Avaliação da Acurácia Posicional de Sensor LiDAR Incorporado em Smartphones
DOI:
https://doi.org/10.26848/rbgf.v18.2.p1247-1262Keywords:
LiDAR, Dispositivos móveis, Acurácia, Nuvem de pontos, Engenharia e GeociênciasAbstract
Recently, Apple Inc. introduced mobile devices with built-in LiDAR sensors. These devices can offer an economical and versatile alternative, overcoming some of the limitations of traditional LiDAR-based systems. In this context, this study evaluated the accuracy of point clouds generated by smartphones with integrated LiDAR technology. The methodology involved analyzing the three-dimensional coordinates of points of interest in the point cloud with the three-dimensional coordinates of the same points surveyed using a total station. Numerical tests demonstrated consistency in the coordinates, with absolute discrepancies below 8.5 cm and a normal distribution of discrepancies around the mean. The average accuracy of the points was 2 cm, with most points showing precision between 1.6 cm and 2.5 cm. These results indicate that mobile devices equipped with LiDAR can produce digital terrain models with sufficient accuracy for most engineering and geoscience applications, providing an affordable and convenient alternative to topographic laser scanner surveys.
Downloads
References
Apple Inc. (2021). iPhone 13 Pro Max - Especificações técnicas - Suporte da Apple (BR). Apple Support. https://support.apple.com/kb/SP848?locale=pt_BR
Błaszczak-Bąk, W., Janicka, J., Dumalski, A., & Masiero, A. (2023). Integration of terrestrial laser scanning and smartphone LiDAR: The case study of Lidzbark Castle. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 48, 51–56. https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-51-2023
Gonçalves, E. M., Albarici, F. L., Oliveira, H. C. de, & Reberte, J. C. B. (2024). Análise do registro de nuvens de pontos obtidas por SVLT e por VANT para aplicação no cadastro territorial multifinalitário. Revista Brasileira de Cartografia, 76, Article 70655. https://doi.org/10.14393/rbcv76n0a-70655
Luz Melo, L. F., de Melo Fagundes, L. J., de Melo Torres, M. T. G., de Araujo, M. S., de Oliveira, J. E. F., Soares, A. M. F., ... & de Oliveira, S. T. (2021). Estudo aplicado ao software ACIC Normalidade 2.0. Brazilian Journal of Development, 7(5), 45014–45038. https://doi.org/10.34117/bjdv.v7i5.29354.
Geosystems. (2023). Estação total manual Leica FlexLine TS03. Leica-Geosystems.com. https://leica-geosystems.com/pt-br/products/total-stations/manual-total-stations/leica-flexline-ts03
Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., & Nothdurft, A. (2021). Measurement of forest inventory parameters with Apple iPad Pro and integrated LiDAR technology. Remote Sensing, 13(16). https://doi.org/10.3390/rs13163129
Hakim, N. N. A. N. A., Razali, R., Mohd Said, M. S., Muhamad, M. A. H., Abdul Rahim, H., & Mokhtar, M. A. (2023). Accuracy assessment on detail survey plan using iPhone 13 Pro Max LiDAR sensor. International Journal of Geoinformatics, 19, 79–86. https://doi.org/10.52939/ijg.v19i5.2665
King, F., Kelly, R., & Fletcher, C. G. (2022). Evaluation of LiDAR-derived snow depth estimates from the iPhone 12 Pro. IEEE Geoscience and Remote Sensing Letters, 19, 1–5. https://doi.org/10.1109/lgrs.2022.3166665
Kottner, S., Thali, M. J., & Gascho, D. (2023). Using the iPhone’s LiDAR technology to capture 3D forensic data at crime and crash scenes. Forensic Imaging, 32, 200535. https://doi.org/10.1016/j.fri.2023.200535
Luetzenburg, G., Kroon, A., & Bjørk, A. A. (2021). Evaluation of the Apple iPhone 12 Pro LiDAR for an application in geosciences. Scientific Reports, 11, 22221. https://doi.org/10.1038/s41598-021-01763-9
Mikita, T., Krausková, D., Hrůza, P., Cibulka, M., & Patočka, Z. (2022). Forest road wearing course damage assessment possibilities with different types of laser scanning methods including new iPhone LiDAR scanning apps. Forests, 13(11), 1763. https://doi.org/10.3390/f13111763
Murtiyoso, A., & Grussenmeyer, P. (2021). Experiments using smartphone-based videogrammetry for low-cost cultural heritage documentation. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 46(M-1–2021). https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-487-2021
MundoGeo. (2022). Matterport Axis, MC250 Pro2 Câmera e MC300 Pro3 Laser Scanner. Www.youtube.com. https://youtu.be/d79hk2NQtvY
Oliveira, P. H. S. M., Albarici, F. L., de Oliveira, H. C., & Ribeiro, L. H. R. (2021). Análise da integração de nuvens de pontos obtidas por varredura LASER terrestre estática e varredura de luz estruturada cinemática. Revista Brasileira de Geomática, 9(4), 273-293. https://doi.org/10.3895/rbgeo.v9n4.13601
Ren, Y., Dai, Z., Lu, P., Ai, C., Huang, Y., & Tolliver, D. (2022). Rail gage-based risk detection using iPhone 12 Pro. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 237(4), 429–437. https://doi.org/10.1177/09544097221093753
Rutkowski, W., & Lipecki, T. (2023). Use of the iPhone 13 Pro LiDAR Scanner for inspection and measurement in the mineshaft sinking process. Remote Sensing, 15(21), 5089. https://doi.org/10.3390/rs15215089
Tatsumi, S., Yamaguchi, K., & Furuya, N. (2022). ForestScanner: A mobile application for measuring and mapping trees with LiDAR-equipped iPhone and iPad. Methods in Ecology and Evolution, 14(8), 1603–1609. https://doi.org/10.1111/2041-210x.14009
D Scanner App. (2024). 3D Scanner App. 3dScannerapp.com. https://3dScannerapp.com
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Enrico Moreira Gonçalves, Fabio Luiz Albarici
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Revista Brasileira de Geografia Física agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted to make their work available online before or during the editorial process, on academic social networks, digital repositories, or preprint servers. After publication in Revista Brasileira de Geografia Física, authors are expected to update the preprint or postprint versions on the platforms where they were originally made available, providing a link to the final published version and any other relevant information, with proper recognition of authorship and the initial publication in this journal.
You are free to:
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
