The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km² of glacier area in southeast Alaska, USA, covered by two void free DEMs as study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier-Stokes and Shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric method) void filling approaches for glacier elevation data sets were implemented and evaluated.
The provided database contains the void filling results of all different approaches and setups (see paper for abbreviations of the approaches). Moreover, the void free elevation change field and void masks are provided to redo the statistical analysis and to apply the novel inpainting techniques at the "Center"-setup. The code to carry out the void filling and analysis can be downloaded here: https://github.com/tseehaus/inpainting-dhdt
For each setup a zip-file is provided containing relevant input data and the generated void-filled results. More details can be found in the readme.pdf file.
