UAV photogrammetry for riverine analysis: A systematic review of methodologies, accuracy, and challenges
DOI:
https://doi.org/10.58524/jgsa.v2i2.115Keywords:
Digital Elevation Model, Hydraulic Modeling, Riverine Environments, Systematic Review, UAV PhotogrammetryAbstract
High-resolution spatial data is crucial for riverine modeling and flood mitigation. Traditional data often lacks necessary resolution or flexibility, making Unmanned Aerial Vehicles (UAVs) a transformative solution for generating precise Digital Elevation Models (DEMs). This systematic review analyzes 65 peer-reviewed studies published between 2014 and 2025. Following PRISMA guidelines, studies were selected based on specific inclusion and exclusion criteria focusing on riverine hydraulic applications to evaluate data acquisition methods, spatial accuracy, and operational challenges. The synthesis reveals a standard workflow using multirotor platforms, Structure from Motion (SfM) photogrammetry, and Ground Control Points (GCPs) to feed hydrodynamic models like HEC-RAS. While the literature consistently reports centimeter-level vertical accuracy—ideal for mapping flood inundation—critical challenges persist regarding the optical penetration of dense vegetation and submerged bathymetry. Ultimately, while UAV photogrammetry is a robust spatial analysis tool, advancing high-fidelity riverine analytics requires hybrid approaches integrating technologies like UAV-borne LiDAR and sonar. Creating these seamless topobathymetric models is essential for improving reliable flood risk management and informing effective environmental policy.
Downloads
References
Acharya, B. S., Bhandari, M., Bandini, F., Pizarro, A., Perks, M., Joshi, D. R., Wang, S., Dogwiler, T., Ray, R. L., Kharel, G., & Sharma, S. (2021). Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives. Water Resources Research, 57(11), Article 11. https://doi.org/10.1029/2021WR029925
Amatebelle, C. E., Owolabi, S. T., Ogundeji, A. A., & Okolie, C. C. (2025). A systematic analysis of remote sensing and geographic information system applications for flood disaster risk management. Journal of Spatial Science, 1–27. https://doi.org/10.1080/14498596.2025.2476973
Annis, A., Nardi, F., Petroselli, A., Apollonio, C., Arcangeletti, E., Tauro, F., Belli, C., Bianconi, R., & Grimaldi, S. (2020). UAV-DEMs for Small-Scale Flood Hazard Mapping. Water, 12(6), Article 6. https://doi.org/10.3390/w12061717
Bandini, F., Jakobsen, J., Olesen, D., Reyna-Gutierrez, J. A., & Bauer-Gottwein, P. (2017). Measuring water level in rivers and lakes from lightweight Unmanned Aerial Vehicles. Journal of Hydrology, 548, 237–250. https://doi.org/10.1016/j.jhydrol.2017.02.038
Clasing, R., Muñoz, E., Arumí, J. L., Caamaño, D., Alcayaga, H., & Medina, Y. (2023). Remote Sensing with UAVs for Modeling Floods: An Exploratory Approach Based on Three Chilean Rivers. Water, 15(8), 1502. https://doi.org/10.3390/w15081502
Dietrich, J. T. (2017). Bathymetric Structure‐from‐Motion: Extracting shallow stream bathymetry from multi‐view stereo photogrammetry. Earth Surface Processes and Landforms, 42(2), 355–364. https://doi.org/10.1002/esp.4060
Eltner, A., Kaiser, A., Castillo, C., Rock, G., Neugirg, F., & Abellán, A. (2016). Image-based surface reconstruction in geomorphometry – merits, limits and developments. Earth Surface Dynamics, 4(2), 359–389. https://doi.org/10.5194/esurf-4-359-2016
Famiglietti, N. A., Cecere, G., Grasso, C., Memmolo, A., & Vicari, A. (2021). A Test on the Potential of a Low Cost Unmanned Aerial Vehicle RTK/PPK Solution for Precision Positioning. Sensors, 21(11), 3882. https://doi.org/10.3390/s21113882
Flener, C., Vaaja, M., Jaakkola, A., Krooks, A., Kaartinen, H., Kukko, A., Kasvi, E., Hyyppä, H., Hyyppä, J., & Alho, P. (2013). Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography. Remote Sensing, 5(12), 6382–6407. https://doi.org/10.3390/rs5126382
Hakim, D. K., Gernowo, R., & Nirwansyah, A. W. (2024). Flood prediction with time series data mining: Systematic review. Natural Hazards Research, 4(2), 194–220. https://doi.org/10.1016/j.nhres.2023.10.001
Hoogendoorn, N. (2023). 3D River Discharge Modelling using UAV photogrammetry.
James, M. R., Robson, S., d’Oleire-Oltmanns, S., & Niethammer, U. (2017). Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment. Geomorphology, 280, 51–66. https://doi.org/10.1016/j.geomorph.2016.11.021
Javernick, L., Brasington, J., & Caruso, B. (2014). Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry. Geomorphology, 213, 166–182. https://doi.org/10.1016/j.geomorph.2014.01.006
Kuhn, J., Casas-Mulet, R., Pander, J., & Geist, J. (2021). Assessing Stream Thermal Heterogeneity and Cold-Water Patches from UAV-Based Imagery: A Matter of Classification Methods and Metrics. Remote Sensing, 13(7), 1379. https://doi.org/10.3390/rs13071379
Luppichini, M., Favalli, M., Isola, I., Nannipieri, L., Giannecchini, R., & Bini, M. (2019). Influence of Topographic Resolution and Accuracy on Hydraulic Channel Flow Simulations: Case Study of the Versilia River (Italy). Remote Sensing, 11(13), 1630. https://doi.org/10.3390/rs11131630
Mazzoleni, M., Paron, P., Reali, A., Juizo, D., Manane, J., & Brandimarte, L. (2020). Testing UAV-derived topography for hydraulic modelling in a tropical environment. Natural Hazards, 103(1), 139–163. https://doi.org/10.1007/s11069-020-03963-4
Mensah, J. K., Ofosu, E. A., Yidana, S. M., Akpoti, K., & Kabo-bah, A. T. (2022). Integrated modeling of hydrological processes and groundwater recharge based on land use land cover, and climate changes: A systematic review. Environmental Advances, 8, 100224. https://doi.org/10.1016/j.envadv.2022.100224
Odey, G., & Cho, Y. (2025). Event-Based vs. Continuous Hydrological Modeling with HEC-HMS: A Review of Use Cases, Methodologies, and Performance Metrics. Hydrology, 12(2), 39. https://doi.org/10.3390/hydrology12020039
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021a). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021b). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71
Reali, Andrea. (2018). Potentialities of Unmanned Aerial Vehicles in Hydraulic Modelling: Drone remote sensing through photogrammetry for 1D flow numerical modelling. KTH.
Rezvani, S. M., Falcão, M. J., Komljenovic, D., & De Almeida, N. M. (2023). A Systematic Literature Review on Urban Resilience Enabled with Asset and Disaster Risk Management Approaches and GIS-Based Decision Support Tools. Applied Sciences, 13(4), 2223. https://doi.org/10.3390/app13042223
Tauro, F., Selker, J., Van De Giesen, N., Abrate, T., Uijlenhoet, R., Porfiri, M., Manfreda, S., Caylor, K., Moramarco, T., Benveniste, J., Ciraolo, G., Estes, L., Domeneghetti, A., Perks, M. T., Corbari, C., Rabiei, E., Ravazzani, G., Bogena, H., Harfouche, A., … Grimaldi, S. (2018). Measurements and Observations in the XXI century (MOXXI): Innovation and multi-disciplinarity to sense the hydrological cycle. Hydrological Sciences Journal, 63(2), 169–196. https://doi.org/10.1080/02626667.2017.1420191
Vélez-Nicolás, M., García-López, S., Barbero, L., Ruiz-Ortiz, V., & Sánchez-Bellón, Á. (2021). Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review. Remote Sensing, 13(7), 1359. https://doi.org/10.3390/rs13071359
Wallace, L., Lucieer, A., Malenovský, Z., Turner, D., & Vopěnka, P. (2016). Assessment of Forest Structure Using Two UAV Techniques: A Comparison of Airborne Laser Scanning and Structure from Motion (SfM) Point Clouds. Forests, 7(3), 62. https://doi.org/10.3390/f7030062
Woodget, A. S., Carbonneau, P. E., Visser, F., & Maddock, I. P. (2015). Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry. Earth Surface Processes and Landforms, 40(1), 47–64. https://doi.org/10.1002/esp.3613
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Nabil Muhamad, Yassir Arafat, Alifi Yunar (Author)

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

