DeltaDTM: A global coastal digital terrain model.

Area of Science:

• Geosciences
• Remote Sensing
• Coastal Studies

Background:

• Accurate coastal elevation data are critical for coastal management, flood modeling, and adaptation planning.
• Low-lying coastal areas face risks from rising sea levels, subsidence, and extreme weather.
• Existing freely available elevation datasets lack the necessary accuracy for precise risk assessment.

Purpose of the Study:

• To introduce DeltaDTM, a novel global coastal Digital Terrain Model (DTM).
• To provide a publicly accessible elevation dataset with high spatial resolution and improved vertical accuracy.
• To enhance the capability for modeling coastal risks and impacts.

Main Methods:

• DeltaDTM was created by correcting the CopernicusDEM using spaceborne lidar data from ICESat-2 and GEDI missions.
• Elevation bias in CopernicusDEM was corrected, non-terrain cells were filtered, and gaps were filled via interpolation.
• A classification approach was employed for DEM correction, outperforming recent regression methods.

Main Results:

• DeltaDTM offers a horizontal spatial resolution of 1 arcsecond (approximately 30m).
• The model achieves a vertical Mean Absolute Error (MAE) of 0.45m, significantly better than existing methods (best MAE of 0.72m).
• The classification approach proved more accurate than regression-based DEM correction techniques.

Conclusions:

• DeltaDTM represents a valuable, publicly available resource for coastal applications.
• The improved accuracy of DeltaDTM will significantly benefit coastal flood impact modeling.
• This dataset will support more effective coastal management and adaptation planning.