Análisis comparativo del levantamiento del terreno mediante UAS y topografía clásica en proyectos de trazado de carreteras

Autores/as

DOI:

https://doi.org/10.3989/ic.86273

Palabras clave:

UAS, SfM, MVS, líneas de rotura, eliminación de ruido, precisión, MDT

Resumen


La incorporación de vehículos aéreos no tripulados (UAS) como alternativa a los levantamientos topográficos clásicos ha experimentado en estos últimos años un gran avance en todos los ámbitos de la ingeniería, dado que permiten una rápida y eficaz generación de diferentes productos fotogramétricos (nube de puntos, modelo digital del terreno, ortofotos), a la vez que favorecen una reducción de los costes. Para demostrar las posibilidades que nos ofrecen los UAS en el ámbito de la ingeniería civil, se presenta aquí un estudio en el que se comparan los resultados obtenidos entre un levantamiento topográfico clásico y otro efectuado con estos medios aéreos, que será la base topográfica que permita realizar el proyecto de construcción de una carretera. Los resultados experimentales revelan que el uso combinado de datos UAS y topografía clásica proporcionan una generación exitosa de los productos.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

(1) Nex, F., Remondino, F. (2014). UAV for 3D mapping applications: a review. Applied geomatics, 6(1): 1-15.

(2) Trujillo, M.M., Darrah, M., Speransky, K., DeRoos, B., Wathen, M. (2016). Optimized flight path for 3D mapping of an area with structures using a multirotor. In 2016 International Conference on Unmanned Aircraft Systems (ICUAS), 7-10: 905-910. Arlington (USA): IEEE.

(3) Chaudhry, M.H., Ahmad, A., Gulzar, Q. (2020). A comparative study of modern UAV platform for topographic mapping. In IOP Conference Series: Earth and Environmental Science, 540(1): 012019. IOP Publishing.

(4) Kraaijenbrink, P.D.A., Shea, J.M., Pellicciotti, F., Jong, S.M. de Immerzeel, W.W. (2016). Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. Remote Sensing of Environment, 186: 581-595.

(5) Rossini, M., Di Mauro, B., Garzonio, R., Baccolo, G., Cavallini, G., Mattavelli, M., Colombo, R. (2018). Rapid melting dynamics of an alpine glacier with repeated UAV photogrammetry. Geomorphology, 304: 159-172.

(6) Chang, K.J., Tseng, C.W., Tseng, C.M., Liao, T.C., Yang, C.J. (2020). Application of Unmanned Aerial Vehicle (UAV)-Acquired Topography for Quantifying Typhoon-Driven Landslide Volume and Its Potential Topographic Impact on Rivers in Mountainous Catchments. Applied Sciences, 10(17):6102.

(7) Yuan, X., Qiao, G., Li, Y., Li, H., Xu, R. (2020). Modelling of Glacier and Ice Sheet Micro-Topography Based on Unmanned Aerial Vehicle Data, Antarctica. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43: 919-923.

(8) Cunliffe, A.M., Tanski, G., Radosavljevic, B., Palmer, W.F., Sachs, T., Lantuit, H., Myers-Smith, I.H. (2019). Rapid retreat of permafrost coastline observed with aerial drone photogrammetry. The Cryosphere, 13: 1513-1528.

(9) Turner, I.L., Harley, M.D., Drummond, C.D. (2016). UAVs for coastal surveying. Coastal Engineering, 114: 19-24.

(10) Gonçalves, G.R., Pérez, J. A., Duarte, J. (2018). Accuracy and effectiveness of low cost UASs and open source photogrammetric software for foredunes mapping. International Journal of Remote Sensing, 39(15-16): 5059-5077.

(11) Tatum, M. C., Liu, J. (2017). Unmanned aircraft system applications in construction. Procedia Engineering, 196: 167-175.

(12) Coetzee, G. L. (2018). Smart Construction Monitoring of Dams with UAVS-Neckartal dam Water Project Phase 1. Smart Dams and Reservoirs: Proceedings of the 20th Biennial Conference of the British Dam, 13-15:445-456. Swanse (ICE Publishing).

.

(13) Sreenath, S., Malik, H., Husnu, N., Kalaichelavan, K. (2020). Assessment and Use of Unmanned Aerial Vehicle for Civil Structural Health Monitoring. Procedia Computer Science, 170: 656-663.

(14) Colomina, I., Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS Journal of Photogrammetry and Remote Sensing, 92: 79-97.

(15) Kardasz, P., Doskocz, J., Hejduk, M., Wiejkut, P., Zarzycki, H. (2016). Drones and possibilities of their using. Journal of Civil Environmental Engineering, 6(3): 1-7.

(16) Kerle, N., Nex, F., Gerke, M., Duarte, D., Vetrivel, A. (2020). UAV-Based Structural Damage Mapping: A Review. ISPRS International Journal of Geo-Information, 9(1): 14.

(17) Pena-Villasenin, S., Gil-Docampo, M., & Ortiz-Sanz, J. (2020). Desktop vs cloud computing software for 3D measurement of building façades: The monastery of San Martín Pinario. Measurement, 149: 106984.

(18) Rangel, J.M.G., Gonçalves, G.R., Pérez, J.A. (2018). The impact of number and spatial distribution of GCPs on the positional accuracy of geospatial products derived from low-cost UASs. International Journal of Remote Sensing, 39(21): 7154-7171.

(19) Pérez, J.A., Gonçalves, G.R., Rangel, J.M.G., Ortega, P.F. (2019). Accuracy and effectiveness of orthophotos obtained from low cost UASs video imagery for traffic accident scenes documentation. Advances in Engineering Software, 132: 47-54.

(20) Hugenholtz, C., Brown, O., Walker, J., Barchyn, T., Nesbit, P., Kucharczyk, M., Myshak, S. (2016). Spatial accuracy of UAV-derived orthoimagery and topography: Comparing photogrammetric models processed with direct geo-referencing and ground control points. Geomatica, 70(1): 21-30.

(21) Agüera-Vega, F., Carvajal-Ramírez, F., Martínez-Carricondo, P. (2017). Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry. Journal of Surveying Engineering, 143(2): 04016025.

(22) Popescu, G., Iordan, D., Păunescu, V. (2016). The resultant positional accuracy for the orthophotos obtained with Unmanned Aerial Vehicles (UAVs). Agriculture and Agricultural Science Procedia, 10: 458-464.

(23) Pérez, Juan Antonio, Gil Rito Gonçalves, and María Cristina Charro. (2019). On the positional accuracy and maximum allowable scale of UAV-derived photogrammetric products for archaeological site documentation. Geocarto International, 34(6): 575-585.

(24) Ferrer-González, E., Agüera-Vega, F., Carvajal-Ramírez, F., Martínez-Carricondo, P. (2020). UAV Photogrammetry Accuracy Assessment for Corridor Mapping Based on the Number and Distribution of Ground Control Points. Remote Sensing, 12(15): 2447.

(25) Ackermann, F. (1966). On the theoretical accuracy of planimetric block triangulation. Photogrammetria, 21(5): 145-170.

(26) Smith, M.W., Carrivick, J.L., Quincey, D.J. (2016). Structure from motion photogrammetry in physical geography. Progress in Physical Geography, 40(2): 247-275.

(27) Pikelj, K., Ružić, I., James, M. R., Ilic, S. (2018). Structure-from-Motion (SfM)monitoring of nourished gravel beaches in Croatia. In Coasts, Marine Structures and Breakwaters 2017: Realising the Potential (pp. 561-564). ICE Publishing.

(28) Iglhaut, J., Cabo, C., Puliti, S., Piermattei, L., O’Connor, J., Rosette, J. (2019). Structure from motion photogrammetry in forestry: A review. Current Forestry Reports, 5(3): 155-168.

(29) 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.

(30) Mayer, C., Pereira, L. G., Kersten, T. P. (2018). A comprehensive workflow to process UAV images for the efficient production of accurate Geo-Information. In IX National Conference on Cartography and Geodesy. Amadora (CNCG2018).

(31) Gindraux, S., Boesch, R., Farinotti, D. (2017). Accuracy assessment of digital surface models from unmanned aerial vehicles’ imagery on glaciers. Remote Sensing, 9(2): 186.

(32) USGS (2017). Unmanned Aircraft Systems Data Post-Processing. United States Geological Survey. UAS Federal Users Workshop 2017. https://uas.usgs.gov/nupo/pdf/PhotoScanProcessingDSLRMar2017.pdf.

(33) James, M. R. (2017). SfM-MVS PhotoScan image processing exercise. IAVCEI 2017 UAS workshop: Lancaster University. James, Mike. (2017). SfM-MVS PhotoScan image processing exercise. https://www.researchgate.net/publication/320407992_SfM-MVS_PhotoScan_image_processing_exercise.

(34) Agisoft, L. L. C. (2018). Agisoft metashape user manual, Professional edition, Version 1.5. Agisoft LLC, St. Petersburg, Russia. https://www.agisoft.com/pdf/metashape-pro_1_6_en.pdf.

(35) Nadal-Romero, E., Revuelto, J., Errea, P., López-Moreno, J.I. (2015). The application of terrestrial laser scanner and SfM photogrammetry in measuring erosion and deposition processes in two opposite slopes in a humid badlands area (central Spanish Pyrenees). Soil, 1(2):561.

(36) Anders, N., Valente, J., Masselink, R., Keesstra, S. (2019). Comparing Filtering Techniques for Removing Vegetation from UAV-Based Photogrammetric Point Clouds. Drones, 3(3): 61.

(37) Montilla Galván, J. (2020). Tratamiento y Depurado de Nubes de Puntos obtenidas mediante Fotogrametría Aérea (UAV/drones) aplicadas a Ingeniería Civil. Algoritmos de Filtrado y Geometrías Convergentes (TFM no publicado), Cáceres, Universidad de Extremadura.

(38) American Society for Photogrammetry and Remote Sensing (ASPRS). (2015). New ASPRS positional accuracy standards for digital geospatial data released. Photogrammetric Engineering and Remote Sensing, 81(4): 227-253. https://www.asprs.org/wp-content/uploads/2015/01/PERS_March2015_Highlight.pdf.

(39) Brunier, G., Fleury, J., Anthony, E. J., Gardel, A., Dussouillez, P. (2016). Close-range airborne Structure-from-Motion Photogrammetry for high-resolution beach morphometric surveys: Examples from an embayed rotating beach. Geomorphology, 261: 76-88.

(40) Kraaijenbrink, P.D.A., Shea, J.M., Pellicciotti, F., de Jong, S.M., Immerzeel, W.W. (2016). Object-based analysis of unmanned aerial vehicle imagery to map and characterise surface features on a debris-covered glacier. Remote Sensing of Environment, 186: 581-595

Publicado

2022-03-25

Cómo citar

Pérez, J. A. ., Rito Gonçalves, G. ., & Montilla Galván, J. . (2022). Análisis comparativo del levantamiento del terreno mediante UAS y topografía clásica en proyectos de trazado de carreteras. Informes De La Construcción, 74(565), e431. https://doi.org/10.3989/ic.86273

Número

Sección

Artículos

Datos de los fondos

Universidad de Extremadura
Números de la subvención Ref 001/20