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Assessment of RTK Quadcopter and Structure-from-Motion Photogrammetry for Fine-Scale Monitoring of Coastal Topographic Complexity

Authors :
Bertin, Stéphane
Stéphan, Pierre
Ammann, Jérôme
Bertin, Stéphane
Stéphan, Pierre
Ammann, Jérôme
Source :
Remote Sensing (2072-4292) (MDPI AG), 2022-04 , Vol. 14 , N. 7 , P. 1679 (24p.)
Publication Year :
2022

Abstract

Advances in image-based remote sensing using unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry continue to improve our ability to monitor complex landforms over representative spatial and temporal scales. As with other water-worked environments, coastal sediments respond to shaping processes through the formation of multi-scale topographic roughness. Although this topographic complexity can be an important marker of hydrodynamic forces and sediment transport, it is seldom characterized in typical beach surveys due to environmental and technical constraints. In this study, we explore the feasibility of using SfM photogrammetry augmented with an RTK quadcopter for monitoring the coastal topographic complexity at the beach-scale in a macrotidal environment. The method had to respond to resolution and time constraints for a realistic representation of the topo-morphological features from submeter dimensions and survey completion in two hours around low tide to fully cover the intertidal zone. Different tests were performed at two coastal field sites with varied dimensions and morphologies to assess the photogrammetric performance and eventual means for optimization. Our results show that, with precise image positioning, the addition of a single ground control point (GCP) enabled a global precision (RMSE) equivalent to that of traditional GCP-based photogrammetry using numerous and well-distributed GCPs. The optimal model quality that minimized vertical bias and random errors was achieved from 5 GCPs, with a two-fold reduction in RMSE. The image resolution for tie point detection was found to be an important control on the measurement quality, with the best results obtained using images at their original scale. Using these findings enabled designing an efficient and effective workflow for monitoring coastal topographic complexity at a large scale

Details

Database :
OAIster
Journal :
Remote Sensing (2072-4292) (MDPI AG), 2022-04 , Vol. 14 , N. 7 , P. 1679 (24p.)
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1313390913
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.3390.rs14071679