IceBoost v2.0 Regional Merged Mosaics for RGI v6.0 and RGI v7.0
Abstract
This repository contains the IceBoost v2.0 regional merged mosaics for Randolph Glacier Inventory (RGI) v6.0 and v7.0. RGI v.6: regional folders from 1 to 19. RGI v.7: regional folders from 1 to 19. Each .tif file contains the distributed ice thickness of all glaciers merged together. The files have the following format: iceboost_20251009_rgixx_vyy_epsg_zzzz.tif - xx: value from 1 to 19- yy: 62 for RGI6 or 70G for RGI7.- zzzz: epsg regional code. (example iceboost_20251009_rgi4_v70G_epsg_32617.tif). File Data layers: IceBoost v2.0-modeled ice thickness Monte Carlo-modeled ice thickness uncertainty Jensen Gap Surface Elevation (TanDEM-X Edited DEM v1, more info here) Geoid Height (EIGEN-6C4 gravity field) Data type: float32.CRS: coordinates, measured in meters within a specific UTM zone.Spatial resolution: 100 meters.Nodata: np.nan File Attributes: Ice volume (with uncertainty): complex ice volume (with uncertainty). Ice volume below sea level (with uncertainty): complex ice volume below sea level (with uncertainty). Area: complex area. Ice thickness measurements contained within the complex, if any: latitude, longitude, ice thickness. Note: individual glaciers may be produced with a finer resolution than 100 meters. The merged mosaics, however, are generated at a fixed 100 meter resolution. For smaller glaciers we refer the users to the individual glacier product at https://zenodo.org/records/17724512. =============== Additional references: Randolph Glacier Inventory: https://www.glims.org/rgi_user_guide/welcome.html To download individual glacier files: see https://zenodo.org/records/17724512 To download the training datasets, the trained model: see https://zenodo.org/records/17724512 IceBoost Web Visualizer at: https://nmaffe.github.io/iceboost_webapp/ IceBoost code on Github at: https://github.com/nmaffe/iceboost ===============
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 30 May 2026
- Language
- EN
- Document type
- Dataset