconstruction of 3D city models

Ledoux, Hugo; Biljecki, Filip; Dukai, Balázs; Kumar, Kavisha; Peters, Ravi; Stoter, J.E.; Commandeur, T.J.F.

doi:10.21105/joss.02866

Cited by 48 publications

(30 citation statements)

References 6 publications

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“…Rapid technological developments impact the development of increasingly sophisticated data acquisition techniques. A 3D model can be obtained from various acquisition techniques [9], for example photogrammetry [18], laser scanning [19][20][21], extrusion from 2D sites [22], Synthetic Aperture Radar (SAR) [23,24], and architectural drawings and models.…”

Section: Related Workmentioning

confidence: 99%

3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management

Suwardhi

Fauzan

Harto

et al. 2022

IJGI

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The development and management of green open spaces are essential in overcoming environmental problems such as air pollution and urban warming. 3D modeling and biomass calculation are the example efforts in managing green open spaces. In this study, 3D modeling was carried out on point clouds data acquired by the UAV photogrammetry and UAV LiDAR methods. 3D modeling is done explicitly using the point clouds fitting method. This study uses three fitting methods: the spherical fitting method, the ellipsoid fitting method, and the spherical harmonics fitting method. The spherical harmonics fitting method provides the best results and produces an R2 value between 0.324 to 0.945. In this study, Above-Ground Biomass (AGB) calculations were also carried out from the modeling results using three methods with UAV LiDAR and Photogrammetry data. AGB calculation using UAV LiDAR data gives better results than using photogrammetric data. AGB calculation using UAV LiDAR data gives an accuracy of 78% of the field validation results. However, for visualization purposes with a not-too-wide area, a 3D model of photogrammetric data using the spherical harmonics method can be used.

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Section: Related Workmentioning

confidence: 99%

3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management

Suwardhi

Fauzan

Harto

et al. 2022

IJGI

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“…Meanwhile, the reconstruction of 3D building models still remains semiautomatic, and to the authors’ knowledge, there are some groups working on automatic 3D building model reconstruction from LiDAR data. [ 63–65 ] A collaboration can be expected to realize a fully automatic PV AC yield modeling framework based on LiDAR data and building footprint.…”

Section: Limitations and Outlookmentioning

confidence: 99%

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

et al. 2021

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Photovoltaic (PV) technology is the most promising renewable energy source to be integrated on urban building surfaces. Modeling and simulating urban PV systems pose more challenges than the conventional ones installed in open field due to rich urban morphology. Herein, a comprehensive workflow to estimate urban solar PV potential is developed where TU Delft campus is used as a case study. This workflow only requires light detection and ranging data and building footprints as data inputs, and multiple levels of result can be delivered including accurate geo‐referenced 3D building models, annual solar irradiation map, annual DC/AC yield maps and classified roof segments according to the specific yield of mounted PV system. The study reports a total of ≈8.1 GWh year−1 of PV energy which can be collected from campus building roofs and facades. Given the total electricity demand on the entire campus being 82.6 GWh/year, this PV potential can cover roughly 10% of the current electricity demand. The results constitute an initial assessment of solar PV potential on TU Delft campus buildings that is currently being used to prioritize PV integration on buildings and accelerate the transition toward a climate‐neutral campus.

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“…These methods can thus hardly be applied to large-scale urban scenes. To facilitate practical applications that require large-scale 3D building models, researchers have attempted to address the reconstruction challenge using various data sources [4,6,16,22,23,25,40,49]. Existing methods based on aerial images [6,16,23] and dense triangle meshes [40] typically require good coverage of the buildings, which imposes challenges in data acquisition [53].…”

Section: Introductionmentioning

confidence: 99%

“…Approaches based on airborne point clouds alleviate data acquisition issues. However, the accuracy and geometric details are usually compromised [4,22,25,49]. Following previous works using widely available airborne point clouds, we strive to recover desired geometric details of real-world buildings while ensuring topological correctness, reconstruction accuracy, and good efficiency.…”

Section: Introductionmentioning

confidence: 99%

City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds

Huang¹,

Stoter²,

Peters³

et al. 2022

Preprint

Self Cite

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We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne point clouds have demonstrated that the method is superior to the stateof-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne point clouds and the use of 3D city models in urban applications.

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3dfier: automatic reconstruction of 3D city models

Cited by 48 publications

References 6 publications

3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management

3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds

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