LIDAR XXI: técnicas topográficas del siglo XXI aplicadas a la detección de yacimientos arqueológicos ocultos por vegetación

Jesús Rodríguez-Bulnes; Emilio García Soto; José Manuel López Funes

doi:10.30827/unes.i16.28660

Authors

Jesús Rodríguez-Bulnes a:1:{s:5:"es_ES";s:19:"0009-0006-5974-0523";} https://orcid.org/0009-0006-5974-0523
Emilio García Soto Profesor de Formación Profesional en el Centro Ave María San Cristóbal https://orcid.org/0009-0003-0428-5832
José Manuel López Funes Profesor de Formación Profesional en el Centro Ave María San Cristóbal https://orcid.org/0009-0003-2153-4300

DOI:

https://doi.org/10.30827/unes.i16.28660

Keywords:

Higher vocational training, LIDAR, Archaeology, Topography, Drone

Abstract

LIDAR XXI is an educational project, which was born with the purpose of including “ciclo formativo grado superior en proyectos de obra civil”, the latest technological advances related to the cartography and surveying sector. It was selected among the 30 most innovative winning projects of vocational training at national level, of the 180 presented to the Caixabank Dualiza call for the 2021-2022 academic year. Participation in this programme meant receiving the necessary funding for its implementation and development. The project has a double purpose, on the one hand, to bring innovation to professional training by incorporating state-of-the-art technology and, on the other, to carry out research in collaboration with the Biocultural-MEMOLab archaeology laboratory of the University of Granada, determining the optimization of the LIDAR application to the detection of archaeological sites.

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References

AlphaAir 450 UAV LIDAR SOLUTIONS MAPPING & GEOSPATIAL. (2022).

Căţeanu, M., & Arcadie, C. (2017). Als for terrain mapping in forest environments: An analysis of LIDAR filtering algorithms. EARSeL EProceedings, 16(1), 9–20. https://doi.org/10.12760/01-2017-1-02

Lozić, E., & Štular, B. (2021). Documentation of Archaeology-Specific Workflow for Airborne LIDAR Data Processing. Geosciences, 11(1), 26. https://doi.org/10.3390/geosciences11010026

Martín Talaverano, R. (2014). Documentación gráfica de edificios históricos: principios, aplicaciones y perspectivas. Arqueología de La Arquitectura, 0(11), e011. https://doi.org/10.3989/arq.arqt.2014.014

Puliti, S., Ene, L. T., Gobakken, T., & Næsset, E. (2017). Use of partial-coverage UAV data in sampling for large scale forest inventories. Remote Sensing of Environment, 194, 115–126. https://doi.org/10.1016/j.rse.2017.03.019

Rizaldy, A., Persello, C., Gevaert, C. M., & Oude Elberink, S. J. (2018). FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, IV–2(2), 231–238. https://doi.org/10.5194/isprs-annals-IV-2-231-2018

Rodriguez-Bulnes, J., Benavides Lopez, J. A., Romero Pellitero, P., Martin Civantos, J. M., & Rouco Collazo, J. (2022). The documentation of archaeological heritage through aerial photogrammetry and UAS-based LIDAR: the case study of the Espique valley (La Peza, Spain). Disegnarecon. https://doi.org/https://doi.org/10.20365/disegnarecon.29.2022.12

Rouco Collazo, J., Benavides López, J. A., & Martén Civantos, J. M. (2020). Falling from the sky. Aerial photogrammetry and LIDAR applied to the Archaeology of Architecture and Landscape: two fortifications from the Alpujarra (Granada, Spain).

Yang, B., Huang, R., Dong, Z., Zang, Y., & Li, J. (2016). Two-step adaptive extraction method for ground points and breaklines from LIDAR point clouds. ISPRS Journal of Photogrammetry and Remote Sensing, 119, 373–389. https://doi.org/10.1016/j.isprsjprs.2016.07.002

Zhang, Wu, & Yang. (2019). Forests Growth Monitoring Based on Tree Canopy 3D Reconstruction Using UAV Aerial Photogrammetry. Forests, 10(12), 1052. https://doi.org/10.3390/f10121052

Zhang, H., Aldana-Jague, E., Ois Clapuyt, F., Wilken, F., Vanacker, V., & Oost, K. van. (2019). Evaluating the Potential of PPK Direct Georeferencing for UAV-SfM Photogrammetry and Precise Topographic Mapping. https://doi.org/10.5194/esurf-2019-2

Zietara, A. M., & Skogseth, T. (2017). Creating Digital Elevation Model (DEM) based on ground points extracted from classified aerial images obtained from Unmanned Aerial Vehicle (UAV).