Low Altitude Photogrammetry for Urban Road Mapping

Authors

  • Shahrul Nizan Abd Mukti Dewan Bandaraya Kuala Lumpur (DBKL), Department of Infrastructure Planning, Level 10 North, Menara DBKL 2, Jalan Raja Laut, 50350 Kuala Lumpur
  • Khairul Nizam Tahar Centre of Studies for Surveying and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, 40450 Shah Alam, Selangor Darul Ehsan, Malaysia.

Keywords:

Road, Mapping, UAV, 3D Reconstruction, Flight Parameter

Abstract

To manage road over the country, geometry data of road is needed for decision making and project well management. The primary data is usually contributed by field technical support persons, such as surveyor, engineer, and others for conventional method of survey. For the sake of life safety, a study aims to carry out mapping work with unmanned aerial vehicle (UAV) platform and photogrammetry-based method. This study proposed an urban road mapping with optimal flight parameter, sensor parameter and GCP distribution by flying low for detail texture acquisition of road. The primary product of photogrammetry based is accurate digital orthophoto model (DOM) and digital elevation model (DEM). The flight parameters, sensor/image parameter of unmanned aerial vehicle (UAV) including focal length effectiveness (10.26mm and 3.61mm), image end lap percentage (90%, 80%, and 70%), Ground Scale distance (GSD) (3cm, 2cm, and 1cm), and ground control point (GCP) distribution setup (pyramid square-, square-, and linear-based networks) were outlined. In this study it was found that longest focal length 10.26mm is suitable for road mapping. 70% end lap with 1cm GSD or 25m altitude is the best parameter. By increased and well distribute GCP over the project area, accuracy increased by 1% of position. Optimal network of GCP is pyramid based network. Photogrammetry-based mapping was an accurate method for detail road mapping by proposed result above.

References

Howell, R., Jensen, R., Petersen, S., & Larsen, R. (2020). Measuring Height Characteristics of Sagebrush (Artemisia sp.) Using Imagery Derived from Small Unmanned Aerial Systems (sUAS). Drones, 4(1), 6. https://doi.org/10.3390/drones4010006

Junqing, C., Zongjian, L., Xiaojing, W., & Yongrong, L. (2012). Application of Uav System for Low Altitude Photogrammetry in Shanxi. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B1(September), 351–354. https://doi.org/10.5194/isprsarchives-xxxix-b1-351-2012

Li, D., & Li, M. (2014). Research advance and application prospect of unmanned aerial vehicle remote sensing system. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 39(5). https://doi.org/10.13203/j.whugis20140045

Saad, A. M., & Tahar, K. N. (2019). Identification of rut and pothole by using multirotor unmanned aerial vehicle (UAV). Measurement: Journal of the International Measurement Confederation, 137, 647–654. https://doi.org/10.1016/j.measurement.2019.01.093

Saberioon, M. M., & Gholizadeh, A. (2016). Novel approach for estimating nitrogen content in paddy fields using low altitude remote sensing system. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2016-Janua(July), 1011–1015. https://doi.org/10.5194/isprsarchives-XLI-B1-1011-2016

Sanz-Ablanedo, E., Chandler, J. H., Rodríguez-Pérez, J. R., & Ordóñez, C. (2018). Accuracy of Unmanned Aerial Vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used. Remote Sensing, 10(10). https://doi.org/10.3390/rs10101606

Seifert, E., Seifert, S., Vogt, H., Drew, D., van Aardt, J., Kunneke, A., & Seifert, T. (2019). Influence of drone altitude, image overlap, and optical sensor resolution on multi-view reconstruction of forest images. Remote Sensing, 11(10). https://doi.org/10.3390/rs11101252

Tahar, K.N. (2013). AN EVALUATION ON DIFFERENT NUMBER OF GROUND CONTROL POINTS IN UNMANNED AERIAL VEHICLE PHOTOGRAMMETRIC BLOCK. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-2/W2, ISPRS 8th 3DGeoInfo Conference & WG II/2 Workshop, 27 – 29 November 2013, Istanbul, Turkey, XL(November), 27–29.

Tahar, Khairul Nizam, & Ahmad, A. (2013). Production of orthophoto and volume determination using low-cost digital cameras. Pertanika Journal of Science and Technology, 21(2), 387–396.

Tonkin, T. N., & Midgley, N. G. (2016). Ground-control networks for image based surface reconstruction: An investigation of optimum survey designs using UAV derived imagery and structure-from-motion photogrammetry. Remote Sensing, 8(9), 16–19. https://doi.org/10.3390/rs8090786

Tsouros, D. C., Bibi, S., & Sarigiannidis, P. G. (2019). A review on UAV-based applications for precision agriculture. Information (Switzerland), 10(11). https://doi.org/10.3390/info10110349

Zhang, Y., Xiong, J., & Hao, L. (2011). Photogrammetric processing of low-altitude images acquired by unpiloted aerial vehicles. Photogrammetric Record, 26(134), 190–211. https://doi.org/10.1111/j.1477-9730.2011.00641.x

Downloads

Published

28-08-2025

How to Cite

Abd Mukti, S. N. ., & Tahar, K. N. . (2025). Low Altitude Photogrammetry for Urban Road Mapping. Built Environment Journal, 18(1). Retrieved from https://journal.uitm.edu.my/ojs/index.php/BEJ/article/view/8627

Issue

Vol. 18 No. 1 (2021): Built Environment Journal

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

CC BY-NC-ND 4.0 DEED

Attribution-NonCommercial-NoDerivs 4.0 International