Use of Unmanned Aerial Vehicle as an Alternative to Generate Topographic Information
Unmanned Aerial Vehicle for topographic
DOI:
https://doi.org/10.29019/enfoqueute.881Keywords:
EBEE SQ, PIX4D, DTM, georeferencing, photogrammetry, 3D point cloud.Abstract
Unmanned Aerial Vehicles (UAVs) are becoming a very versatile technology tool in several application areas for development activities. Topography, as a fundamental area of engineering, provides information related to the three-dimensional location of points on the earth's surface. The objective of this work was to generate topographic information, using UAV as a technological alternative to traditional techniques. The methodology consisted of planning and execution of two photogrammetric flights with the EBEB SQ UAV, instrumented with the Sequoia multispectral camera. Five control points were placed on the ground, georeferenced with a total station, used as control points in the processing of the flight images. The photographs captured in flight were processed by photogrammetry with PIX4Dmapper software on a desktop computer, with an Intel(R) Core (TM) i9-9900K CPU 3.60GHz processor and 32.0 GB of RAM. The photogrammetric flight results consisted of a total of 633 RGB photographs in a flight time of 36:27 minutes, for a coverage area of 57.7 ha. The processing quality report showed an accuracy of 2 mm in the georeferencing of the photographs with the control points. The photogrammetric processing was executed in a time of 48 minutes to generate Orthophotos, Digital Terrain Model (DTM) and three-dimensional point cloud. The generated products reached a spatial resolution of 5 cm/pixel, with millimeter accuracies that allowed the management of secondary topographic information such as slope. The point cloud made it possible to classify the coverage in vegetation and soil, to estimate the height of the cotton crop canopy with an accuracy of 91%. As advantages of the UAV over traditional techniques for topographic surveys, the variety and precision of geospatial products and the optimization of times can be highlighted.
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References
Carrivick, J. L., Smith, M. W. y Quincey, D. J. (2016). Structure from Motion in the Geosciences. John Wiley & Sons, 73(2), 1445-146. https://doi.org/10.1111/nzg.12161
Cevallos, M. R., y L. Shkiliova. 2018. Desarrollo del programa “Mecanización agrícola comunitaria” en la provincia de Manabí, República de Ecuador. Revista Ingeniería Agrícola, 6(2), 45-50. https://cutt.ly/jQMFlMC
Dai, W., Qian, W., Liu, A., Wang, C., Yang, X., Hu, G. y Tang, G. (2022). Monitoring and modeling sediment transport in space in small loess catchments using UAV-SfM photogrammetry. CATENA, 214, 106244. https://doi.org/10.1016/j.catena.2022.106244
Gómez-Gutiérrez, Á., y Gonçalves, G. R. (2020). Surveying coastal cliffs using two UAV platforms (multirotor and fixed-wing) and three different approaches for the estimation of volumetric changes. International Journal of Remote Sensing, 41(21), 8143-8175. https://doi.org/10.1080/01431161.2020.1752950
Gürtekin, E., y Gökçe, O. (2021). Estimation of erosion risk of Harebakayiş sub-watershed, Elazig, Turkey, using GIS based RUSLE model. Environmental Challenges, 5, 100315. https://doi.org/10.1016/j.envc.2021.100315
Herrero, M. J., Pérez-Fortes, A. P., Escavy, J. I., Insua-Arévalo, J. M., De la Horra, R., López-Acevedo, F. y Trigos, L. (2022). 3D model generated from UAV photogrammetry and semi-automated rock mass characterization. Computers & Geosciences, 163, 105121. https://doi.org/10.1016/j.cageo.2022.105121
Huang, G., Lv, G., Zhang, S., Huang, D., Zhao, L., Ni, X.,... y Liu, C. (2022). Numerical analysis of debris flows along the Sichuan-Tibet railway based on an improved 3D sphere DDA model and UAV-based photogrammetry. Engineering Geology, 106722. https://doi.org/10.1016/j.enggeo.2022.106722
James, M. R. y Robson, S. (2012). Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. Journal of Geophysical Research: Earth Surface, 117(F3). https://doi.org/10.1029/2011JF002289
Liu, Y., Fu, Y., Zhou, P., Zhuan, Y., Zhong, K. y Guan, B. (2020). A real-time 3D shape measurement with color texture using a monochromatic camera. Optics Communications, 474, 126088. https://doi.org/10.1016/j.optcom.2020.126088
Lopes Bento, N., Araújo E Silva Ferraz, G., Alexandre Pena Barata, R., Santos Santana, L., Diennevan Souza Barbosa, B., Conti, L. y Rossi, G. (2022). Overlap influence in images obtained by an unmanned aerial vehicle on a digital terrain model of altimetric precision. European Journal of Remote Sensing, 55(1), 263-276. https://doi.org/10.1080/22797254.2022.2054028
Lu, J., Cheng, D., Geng, C., Zhang, Z., Xiang, Y. y Hu, T. (2021). Combining plant height, canopy coverage and vegetation index from UAV-based RGB images to estimate leaf nitrogen concentration of summer maize. Biosystems Engineering, 202, 42-54. https://doi.org/10.1016/j.biosystemseng.2020.11.010
Malamiri, H. R. G., Aliabad, F. A., Shojaei, S., Morad, M. y Band, S. S. (2021). A study on the use of UAV images to improve the separation accuracy of agricultural land areas. Computers and Electronics in Agriculture, 184, 106079. https://doi.org/10.1016/j.compag.2021.106079
Martínez-Carricondo, P., Agüera-Vega, F. y Carvajal-Ramírez, F. (2020). Use of UAV-photogrammetry for quasi-vertical wall surveying. Remote Sensing, 12(14), 2221. https://doi.org/10.3390/rs12142221
Meinen, B. U., y Robinson, D. T. (2020). Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS. Remote Sensing of Environment, 239, 111666. https://doi.org/10.1016/j.rse.2020.111666
Mello, C. C. de Sousa, Salim, D. H. C. y Simões, G. F. (2022). UAV-based landfill operation monitoring: A year of volume and topographic measurements. Waste Management, 137, 253-263. https://doi.org/10.1016/j.wasman.2021.11.020
Mesas-Carrascosa, F. J., de Castro, A. I., Torres-Sánchez, J., Triviño-Tarradas, P., Jiménez-Brenes, F. M., García-Ferrer, A. y López-Granados, F. (2020). Classification of 3D point clouds using color vegetation indices for precision viticulture and digitizing applications. Remote Sensing, 12(2), 317. https://doi.org/10.3390/rs12020317
Nesbit, P. R., Hubbard, S. M. y Hugenholtz, C. H. (2022). Direct Georeferencing UAV-SFM in High-Relief Topography: Accuracy Assessment and Alternative Ground Control Strategies Along Steep Inaccessible Rock Slopes. Remote Sensing, 14(3), 490. https://doi.org/10.3390/rs14030490
Nesbit, P. R., Hubbard, S. M., Daniels, B. G., Bell, D., Englert, R. G. y Hugenholtz, C. H. (2021). Digital re‐evaluation of down‐dip channel‐fill architecture in deep‐water slope deposits: Multi‐scale perspectives from UAV‐SfM. The Depositional Record, 7(3), 480-499. https://doi.org/10.1002/dep2.137
Pacheco Gil, H. A. (2012). Modelos digitales del terreno, variables hidrológicas y movimientos en masa, estado Vargas, Venezuela. Geoenseñanza, 17(1), 57-75. http://www.saber.ula.ve/handle/123456789/40243
Parizi, E., Khojeh, S., Hosseini, S. M. y Moghadam, Y. J. (2022). Application of Unmanned Aerial Vehicle DEM in flood modeling and comparison with global DEMs: Case study of Atrak River Basin, Iran. Journal of Environmental Management, 317, 115492. https://doi.org/10.1016/j.jenvman.2022.115492
Štroner, M., Urban, R., Reindl, T., Seidl, J. y Brouček, J. (2020). Evaluation of the georeferencing accuracy of a photogrammetric model using a quadrocopter with onboard GNSS RTK. Sensors, 20(8), 2318. https://doi.org/10.3390/s20082318
Teppati Losè, L., Chiabrando, F. y Giulio Tonolo, F. (2020). Are measured ground control points still required in UAV based large scale mapping? Assessing the positional accuracy of an RTK multi-rotor platform. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences. https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B1-2020/507/2020/
Tonkin, T. N., y 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), 786. https://doi.org/10.3390/rs8090786
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J. y Reynolds, J. M. (2012). ‘Structure-From-Motion’photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology, 179, 300-314. https://doi.org/10.1016/j.geomorph.2012.08.021
Whelan, B. M., y McBratney, A. B. (2000). The “null hypothesis” of precision agriculture management. Precision Agriculture, 2(3), 265-279. https://link.springer.com/article/10.1023/A:1011838806489
Wright, D., Dering, B., Martinovic, J. y Gheorghiu, E. (2020). Neural responses to dynamic adaptation reveal the dissociation between the processing of the shape of contours and textures. Cortex, 127, 78-93. https://doi.org/10.1016/j.cortex.2020.01.015
Wu, B., Liu, W. C., Grumpe, A. y Wöhler, C. (2018). Construction of pixel-level resolution DEMs from monocular images by shape and albedo from shading constrained with low-resolution DEM. ISPRS journal of photogrammetry and remote sensing, 140, 3-19. https://doi.org/10.1016/j.isprsjprs.2017.03.007
Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X. y Yan, G. (2016). An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote sensing, 8(6), 501. https://doi.org/10.3390/rs8060501
Zhang, J., Xu, S., Zhao, Y., Sun, J., Xu, S. y Zhang, X. (2023). Aerial orthoimage generation for UAV remote sensing. Information Fusion, 89, 91-120. https://doi.org/10.1016/j.inffus.2022.08.007
Zolkepli, M. F., Ishak, M. F., Yunus, M. Y. M., Zaini, M. S. I., Wahap, M. S., Yasin, A. M., ... y Hezmi, M. A. (2021). Application of unmanned aerial vehicle (UAV) for slope mapping at Pahang Matriculation College, Malaysia. Physics and Chemistry of the Earth, Parts A/B/C, 123, 103003. https://doi.org/10.1016/j.pce.2021.103003
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