DeltaDTM: A global coastal digital terrain model

Datacite citation style:
Pronk, Maarten (2023): DeltaDTM: A global coastal digital terrain model. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21997565.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version: version 3 - 2024-11-21 (latest) version 2 - 2024-03-06
version 1 - 2023-10-30
Delft University of Technology logo
usage stats
2980
views
11252
downloads
geolocation
Earth
time coverage
2012-2023
licence
cc-by.png logo CC BY 4.0

Coastal elevation data are essential for a wide variety of applications, such as coastal management, flood modelling, and adaptation planning. Low-lying coastal areas (found below 10 m +Mean Sea Level (MSL)) are at risk of future extreme water levels due to Sea Level Rise (SLR), subsidence and changing extreme weather patterns. However, current freely available elevation data sets are not sufficiently accurate to model these risks. We present DeltaDTM, a global coastal Digital Terrain Model (DTM) available in the public domain, with a horizontal spatial resolution of 30 m and a vertical mean absolute error (MAE) of 0.45 m overall. DeltaDTM corrects the CopernicusDEM with space borne lidar from the ICESat-2 and GEDI missions. Specifically, we correct the elevation bias in CopernicusDEM, apply filters to remove non-terrain cells, and fill the gaps using interpolation. Notably, our classification approach produces more accurate results than regression methods (including machine learning) recently used by others to correct DEMs, that achieve an overall MAE of 0.72 m at best. We conclude that DeltaDTM will be a valuable resource for coastal flood impact modelling and other applications.

history
  • 2023-10-30 first online, published, posted
publisher
4TU.ResearchData
format
Cloud Optimized GeoTiff (COG) as in .tif files, zipped per continent, with the mask .tif files in mask_tiles.zip. An overview of the tiles is given in the deltadtm_tiles.gpkg.
organizations
Deltares
TU Delft, Faculty of Architecture and the Built Environment, Department of Urban Data Science

DATA

files (12)