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 km2 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 high-quality 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.
Highlights
Knowledge of changes in the extent, mass and surface velocity of glaciers and rock glaciers contributes to a better understanding of the dynamic processes occurring in cold high-mountain environments and serves as an important contribution to climate monitoring (Kääb et al, 2003)
The mean difference between the 2014 and 2013 structure from motion (SfM)–multi-view stereo (MVS) digital elevation models (DEMs) is 0.38 m (σ = 1.73 m), and the mean difference between the respective airborne laser scanning (ALS) DEMs is −0.09 m (σ = 0.29 m, Table 3). These results show that the photogrammetric survey conducted in 2014, using a higher number of camera positions and photographs and a slightly longer focal length, provided a significant improvement compared to the survey of 2013
In addition to the higher σ, the 2013 SfM–MVS DEM has a residual average bias of −0.42 m, which must be taken into account in the glacier mass balance calculations
Summary
Knowledge of changes in the extent, mass and surface velocity of glaciers and rock glaciers contributes to a better understanding of the dynamic processes occurring in cold high-mountain environments and serves as an important contribution to climate monitoring (Kääb et al, 2003). Fieldwork generally yields high-quality data but with a small spatial extent, given the remoteness and low accessibility of mountain areas at high elevations (Roer et al, 2007). Using remotely sensed data sets for at least two different points in time has become an important tool for monitoring highmountain terrain dynamics (Kääb, 2002). L. Piermattei et al.: Analysis of glacial and periglacial processes using SfM ital elevation models (DEMs) based on remote sensing data are the most commonly used products for such investigations (Kääb, 2005; Tseng et al, 2015)
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