IceBoost - a Gradient Boosted Tree global framework for glacier ice thickness retrieval ...
The repository contains: IceBoost model (.json file). Training datasets (.csv), in 2 versions: RAW and spatially downscaled. An example of IceBoost inference: a detail of the modeled ice distribution of the Yanatsugat glacier (RGI60-14-06580), Karakoram range. Comparisons between IceBoost and other...
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| Format: | Article in Journal/Newspaper |
| Language: | English |
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Zenodo
2024
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| Online Access: | https://dx.doi.org/10.5281/zenodo.12791380 https://zenodo.org/doi/10.5281/zenodo.12791380 |
| Summary: | The repository contains: IceBoost model (.json file). Training datasets (.csv), in 2 versions: RAW and spatially downscaled. An example of IceBoost inference: a detail of the modeled ice distribution of the Yanatsugat glacier (RGI60-14-06580), Karakoram range. Comparisons between IceBoost and other two models, on 10 selected glaciers for each one of the 19 regions of the Randolph Glacier Inventory v.6 (.zip archive), alongside a .csv file listing the ids of the compared glaciers. In all comparisons: Model 1 refers to Millan et al. (2022), or BedMachine Greenland/Antarctica (if applicable). Model 2 refers to Farinotti et al. (2019). BedMachine Greenland v5: Morlighem, M. et al (2022). BedMachine Antarctica v3: Morlighem, M. et al (2022). All colorbars are tied to the IceBoost output, therefore the other two models may appear in saturated colors. The big circles (if any) reflect the ice thickness measurements from GlaThiDa v. 3.1.0. IceBoost is actively developed on Github: iceboost repository. ... |
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