Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion

Stumpf, André; Malet, Jean‐Philippe; Allemand, Pascal; Pierrot-Deseilligny, Marc; Skupinski, Grzegorz

doi:10.1016/j.geomorph.2014.10.039

Cited by 198 publications

(139 citation statements)

References 43 publications

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“…For all reconstructed image-based models, the highest values of elevation difference are identified on the vegetated area and on the undercut area where, however, a vertical difference is not appropriate for accuracy evaluation. In SfM approach, vegetation represents a general limitation not only for occlusion but also for degradation in the quality of surface reconstruction (Micheletti et al, 2014;Dietrich, 2015) due to the high surface roughness and variable pattern (Stumpf et al, 2015). In our work, the standard deviation of the elevation differences and distance 'cloud to cloud' with the TLS is significantly higher than the mean values in the vegetated area.…”

Section: Discussionmentioning

confidence: 60%

“…This approach is lower in instrument costs compared to light detection and ranging technology (LiDAR), and has lower requirements on user expertise to create a geometrical 3D model thanks to the high level of automation in image processing. Additionally, in different fields of the geosciences (James and Robson, 2014;Thoeni et al, 2014;Piermattei et al, 2015;Smith and Vericat, 2015;Stumpf et al, 2015) it was shown that accuracy and resolution obtained are comparable to those obtained by LiDAR. However, as reported in the investigations on error sources and obtained precision by (Wackrow and Chandler, 2011;James and Robson, 2012;Micheletti et al, 2014;Nocerino et al, 2014;Bemis et al, 2014) the quality of the photogrammetric results depends principally upon (i) the camera network geometry and (ii) control data.…”

Section: Introductionmentioning

confidence: 58%

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Panorama Image Sets for Terrestrial Photogrammetric Surveys

Piermattei

Karel

Vettore

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:High resolution 3D models produced from photographs acquired with consumer-grade cameras are becoming increasingly common in the fields of geosciences. However, the quality of an image-based 3D model depends on the planning of the photogrammetric surveys. This means that the geometric configuration of the multi-view camera network and the control data have to be designed in accordance with the required accuracy, resolution and completeness. From a practical application point of view, a proper planning (of both photos and control data) of the photogrammetric survey especially for terrestrial acquisition, is not always ensured due to limited accessibility of the target object and the presence of occlusions. To solve these problems, we propose a different image acquisition strategy and we test different geo-referencing scenarios to deal with the practical issues of a terrestrial photogrammetric survey. The proposed photogrammetric survey procedure is based on the acquisition of a sequence of images in panorama mode by rotating the camera on a standard tripod. The offset of the pivot point from the projection center prevents the stitching of these images into a panorama. We demonstrate how to still take advantage of this capturing mode. The geo-referencing investigation consists of testing the use of directly observed coordinates of the camera positions, different ground control point (GCP) configurations, and GCPs with different accuracies, i.e. artificial targets vs. natural features. Images of the test field in a low-slope hill were acquired from the ground using an SLR camera. To validate the photogrammetric results a terrestrial laser scanner survey is used as benchmark.

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Section: Discussionmentioning

confidence: 60%

Section: Introductionmentioning

confidence: 58%

Panorama Image Sets for Terrestrial Photogrammetric Surveys

Piermattei

Karel

Vettore

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…and its evolution over time by comparing 3-D point clouds acquired at different time steps. For example, 3-D remote sensing techniques are helping to better quantify key aspects of rock slope evolution, including the accurate quantification of rockfall rates and the deformation of rock slopes before failure using both lidar (Rosser et al, 2005;Oppikofer et al, 2009;Royan et al, 2014;Kromer et al, 2015;Fey and Wichmann., 2017) and photogrammetrically derived point clouds (Walstra et al, 2007;Lucieer et al, 2013, Stumpf et al, 2015Fernandes et al, 2016;Guerin et al, 2017;Ruggles et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Using street view imagery for 3-D survey of rock slope failures

Voumard

Abellán

Nicolet

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. We discuss here different challenges and limitations of surveying rock slope failures using 3-D reconstruction from image sets acquired from street view imagery (SVI). We show how rock slope surveying can be performed using two or more image sets using online imagery with photographs from the same site but acquired at different instances. Three sites in the French alps were selected as pilot study areas: (1) a cliff beside a road where a protective wall collapsed, consisting of two image sets (60 and 50 images in each set) captured within a 6-year time frame; (2) a large-scale active landslide located on a slope at 250 m from the road, using seven image sets (50 to 80 images per set) from five different time periods with three image sets for one period; (3) a cliff over a tunnel which has collapsed, using two image sets captured in a 4-year time frame. The analysis include the use of different structure from motion (SfM) programs and a comparison between the extracted photogrammetric point clouds and a lidar-derived mesh that was used as a ground truth. Results show that both landslide deformation and estimation of fallen volumes were clearly identified in the different point clouds. Results are site-and softwaredependent, as a function of the image set and number of images, with model accuracies ranging between 0.2 and 3.8 m in the best and worst scenario, respectively. Although some limitations derived from the generation of 3-D models from SVI were observed, this approach allowed us to obtain preliminary 3-D models of an area without on-field images, allowing extraction of the pre-failure topography that would not be available otherwise.

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“…A nivel internacional, dentro del ámbito de las Ciencias de la Tierra, las técnicas de fotoreconstrucción 3D se han empleado para modelizar superficies de diferente naturaleza y magnitud (James y Robson, 2012;Westoby et al, 2012;Fonstad et al, 2013;Javernick et al, 2014;Lucieer et al, 2014a;Frankl et al, 2015;Smith y Vericat, 2015;Stumpf et al, 2015). Las previsiones de los trabajos que se han publicado durante los últimos 5 años son claras y unánimes en cuanto a que tendrá lugar una utilización y expansión generalizada de estas técnicas en disciplinas como la Geomorfología.…”

Section: Introductionunclassified

Elaboración de modelos 3D de diferentes morfologías y escalas utilizando técnicas Structure-from-Motion y fotografías terrestres

Gutiérrez

Schnabel

Conoscenti

et al. 2016

CyG

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En este trabajo se evalúan los métodos de foto-reconstrucción automatizada basados en el uso conjunto de las técnicas Structure from Motion (SfM) y Multi-View Stereo (MVS) para medir, monitorizar y cuantificar la dinámica de tres formas geomorfológicas: i) el glaciar rocoso del Corral del Veleta (Granada, España), ii) un paisaje de cárcavas de tipo calanchi (Sicilia, Italia) y ii) cinco pequeñas cabeceras de cárcava (Cáceres, España). Se incluyen en este trabajo los resultados sobre la precisión, utilidad y aplicabilidad de estas técnicas. Para la cuantificación de la precisión se utilizan el error cuadrático medio (RMSE) de los puntos de control que se emplean en la georreferenciación y las distancias medias absolutas entre cada nube de puntos y una nube de puntos de referencia calculadas con los métodos cloud-to-cloud y multiscale model-to-model cloud comparison. Para los casos i) y iii) las nubes de referencia se capturaron utilizando un escáner láser terrestre, mientras que para el caso ii) se empleó un modelo digital de elevaciones obtenido mediante fotogrametría clásica aplicada a fotogramas aéreos capturados con un vehículo aéreo no tripulado. Los resultados de estos análisis mostraron precisiones de rango centimétrico con distancias medias a los modelos de referencia que oscilaron entre 0,01 m y 0,42 m. Las precisiones estimadas indican que los modelos obtenidos podrían utilizarse para calcular el volumen de cambio geomorfológico, tan sólo en el caso de las cabeceras. En el caso del glaciar y del calanchi los modelos podrían emplearse para elaborar cartografía precisa o estimar parámetros morfológicos, pero no para registrar cambios a escala anual.

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Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion

Cited by 198 publications

References 43 publications

Panorama Image Sets for Terrestrial Photogrammetric Surveys

Panorama Image Sets for Terrestrial Photogrammetric Surveys

Using street view imagery for 3-D survey of rock slope failures

Elaboración de modelos 3D de diferentes morfologías y escalas utilizando técnicas Structure-from-Motion y fotografías terrestres

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