http://bolin.su.se/data/schytt-mannerfelt-2022-marma-dem-1 Erik Schytt Mannerfelt Bolin Centre Database 2022 Datafile Terrestrial Glaciers Glacier DEM Digital Elevation Model Aerial Helicopter Lidar Grid Elevation Geodetic mass balance Mårma Sweden Tarfala Research Station Earth science > Cryosphere > Glaciers/ice sheets > Glaciers Erik Schytt Mannerfelt 2022-12-02T12:23:29+00:00 English 1 The six DEMs have been assimilated from multiple sources. They have been homogenised, bias-corrected and uncertainty assessed following a state-of-the-art workflow as of 2022. | **Date** | **Data source** | **Surveyed by** | **Processed by** | | -------|-----------------|-------------------|-------------------| | 1959-09-23 | Aerial nadir photographs | Lantmäteriet | Lantmäteriet | | 1978-07-21 | Aerial nadir photographs | Lantmäteriet | Lantmäteriet | | 1991-07-31 | Aerial nadir photographs | Lantmäteriet | Lantmäteriet | | 2008-09-10 | Aerial nadir photographs | Lantmäteriet | Lantmäteriet | | 2016-09-17 | Airborne laser scanning | Lantmäteriet | Lantmäteriet | | 2021-08-10 | Helicopter oblique photographs | Erik Schytt Mannerfelt | Erik Schytt Mannerfelt | ##### Data preparation The 1959⁠ – 2008 DEMs were originally prepared for the publication by [Holmlund et al. (2016)](https://www.stralsakerhetsmyndigheten.se/publikationer/rapporter/avfall--transport--fysiskt-skydd/2016/201621/), based on data from Lantmäteriet. Those DEMs were provided by Per Holmlund, Department of Physical Geography, Stockholm University, as finished gridded DEMs in 10x10 m ASCII formatted grids. They were then translated to GeoTiffs and cropped to the same extent. The 2016 DEM was derived from lidar point data by Lantmäteriet as a finished GeoTiff, and was cropped and resampled (using cubic spline interpolation) to the same grid as the 1959–2008 DEMs. It was retrieved from the [SLU GET service](https://zeus.slu.se/get), which is managed by the [The Swedish University of Agricultural Sciences](https://www.slu.se/en/) and is available to staff and students at Swedish universities. The 2021 DEM was created in Agisoft Metashape Pro version 1.7.1 by Erik Schytt Mannerfelt. A total of 98 images were collected using a Nikon D800 digital single-lens reflex camera with a 50 mm lens from a helicopter, with images captured in a concentric pattern from 200–900 metres above the ground. Ground control points (GCPs) were derived from the 2016 lidar DEM, used as a reference, in 15 well-dispersed locations. The root mean square residual error of the GCPs was 0.84 m. A dense cloud was reconstructed, and a DEM generated from the dense cloud. The DEM contained gaps which were interpolated in a subsequent processing step. ##### Data homogenisation The six DEMs, now in the same grid, coordinate reference system and resolution, had horizontal and vertical shifts that needed correction. In addition, the 2021 DEM had gaps that required interpolation. The *[xdem](https://xdem.readthedocs.io/en/latest/)* python package was used to co-register (align) the DEMs, using the 2016 lidar DEM as the reference. Glacier and snow masks were delineated ([available as a separate dataset](https://bolin.su.se/data/schytt-mannerfelt-2022-marma-outlines-1)) to extract a stable terrain mask, and co-registration was performed on only the terrain outside of these areas. The [Nuth and Kääb (2011)](https://doi.org/10.5194/tc-5-271-2011) co-registration approach in *xdem* was used. Using the co-registered DEMs, elevation change (dH) maps were generated by subtracting each sequential DEM with its latter counterpart. The 2016–2021 dH map was interpolated using bilinear spatial interpolation, resulting in a spatially gap-free dH map. A gap-free 2021 DEM was subsequently generated by adding the 2016–2021 dH map with the 2016 DEM (c.f. *interpolation of elevation differences*; [McNabb et al. 2019](https://doi.org/10.5194/tc-13-895-2019)). ##### Uncertainty assessment The uncertainty in elevation change (dH) at different spatial scales was estimated by fitting double-spherical variogram models to each individual dH map (c.f. [Hugonnet et al. 2021](https://doi.org/10.1038/s41586-021-03436-z)). These variograms show at which scales uncertainties are correlated, and allows to account for both short- and long-range correlations when integrating the mean elevation change and the uncertainty thereof over a glacier. ##### Data structure One version of the 1959–2016 DEMs and two versions of the 2021 DEM are supplied as `GeoTiff` raster files. They can be read in software like QGIS, ArcGIS, rasterio, or any other GDAL wrapper. The DEMs are in the SWEREF99 TM (EPSG:3006) coordinate reference system, with the RH 2000 (EPSG:5613) vertical datum. In addition, the variograms and integrated-area-vs.-uncertainty tables are given, to properly derive volume changes from the DEMs. Two image files (JPEG raster data) that illustrate the data are also included. ##### Filenames and content - `Marma_DEM_1959.tif`: DEM of the Mårma massif from 1959 - `Marma_DEM_1978.tif`: DEM of the Mårma massif from 1978 - `Marma_DEM_1991.tif`: DEM of the Mårma massif from 1991 - `Marma_DEM_2008.tif`: DEM of the Mårma massif from 2008 - `Marma_DEM_2016.tif`: DEM of the Mårma massif from 2016 - `Marma_DEM_2021.tif`: DEM of the Mårma massif from 2021 with gaps - `Marma_DEM_2021_interp.tif`: Interpolated DEM of the Mårma massif from 2021 - `dH_variograms.csv`: Empirical variograms for each dH map (1959–1978, 1978–1991, etc.; the `product` column), showing the variance (in m; `exp`) and the empirical spread (in m; `err_exp`) as a function of spatial lag (in m; `bins`). - `dH_integration_uncertainty.csv`: The uncertainty in elevation change (dH) as a function of integrated area (in m²; `integration_area`). This is using the assumption that the integrated area is circular (c.f. [Hugonnet et al. 2021](https://doi.org/10.1038/s41586-021-03436-z)). - `marma_dh_maps.jpg`: Maps showing elevation changes between the DEM timepoints - `marma_integrated_area_uncertainty.jpg`: Graphs showing uncertainties in the elevation changes [The source code for the analysis](https://git.bolin.su.se/bolin/schytt-mannerfelt-2022-marma) has been made available by Schytt Mannerfelt (2022). [Geodetic mass balance derivations from the DEMs](https://bolin.su.se/data/schytt-mannerfelt-2022-marma-geodetic-1) are available as a separate dataset. Erik Schytt Mannerfelt was affiliated with the Department of Physical Geography, Stockholm University, when this dataset was prepared.