Uav Photogrammetry to Monitor Dykes – Calibration and Comparison to Terrestrial Lidar

Tournadre, Vincent; Pierrot-Deseilligny, Marc; Faure, Paul-Henri

doi:10.5194/isprsarchives-xl-3-w1-143-2014

Cited by 19 publications

(14 citation statements)

References 7 publications

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“…To reduce the influence of the “human factor,” the same location (pixel coordinates) of georeferenced high contrast markers in the aerial 2D images was used across the four different software. The citations given alongside indicate other literature examples that have utilized these software in ecology research: 3DFlow Zephyr Aerial (little evidence of use in ecology, though widely used in urban environments, e.g., Vassena & Clerici, ; Peel, Luo, Cohn, & Fuentes, ; Azzola, Cardaci, Mirabella Roberti, & Nannei, ). Agisoft Photoscan (Cunliffe et al, ; Dandois et al, ; Hoffmann et al, ; Javernick, Brasington, & Caruso, ; Lucieer, Turner, King, & Robinson, ; Obanawa & Hayakawa, ). Pix4D (Magtalas, Aves, & Blanco, ; Ouédraogo, Degré, Debouche, & Lisein, ; Raeva, Filipova, & Filipov, ). MICMAC (Forsmoo et al, ; Lisein, Pierrot‐Deseilligny, Bonnet, & Lejeune, ; Ouédraogo et al, ; Tournadre, Pierrot‐Deseilligny, & Faure, ; Tournadre, Pierrot‐Deseilligny, & Faure, ). …”

Section: Methodsmentioning

confidence: 99%

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Forsmoo

Anderson

Macleod

et al. 2019

Ecology and Evolution

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Image‐based modeling, and more precisely, Structure from Motion (SfM) and Multi‐View Stereo (MVS), is emerging as a flexible, self‐service, remote sensing tool for generating fine‐grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone‐based SfM + MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM + MVS if it is to fulfill a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer‐grade camera was used to capture replicate, centimeter‐resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of method reproducibility and the impact of SfM + MVS software choice on derived vegetation canopy height measurement accuracy. The quality of DSM height measurements derived from four different, yet widely used SfM‐MVS software—Photoscan, Pix4D, 3DFlow Zephyr, and MICMAC, was compared with in situ data captured on the same day as image capture. We used both traditional agronomic techniques for measuring sward height, and a high accuracy and precision differential GPS survey to generate independent measurements of the underlying ground surface elevation. Using the same replicate image dataset (n = 3) as input, we demonstrate that there are 1.7, 2.0, and 2.5 cm differences in RMSE (excluding one outlier) between the outputs from different SfM + MVS software using High, Medium, and Low quality settings, respectively. Furthermore, we show that there can be a significant difference, although of small overall magnitude between replicate image datasets (n = 3) processed using the same SfM + MVS software, following the same workflow, with a variance in RMSE of up to 1.3, 1.5, and 2.7 cm (excluding one outlier) for “High,” “Medium,” and “Low” quality settings, respectively. We conclude that SfM + MVS software choice does matter, although the differences between products processed using “High” and “Medium” quality settings are of small overall magnitude.

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Section: Methodsmentioning

confidence: 99%

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Forsmoo

Anderson

Macleod

et al. 2019

Ecology and Evolution

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“…() and is described step‐by‐step in the , to further facilitate the adoption and adaptation of the workflow described herein. Moreover, in the studies that have used MICMAC it has performed favourably when compared to validation data and/or other software on the basis of accuracy and robustness (Ouédraogo, Degré, Debouche, & Lisein, ; Tournadre, Pierrot‐Deseilligny, & Faure, ; Tournadre et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…MICMAC implements a range of different camera lens distortion models. The choice of camera lens calibration method has been shown to influence the accuracy of the resulting model produced by the SfM+MVS‐processing workflow (Tournadre et al., ). In this study, the Radial Extended camera calibration method was chosen, as it has been shown to perform well in other studies (Tournadre et al., ).…”

Section: Methodsmentioning

confidence: 99%

Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability

Forsmoo

Anderson

Macleod

et al. 2018

Journal of Applied Ecology

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Grasslands deliver a range of ecosystem services, including the provision of food and biodiversity, and regulation of soil carbon storage and hydrology. Monitoring schemes are needed to quantify spatial changes in these multiple functions alongside ecosystem degradation. Sward height is widely recognised as a key spatial variable in the provision of these services. Current manual monitoring approaches are labour intensive, and often fail to capture spatial patterns of important features, including sward height. Proximal sensing from small aerial drones carrying lightweight cameras can be transformed into surface height models using image‐based structure‐from‐motion and Multi‐View Stereo‐based approaches; this presents a new opportunity for monitoring the spatial structure of grassland sward height. We combined aerial photographs with field survey data and an open‐source image‐based modelling‐processing workflow to generate sward height measurements for a field comprising mainly Lolium perenne (perennial ryegrass) and Trifolium pratense (red clover). We compared the derived measurements with in situ data captured on the same day using traditional agronomic sward height techniques to determine the quality of the drone‐derived surface model product for sward characterisation. The SfM and Multi‐View Stereo‐based surface model had a mean absolute sward height measurement error of between 3.7 and 4.2 cm. To produce field observations with equivalent quality would require up to 550 sward height measurements for the study site (area: 8,059 m2), which is not feasible over larger extents required for conservation of key species or agronomic purposes. Synthesis and applications. We demonstrate how the collection of precise and detailed information on the spatial structure of grasslands can be made over management‐relevant extents. Aerial digital photographs can be transformed into surface models using an image‐based modelling approach: structure‐from‐motion and Multi‐View Stereo techniques. Image‐based measurements of sward heights were compared with manual sward height data captured on the same day. This novel source of vegetation spatial information could improve sward management for conservation and agronomy applications. The approach supports frequent surveys, at user‐controlled revisit times, and delivers data for spatial monitoring of key grassland functions and services.

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“…Van Iersel, Straatsma, Addink, and Middelkoop (); 12. Tournadre, Pierrot‐Deseilligny, and Faure (); 13. Young, Peschel, Penny, Thompson, and Srinivasan (); 14.…”

Section: River Corridor Remote Sensingmentioning

confidence: 99%

Remote sensing of river corridors: A review of current trends and future directions

Tomsett

Leyland

2019

River Research & Apps

104

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River corridors play a crucial environmental, economic, and societal role yet also represent one of the world's most dangerous natural hazards, making monitoring imperative to improve our understanding and to protect people. Remote sensing offers a rapidly growing suite of methods by which river corridor monitoring can be performed efficiently, at a range of scales and in difficult environmental conditions. This paper aims to evaluate the current state and assess the potential future of river corridor monitoring, whilst highlighting areas that require further investigation. We initially review established methods that are used to undertake river corridor monitoring, framed by the context and scales upon which they are applied. Subsequently, we review cutting edge technologies that are being developed and focussed around unmanned aerial vehicle and multisensor system advances. We also "horizon scan" for future methods that may become increasingly prominent in research and management, citing examples from within and outside of the fluvial domain. Through review of the literature, it has become apparent that the main gap in fluvial remote sensing lies in the trade-off between resolution and scales. However, prioritising process measurements and simultaneous multisensor data collection is likely to offer a bigger advance in understanding than purely from better surveying methods alone. Challenges regarding the legal deployment of more complex systems, as well as effectively disseminating data into the science community, are amongst those that we propose need addressing. However, the plethora of methods currently available means that researchers and monitoring agencies will be able to identify suitable techniques for their needs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Uav Photogrammetry to Monitor Dykes – Calibration and Comparison to Terrestrial Lidar

Cited by 19 publications

References 7 publications

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability

Remote sensing of river corridors: A review of current trends and future directions

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