Suitability of ground-based SfM–MVS for monitoring glacial and periglacial processes

Abstract

Abstract. Photo-based surface reconstruction is rapidly emerging as an alternative survey technique to lidar (light detection and ranging) in many fields of geoscience fostered by the recent development of computer vision algorithms such as structure from motion (SfM) and dense image matching such as multi-view stereo (MVS). The objectives of this work are to test the suitability of the ground-based SfM-MVS approach for calculating the geodetic mass balance of a 2.1 km 2 glacier and for detecting the surface displacement of a neighbouring active rock glacier located in the eastern Italian Alps. The photos were acquired in 2013 and 2014 using a digital consumer-grade camera during single-day field surveys. Airborne laser scanning (ALS, otherwise known as airborne lidar) data were used as benchmarks to estimate the accuracy of the photogrammetric digital elevation models (DEMs) and the reliability of the method. The SfM-MVS approach enabled the reconstruction of highquality DEMs, which provided estimates of glacial and periglacial processes similar to those achievable using ALS. In stable bedrock areas outside the glacier, the mean and the standard deviation of the elevation difference between the SfM-MVS DEM and the ALS DEM was −0.42 ± 1.72 and 0.03 ± 0.74 m in 2013 and 2014, respectively. The overall pattern of elevation loss and gain on the glacier were similar with both methods, ranging between −5.53 and + 3.48 m. In the rock glacier area, the elevation difference between the SfM-MVS DEM and the ALS DEM was 0.02 ± 0.17 m. The SfM-MVS was able to reproduce the patterns and the magnitudes of displacement of the rock glacier observed by the ALS, ranging between 0.00 and 0.48 m per year.The use of natural targets as ground control points, the occurrence of shadowed and low-contrast areas, and in particular the suboptimal camera network geometry imposed by the morphology of the study area were the main factors affecting the accuracy of photogrammetric DEMs negatively. Technical improvements such as using an aerial platform and/or placing artificial targets could significantly improve the results but run the risk of being more demanding in terms of costs and logistics.

Frontiers in Geomorphometry and Earth Surface Dynamics: possibilities, limitations and perspectives

“…The work by Piermattei et al (2016) demonstrates the advantages and potential of SfM to calculate the geodetic mass balance of glacier in the Ortles-Cevedale Group, Eastern Italian Alps. In addition, they investigated the feasibility of using the image-based approach for the detection of the surface displacement rate of an active rock glacier.…”

“…Wickert, 2016 Multitemporal data set to evaluate erosion patterns: Loye et al, 2016;Bechet et al, 2015; SfM for glacial processes: Westoby et al, 2016;Piermattei et al, 2016 graphic data type, which vary depending on the objectives of the analysis; often significant weaknesses or methodological limitations exist, which prevent us from gaining the insights into processes that we otherwise might. The interdisciplinarity of geomorphometry is its greatest strength and also one of its major challenges.…”

Multi-Annual Kinematics of an Active Rock Glacier Quantified from Very High-Resolution DEMs: An Application-Case in the French Alps

“…In addition, their repetitivity can be annual or even at smaller time intervals, mostly depending on the terrain characteristics and the range of surface velocities. So far, these methods have rarely been used for rock glacier studies [17][18][19][20], and no investigations have yet addressed the potential of those methods for long-term monitoring of the surface kinematics.…”

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards

“…The images acquired were processed using the commercial software Agisoft PhotoScan®, as already successfully considered in different analyses (Doneus et al, 2011;Javernick et al, 2014;Piermattei et al, 2016;Prosdocimi et al, 2015;Verhoeven et al, 2012;Woodget et al, 2015). A custom algorithm similar to the Lowe's (2004) Scale Invariant Feature Transform (SIFT) object recognition system was used by the software to determine the 3D location of matching features in multiple images.…”

“…Remote-sensing technologies have proven to facilitate significantly the creation of high-resolution DEMs (Aucelli et al, 2016;Tarolli, 2014;Tarolli et al, 2015), and the availability of DEMs at multiple scales in terms of resolution but also temporal coverage is becoming essential to the understanding of global issues, such sediment production and anthropogenic changes to the Earth system, among others . The recent development of the photogrammetric technique 'Structure-from-Motion' (SfM) has confirmed to represent a valid and cheaper alternative to the established airborne and terrestrial lidar (Light Detection and Ranging) technology for measuring soil surface changes in different environments (Dandois and Ellis, 2013;Eltner et al, 2015;James and Robson, 2012;Masiero et al, 2015;Piermattei et al, 2016;Westoby et al, 2012;Whitehead et al, 2013;Woodget et al, 2015). All this information can shed light into the connectivity within the soil and water losses (López-Vicente et al, 2016;Marchamalo et al, 2016;Masselink et al, 2016).…”