FathomDEM: an improved global terrain map using a hybrid vision transformer model

FathomDEM: an improved global terrain map using a hybrid vision transformer model

The Earth’s terrain is linked to many physical processes, and gaining the most accurate representation is key to work in many sectors from engineering to natural hazards modeling and ecology. Existing global digital elevation models (DEMs) are widely used, however often suffer from systematic biases...

Full description

Saved in:
Bibliographic Details
Main Authors: Peter Uhe, Chris Lucas, Laurence Hawker, Malcolm Brine, Hamish Wilkinson, Anthony Cooper, Alex A Saoulis, James Savage, Christopher Sampson
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Letters
Subjects:
terrain
digital elevation model
machine learning
vision transformer
remote sensing
Online Access:https://doi.org/10.1088/1748-9326/ada972
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1088/1748-9326/ada972

Similar Items