3D surface and DEM construction from imagesDigital elevation models (DEMs) have been made from images for many years. However, traditional photogrammetric analyis techniques require considerable expertise for both image capture and data processing. The recent emergence of structure-from-motion and multi-view stereo (SfM-MVS) approaches from the computer vision community offer the potential for significantly easing some of the requirements for obtaining 3D models from consumer cameras for geoscience applications.
One of the main drawbacks of SfM-MVS is that the error assessments that are integral to photogrammetric workflows are difficult to carry out as they are not implemented in the SfM-MVS reconstruction pipelines. However, error magnitudes do appear suitable for many geoscience applications (James & Robson, 2012) with surface precisions being around 1:1000 (i.e. a precision of ±1 mm for every 1 m of viewing distance). Jim Chandler has also carried out some accuracy assessment of the output from Autodesk's SfM-MVS webservice, 123D Catch.
Most of the reconstructions carried out here have been done using the free 'Bundler Photogrammetry Package' put together by Josh Harle (requires 64-bit machine, Windows and Nvidia graphics card). The output is a dense point cloud representing the reconstructed surfaces, but does not have a scale and has an arbitrary orientation. To attribute scale or to fully georeference the model, see sfm_georef, which also gives for further example models.
SfM software: A table of SfM software and websites is available here .
Tuffen, H., James, M. R., Castro, J. M. and Schipper, C. I. (2013) Exceptional mobility of an advancing rhyolitic obsidian flow at Cordón Caulle volcano in Chile, Nature Comms., 4, 2709, doi:10.1038/ncomms3709
James, M. R. and Quinton, J. (2013) Ultra-rapid topographic surveying for complex environments: The hand-held mobile laser scanner (HMLS), Earth Surf. Proc. Landforms, doi:10.1002/esp.3489
James, M. R. and Varley, N. (2012) Identification of structural controls in an active lava dome with high resolution DEMs: Volcán de Colima, Mexico, Geophys. Res. Letts., 39, L22303, 10.1029/2012GL054245
James, M. R., Applegarth, L. J. Pinkerton, H. (2012) Lava channel roofing, overflows, breaches and switching: insights from the 2008-2009 eruption of Mt. Etna, Bull. Volc., 1, 107-117, 10.1007/s00445-011-0513-9
Castillo, C., Pérez, R., James, M. R., Quinton, J. N., Taguas, E. V. and Gómez, J. A. (2012) Comparing the accuracy of several field methods for measuring gully erosion, Soil Sci. Soc. Am. J., 76, 1319-1332, 10.2136/sssaj2011.0390
James, M. R. and Robson, S. (2012) Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application, J. Geophys. Res., 117, F03017, 10.1029/2011JF002289
Niethammer U. , Rothmund S. , James M. R., Travelletti J. and Joswig, M. (2010) UAV-based remote sensing of landslides, Int. Arch. Photogram., Rem. Sens. Spatial Inf. Sci., Vol. XXXVIII, Part 5, Comm. V Symp., Newcastle upon Tyne, UK.,
Lava flowsIn fieldwork expeditions to Chile in 2012 and 2013, photographs were taken of an advancing rhyolite lava flow to produce 3D models of the flow surface. See a fly-by of one of the reconstructions, or interact with the 3D model. Rhyolite flows are relatively rare and this was the first time that we have been able to study an active flow. The models have shown intriging insights into how such flows advance (Tuffen et al. 2013).
Lava domesMonitoring changes in active lava domes is critical for quantifying their rates of growth and collapse. Photo-based surveys can be useful in order to obtain regular data from safe working distances. Although sparse point clouds can be constructed using manual point identification and photogrammetry techniques, SfM-MVS offers the potential to automate the process and generate detailed digital elevation models. James and Varley (2012) used such models to produce high resolution DEMs of Colima's dome that allowed mapping and analysis of structural features within the dome.
Soil erosion and gully formationAs part of a workshop in Cordoba, Spain, organised by José Gómez (IAS-CSIC), SfM-MVS was explored as a viable technique for quantifying soil loss during gully formation.
Carlos Castillo demonstrating a profilometer in the gully.
The topogaphic data acquired were compared with those from a laser scanner survey carried out at the same time. The SfM-MVS model was scaled and georeferenced using the MATLAB application sfm_georef. The results have been published as part of a study of the accuracy of field techniques used to measure gully erosion (Castillo et al., 2012).
Point cloud: low res (5 Mb)