INFLUENCE OF GROUND CONTROL POINTS (GCPS) ON THE ACCURACY OF CARTOGRAPHIC PRODUCTS GENERATED BY UNMANNED AERIAL VEHICLES (UAVS) IN AREA WITH ALTIMETRIC VARIATION
Keywords:
GCPs, control points, RMSE, UAV, SfM-CMVSAbstract
The processing of images obtained by UAVs, with advances in the SfM-MVS technique, has become popular in studies in the area of Geosciences, having several applications due to its low cost, speed and practicality of the method. Practicality means that less experienced users use the method and, often, cartographic accuracy is left in the background. The precision and accuracy of models obtained with UAVs have been the subject of studies in recent years, but there is still a need for in-depth studies on the mapping of areas with large elevation amplitudes. The objective of this research was to analyze the variation in RMSE according to the influence of the number of GCPs and to estimate an ideal number of control points that should be used to produce accurate results in an area of open pit basalt extraction in the form of platforms in the state of Rio Grande do Sul with an elevation variation of approximately 50m. With a number of 10 to 16 GCPs, a stabilization of errors was observed in the study area, but other factors besides the number of GCPs proved to be important in the error variation, such as point distribution, lighting, image overlap rate and variation in scale due to the height of the photo.
References
AGISOFT. Agisoft Metashape User Manual - Professional Edition, Version 2.0. 2023.
AGÜERA-VEGA, Francisco; RAMÍREZ, Fernando Carvajal; CARRICONDO, Patricio Martínez. Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement, v. 98, p. 221-227, 2017. https://doi.org/10.1016/j.measurement.2016.12.002
ANDERS, N.; SMITH, M.; SUOMALAINEN, J.; Impact of flight altitude and cover orientation on Digital Surface Model (DSM) accuracy for flood damage assessment in Murcia (Spain) using a fixed-wing UAV. Earth Science Informatics, v. 13, n. 2, p. 391–404, 2020.
BOLKAS, Dimitrios. Assessment of GCP number and separation distance for small UAS surveys with and without GNSS-PPK positioning. Journal of Surveying Engineering, v. 145, n. 3, p. 04019007, 2019.https://doi.org/10.1061/(ASCE)SU.1943-5428.0000283
CARRERA-HERNÁNDEZ, Jaime Jesús et al. A low cost technique for development of ultra-high resolution topography: application to a dry maar's bottom. Revista mexicana de ciencias geológicas, v. 33, n. 1, p. 122-133, 2016.
CARRICONDO, Patricio Martínez et al. Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International journal of applied earth observation and geoinformation, v. 72, p. 1-10, 2018. https://doi.org/10.1016/j.jag.2018.05.015
COOK, Kristen L. An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection. Geomorphology, v. 278, p. 195–208, 2017. https://doi.org/10.1016/j.geomorph.2016.11.009
ELTNER, Anette; SOFIA, Giulia. Structure from motion photogrammetric technique. Developments in Earth surface processes. Elsevier, v. 23, p. 1-24, 2020. https://doi.org/10.1016/B978-0-444-64177-9.00001-1
GABRLIK, Petr et al.; COUR-HARBO, A. LA; KALVODOVA, P.; ZALUD, L.; JANATA, P. Calibration and accuracy assessment in a direct georeferencing system for UAS photogrammetry. International Journal of Remote Sensing, v. 39, n. 15–16, p. 4931–4959, 2018. https://doi.org/10.1080/01431161.2018.1434331
GARRETT, Bradley; ANDERSON, Karen. Drone methodologies: Taking flight in human and physical geography. Transactions of the Institute of British Geographers, v. 43, n. 3, p. 341–359, 2018. https://doi.org/10.1111/tran.12232.
GLENDELL, Miriam et al. Testing the utility of structure-from-motion photogrammetry reconstructions using small unmanned aerial vehicles and ground photography to estimate the extent of upland soil erosion. Earth Surface Processes and Landforms, v. 42, n. 12, p. 1860–1871, 2017. https://doi.org/10.1002/esp.4142.
GONÇALVES, Gil et al. 3D reconstruction of coastal cliffs from fixed-wing and multi-rotor uas: Impact of sfm-mvs processing parameters, image redundancy and acquisition geometry. Remote Sensing, v. 13, n. 6, p. 1222, 2021. https://doi.org/10.3390/rs13061222
GONCALVES, José A.; HENRIQUES, Renato. UAV photogrammetry for topographic monitoring of coastal areas. ISPRS journal of Photogrammetry and Remote Sensing, v. 104, p. 101-111, 2015. https://doi.org/10.1016/j.isprsjprs.2015.02.009
GONG, Chuangang et al. Analysis of the Development of an Erosion Gully in an Open-Pit Coal Mine Dump During a Winter Freeze-Thaw Cycle by Using Low-Cost UAVs. Remote Sensing, v. 11, n. 11, p. 1356, 2019. https://doi.org/10.3390/rs11111356.
JAMES, Michael R. et al. Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment. Geomorphology, v. 280, p. 51–66, 2017. https://doi.org/10.1016/j.geomorph.2016.11.021.
LIU, Kai et al. Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau. ISPRS International Journal of Geo-Information, v. 5, n. 12, p. 238, 2016. https://doi.org/10.3390/ijgi5120238.
MEINEN, Benjamin U.; ROBINSON, Derek T. Mapping erosion and deposition in an agricultural landscape: Optimization of UAV image acquisition schemes for SfM-MVS. Remote Sensing of Environment, v. 239, p. 111666, 2020. https://doi.org/10.1016/j.rse.2020.111666
NOTA, Eise Wiebe; NIJLAND, W.; DE HAAS, Tjalling. Improving UAV-SfM time-series accuracy by co-alignment and contributions of ground control or RTK positioning. International Journal of Applied Earth Observation and Geoinformation, v. 109, p. 102772, 2022. https://doi.org/10.1016/j.jag.2022.102772
RADEMANN, Lucas Krein; TRENTIN, Romario; ROBAINA, Luis Eduardo de Souza. Caracterização e análise de erosão por voçorocamento no sul do Brasil com o auxílio de Veículo Aéreo Não Tripulado. Mercator (Fortaleza), v. 21, 2022. https://doi.org/10.4215/rm2022.e21022
REN, He et al. An Improved Ground Control Point Configuration for Digital Surface Model Construction in a Coal Waste Dump Using an Unmanned Aerial Vehicle System. Remote Sensing, v. 12, n. 10, p. 1623, 2020. https://doi.org/10.3390/rs12101623
SANZ-ABLANEDO, Enoc et al. Accuracy of Unmanned Aerial Vehicle (UAV) and SfM Photogrammetry Survey as a Function of the Number and Location of Ground Control Points Used. Remote Sensing, v. 10, n. 10, p. 1606, 2018. https://doi.org/10.3390/rs10101606
STÖCKER, Claudia; ELTNER, Anette; KARRASCH, Pierre. Measuring gullies by synergetic application of UAV and close-range photogrammetry - A case study from Andalusia, Spain. Catena, v. 132, p. 1–11, 2015. https://doi.org/10.1016/j.catena.2015.04.004.
TURNER, Darren; LUCIEER, Arko; WALLACE, Luke. Direct georeferencing of ultrahigh-resolution UAV imagery. IEEE Transactions on Geoscience and Remote Sensing, v. 52, n. 5, p. 2738-2745, 2013. https://doi.org/10.1109/TGRS.2013.2265295.
TURNER, Darren; LUCIEER, Arko; WATSON, Cristopher. An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds. Remote Sensing, v. 4, n. 5, p. 1392–1410, 2012. https://doi.org/10.3390/rs4051392
UYSAL, Murat; TOPRAK, Ahmet S.; POLAT, Nizar. DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill. Measurement, v. 73, p. 539–543, 2015. https://doi.org/10.1016/j.measurement.2015.06.010.
VERDONK, S. C. Gully volume estimates using UAV Photometry. Dissertação de Mestrado, University of Utrecht, p. 80, 2015. https://studenttheses.uu.nl/handle/20.500.12932/34266
WESTOBY, Matthew J. et al. ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology, v. 179, p. 300–314, 2012. https://doi.org/10.1016/j.geomorph.2012.08.021
WILDNER, W. et al. Geologia e recursos minerais do estado do Rio Grande do Sul: escala 1:750.000. Porto Alegre: CPRM, 2008.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 REVISTA GEOGRÁFICA ACADÊMICA
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
A RGA é detentora dos direitos autorais publicados, não sendo permitido que o mesmo conteúdo seja publicado em demais periódicos.
