Authors :
Umar Yusuf; Ibrahim Musa; Waheed Adeyemi; Umar Zulkifil Usman
Volume/Issue :
Volume 10 - 2025, Issue 9 - September
Google Scholar :
https://tinyurl.com/h6c8z9hj
Scribd :
https://tinyurl.com/ynvt7m7t
DOI :
https://doi.org/10.38124/ijisrt/25sep986
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
Aerial photogrammetry has been around long before Unmanned Aerial Vehicle (UAV) and more specifically the
drones. Drone photogrammetry has made the accurate creation of 2D maps and 3D models of physical landscapes faster
and less expensive, putting it within reach of the budgets of many more users and organizations. It has emerged as a
powerful tool for capturing high-resolution aerial imagery to create accurate maps and detailed models. To ensure that the
resolution and data density of the output files are adequate, drones must fly based on a previously planned scheme, and
then take pictures at specified distances or intervals along the route with predefined overlaps. The photos taken in this way
will be suitable for creating maps and models. This study aims to use Mission Planner oftware (MPS) version 1.3.82 to
plan and create an effective flight route for drone photogrammetry survey over the vast land of the Federal Polytechnic
Nasarawa, Tammah campus. The methodology utilizes thirty-one (31) drone payload of passive optical sensors (RGB
photogrammetry cameras) available in MPS. The study used properties of ten different RGB cameras with 500m altitude,
80% and 70% for forward and sideward overlap respectively. Results showed that camera “Canon EOS 5D Mark II”
produces the most efficient flight mission plan with 54 photographs, 7 number of strips, 40.00 seconds stop spots and flight
time of 1:03:57 hours. The integration of systematic planning methodologies with advanced software tools like Mission
Planner enables the creation of highly effective flight route plans that deliver survey-grade photogrammetric products.
Keywords :
Flight Route Planning, Drone Photogrammetry Survey, Mission Planner, Unmanned Aerial Vehicle, Aerial Photogrammetry.
References :
- Aerotas. (2023). Linear mission planning: Best practices for GCP placement. Aerotas.com. Hsieh, P.-Y., et al. (2022). Contour mission planning for UAV photogrammetry. Applied Sciences, 12(3), 1134.
- ArduPilot Development Team, (2024). MissionPlanner Documentation, ArduPilot. Available: https://ardupilot.org/planner/
- Ardupilot, 2015. ArduPilot. Open-source auto pilot, http://ardupilot.com/.
- Colomina, I., Molina, P., 2014. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry & Remote Sensing 92, 79–97.
- EASA European Aviation Safety Agency, 2015. Unmanned Aircraft Systems (UAS) and Remotely Piloted Aircraft Systems (RPAS), https://easa.europa.eu/unmanned-aircraft-systems-uas- and-remotely-piloted-aircraft-systems-rpas (accessed 1.7.15).
- Ey-Chmielewska, H., Chruściel-Nogalska, M., & Frączak, B. (2015). Photogrammetry and its potential application in medical science on the basis of selected literature. Adv Clin Exp Med, 24(4), 737-41.
- HiSystems, 2015. Mikrokopter-Tool OSD. HiSystems GmbH, Germany.
- Jiang, S., Jiang, W., & Wang, L. (2021). Unmanned Aerial Vehicle-Based Photogrammetric 3D Mapping: A survey of techniques, applications, and challenges. IEEE Geoscience and Remote Sensing Magazine, 10(2), 135-171.
- Leica, 2012. MissionPro. Leica Geosystems, http://www.leica- geosystems.com/en/Leica-MissionPro_98219.htm.
- Maboudi, M., et al. (2022). UAV viewpoint selection and path planning for large-scale 3D reconstruction. ArXiv preprint arXiv:2205.03716.
- MAVinci, 2015. MAVinci Desktop. MAVinci GmbH, Germany, http://www.mavinci.de/en/completesys/desktop.
- Meier, L., 2010. QGroundControl, http://qgroundcontrol.org/. Microdrones, 2015. mdCockpit. Microdrones GmbH, Germany.
- Oborne, M., 2015. Mission Planner, http://planner.ardupilot.com.
- Panda, S. S., Rao, M. N., Thenkabail, P. S., Misra, D., & Fitzgerald, J. P. (2016). Remote Sensing Systems—Platforms and Sensors: Aerial, Satellite, UAV, Optical, Radar, and LiDAR. In Remote Sensing Handbook, Volume I (pp. 3-86). CRC Press.
- Pepe, M., Fregonese, L., & Scaioni, M. (2018). Planning airborne photogrammetry and remote-sensing missions with modern platforms and sensors. European Journal of Remote Sensing, 51(1), 412-436.
- Pix4D. (2023). Image acquisition guidelines for UAV photogrammetry. Pix4D.com. UgCS. (2023). Photogrammetry tool for UAV land surveying missions. UgCS documentation.
- Schaer, P., Skaloud, J., 2007. ALS Mission Planner. EPFL internal software.
- senseFly, 2015. eMotion. senseFly, Switzerland, https://www.sensefly.com/drones/emotion.html.
- SPH Engineering, 2015. Universal Ground Control Station (UgCS). SPH Engineering, Latvia, http://www.ugcs.com/en/.
- Yang, C., Westbrook, J. K., Suh, C. P. C., Martin, D. E., Hoffmann, W. C., Lan, Y., ... & Goolsby, J. A. (2014). An airborne multispectral imaging system based on two consumer-grade cameras for agricultural remote sensing. Remote Sensing, 6(6), 5257-5278.
- Zacc Dukowitz, (2025). Drone Photogrammetry: An In-Depth Guide. UAVCoach. Available: https://uavcoach.com/drone-photogrammetry
- Zhang, H. (2024). UAV path planning algorithms: A comparative review. Proceedings of ACE Conference, 9980.
Aerial photogrammetry has been around long before Unmanned Aerial Vehicle (UAV) and more specifically the
drones. Drone photogrammetry has made the accurate creation of 2D maps and 3D models of physical landscapes faster
and less expensive, putting it within reach of the budgets of many more users and organizations. It has emerged as a
powerful tool for capturing high-resolution aerial imagery to create accurate maps and detailed models. To ensure that the
resolution and data density of the output files are adequate, drones must fly based on a previously planned scheme, and
then take pictures at specified distances or intervals along the route with predefined overlaps. The photos taken in this way
will be suitable for creating maps and models. This study aims to use Mission Planner oftware (MPS) version 1.3.82 to
plan and create an effective flight route for drone photogrammetry survey over the vast land of the Federal Polytechnic
Nasarawa, Tammah campus. The methodology utilizes thirty-one (31) drone payload of passive optical sensors (RGB
photogrammetry cameras) available in MPS. The study used properties of ten different RGB cameras with 500m altitude,
80% and 70% for forward and sideward overlap respectively. Results showed that camera “Canon EOS 5D Mark II”
produces the most efficient flight mission plan with 54 photographs, 7 number of strips, 40.00 seconds stop spots and flight
time of 1:03:57 hours. The integration of systematic planning methodologies with advanced software tools like Mission
Planner enables the creation of highly effective flight route plans that deliver survey-grade photogrammetric products.
Keywords :
Flight Route Planning, Drone Photogrammetry Survey, Mission Planner, Unmanned Aerial Vehicle, Aerial Photogrammetry.