Abstract
In this study, we use Pléiades tri-stereo data to generate a digital elevation model (DEM) from the Pléiades images using a workflow employing semi-global matching (SGM). We examine the DEM accuracy in complex mountain glaciated terrain by comparing the new DEMs with an independent high-quality DEM based on airborne laser scanning (ALS) data for a study area in the Austrian Alps, and with ground control points for a study area in the Khumbu Himal of Nepal. The DEMs derived using the SGM algorithm compare well to the independent high-quality ALS DEM, and the workflow produces models of sufficient quality to resolve ground control points, which are based on Pléiades imagery that are of sufficient quality to perform high spatio-temporal resolution assessments of remote areas for which no field data is available. The relative accuracy is sufficient to investigate glacier surface elevation changes below one meter, and can therefore be applied over relatively short periods of time, such as those required for annual and seasonal assessments of change. The annual geodetic mass balance for the Alpine case derived from our DEM compares well to the glaciological mass balance, and multitemporal DEM analysis is used to resolve the seasonal changes of five glaciers in the Khumbu Himal, revealing that glaciological processes such as accumulation, ablation, and glacier movement mainly take place during the summer season, with the winter season being largely inactive in the year sampled.
Highlights
In recent years, the increasing availability and quality of satellite data has stimulated an expansion in the applications of satellite remote sensing to glaciological problems
Applications of satellite optical imagery in glaciology can be split into three main categories: (i) the derivation of digital elevation models (DEMs) from which volume changes and mass movements can be determined via DEM differencing, (ii) the identification of surface features based on optical properties, and (iii) the computation of glacier movement rates using image matching
Of particular interest is the acquisition of glaciological information from poorly understood parts of the mountain cryosphere such as the mountains of high Asia where DEMs constructed from satellite imagery (e.g., ASTER, SRTM, SPOT5, Indian Remote Sensing Satellite (IRS-1C), or CORONA) are increasingly being used for glaciological studies
Summary
The increasing availability and quality of satellite data has stimulated an expansion in the applications of satellite remote sensing to glaciological problems. Of particular interest is the acquisition of glaciological information from poorly understood parts of the mountain cryosphere such as the mountains of high Asia where DEMs constructed from satellite imagery (e.g., ASTER, SRTM, SPOT5, Indian Remote Sensing Satellite (IRS-1C), or CORONA) are increasingly being used for glaciological studies. The most readily available sources of remote sensing-derived elevation data over the Himalayas is currently still the SRTM DEM version 3, but ASTER and Corona DEMs have been used in recent glaciological studies in the Nepal and Bhutan Himalaya, e.g., Bolch et al [1] and Nuimura et al [2]. Several studies focused on evaluating DEMs from stereo satellite data: Berthier et al [4] compared SRTM elevations with SPOT5-derived elevations on non-glaciated terrain, while Bélart et al [5] used WorldView and Pléiades data to investigate the winter mass balance of the Drangajökull ice cap in Iceland. Developments in optical satellite remote sensing have led to a limited number of very-high resolution sensors, represented by IKONOS, QuickBird, OrbView-3, SPOT-5, Worldview 1–4, GeoEye, and the Pléiades twins
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