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High-resolution topographic surveying and change detection with the iPhone LiDAR

Nature Protocols (2024)Cite this article

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Abstract

This paper introduces a comprehensive protocol leveraging open-access techniques to create small- to medium-scale 3D representations of the environment by using iPhone and iPad light detection and ranging (LiDAR). The protocol focuses on two capabilities of the iPhone LiDAR. The first capability is 3D modeling: iPhone LiDAR rapidly generates detailed indoor and outdoor 3D models, providing insights into object size, volume and geometry. The second capability is change detection: the 3D models created by the LiDAR sensor can be used for precise measurement of changes over time. Compared to other 3D topographic surveying methods, this method is rapid, high resolution, low cost and easy to use. The protocol outlines iPhone LiDAR scanning practices, model export and change detection. The expected results after executing the protocol are (i) a detailed 3D model of a small- to medium-sized object or area of interest and (ii) a distance point cloud revealing change between two point clouds of the same object or area between different times. The entire protocol can be conducted within 2 h by anyone with an iPhone with the LiDAR sensor and a computer. This protocol empowers scientists, students and community members conducting research with a cheap, easy-to-use method for addressing a range of questions and challenges, thus benefiting experts and the broader community.

Key points

  • This protocol describes the use of iPhone LiDAR to generate high-resolution indoor and outdoor 3D models, providing insights into object size, volume and geometry. The 3D models created by the LiDAR sensor can be used for precise measurement of changes over time.

  • Compared with other 3D surveying methods such as photogrammetry, this method is fast and cost effective and achieves high resolution. It also makes 3D surveying accessible to non-experts.

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Fig. 1: Outline of the protocol.
Fig. 2: 3d Scanner App user interface and scan modes.
Fig. 3: Flow diagram of scanning and export options.
Fig. 4: Recoding a LiDAR scan with the iPhone.
Fig. 5: CloudCompare graphical user interface with a LiDAR point cloud of a mushroom rock in the center, DB Tree and Properties to the left and toolbar on the top.
Fig. 6: M3C2 distance point cloud.
Fig. 7: Anticipated results.

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Data availability

Test data for Steps 10–37 are available at https://doi.org/10.6084/m9.figshare.24434689.v1.

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Acknowledgements

G.L. expresses gratitude to M. Jensen and C.N. Blok from the University Center in Svalbard for their kind invitation to Longyearbyen. This opportunity allowed him to gather the example data used in developing this protocol. We are also thankful to T. Dunlop from UNSW Sydney for feedback on an earlier version of the protocol.

Author information

Authors and Affiliations

  1. Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark

    Gregor Luetzenburg & Kristian K. Kjeldsen

  2. Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark

    Aart Kroon & Anders A. Bjørk

  3. School of Civil and Environmental Engineering and Water Research Laboratory (WRL), UNSW Sydney, Sydney, New South Wales, Australia

    Kristen D. Splinter

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  1. Gregor Luetzenburg
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  5. Anders A. Bjørk
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Contributions

G.L. was responsible for conceptualization, method development, visualization and writing the original draft. All authors were responsible for review and editing.

Corresponding author

Correspondence to Gregor Luetzenburg.

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The authors declare no competing interests.

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Nature Protocols thanks Amerigo Corradetti, Georg Stauch and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Key reference using the protocol

Luetzenburg, G. et al. Sci. Rep. 11, 22221 (2021): https://doi.org/10.1038/s41598-021-01763-9

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Luetzenburg, G., Kroon, A., Kjeldsen, K.K. et al. High-resolution topographic surveying and change detection with the iPhone LiDAR. Nat Protoc (2024). https://doi.org/10.1038/s41596-024-01024-9

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