GrIML - Investigating Greenland's ice-marginal lakes under a changing climate
The GrIML (Investigating Greenland's ice marginal lakes under a changing climate) processing package for classifying water bodies from satellite imagery using a multi-sensor, multi-method remote sensing approach. This workflow is used for the production of the Greenland ice-marginal lake inventory series, as part of the ESA GrIML project. This repository also holds all project-related materials.
Installation
The GrIML Python package can be installed using pip:
$ pip install griml
Or cloned from the Github repository:
$ git clone git@github.com:GEUS-Glaciology-and-Climate/GrIML.git
$ cd GrIML
$ pip install .
Full documentation and tutorials are available at GrIML's readthedocs
Workflow outline
GrIML proposes to examine ice marginal lake changes across Greenland using a multi-sensor and multi-method remote sensing approach to better address their influence on sea level contribution forecasting.
Ice-marginal lakes are detected using a remote sensing approach, based on offline workflows developed within the ESA Glaciers CCI (Option 6, An Inventory of Ice-Marginal Lakes in Greenland) (How et al., 2021). Initial classifications are performed using Google Earth Engine, with the scripts available here. Lake extents are defined through a multi-sensor approach using:
- Multi-spectral indices classification from Sentinel-2 optical imagery
- Backscatter classification from Sentinel-1 SAR (synthetic aperture radar) imagery
- Sink detection from ArcticDEM digital elevation models
Post-processing of these classifications is performed using the GrIML Python package, including raster-to-vector conversion, filtering, merging, metadata population, and statistical analysis.
Terms of use
If the workflow or data are presented or used to support results of any kind, please include an acknowledgement and references to the applicable publications:
How, P. et al. (2025) "Greenland Ice-Marginal Lake Inventory annual time-series Edition 1". GEUS Dataverse. https://doi.org/10.22008/FK2/MBKW9N
How, P. et al. (In Review) "Greenland ice-marginal lake inventory series from 2016 to 2023". Earth Syst.Sci. Data Discuss. https://doi.org/10.5194/essd-2025-18
How, P. (2025). "GrIML: A Python package for investigating Greenland's ice-marginal lakes under a changing climate". J. Open Source Software 10(111), 7927, https://doi.org/10.21105/joss.07927
How, P. et al. (2021) "Greenland-wide inventory of ice marginal lakes using a multi-method approach". Sci. Rep. 11, 4481. https://doi.org/10.1038/s41598-021-83509-1
Project links
-
The Greenland ice-marginal lake inventory series, available through the GEUS Dataverse
-
ESA project outline and fellow information
-
Information about the ESA Living Planet Fellowship
-
2017 ice marginal lake inventory Scientific Reports paper and dataset
Release files for griml 1.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| griml-1.0.6.tar.gz | 28.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| griml-1.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 74.6 kB
Release files / griml-1.0.6.tar.gz
| Download URL | griml-1.0.6.tar.gz |
|---|---|
| Size | 28.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a1ef86f93a997298c16e14eca88a7c80dd5f4c7eec418471a525ed23fac9ed04
|
|
BLAKE2b-256 checksum How to use checksums |
8b028e6bd14db2f11668a3eebef98ec409050c43eb4cbb24eb07f02fbe33edd4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.25
|
Release files / griml-1.0.6-py3-none-any.whl
| Download URL | griml-1.0.6-py3-none-any.whl |
|---|---|
| Size | 45.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8321eb4a4f6062313243593565ebc891d7b16bf2b20dc160f8689b9e894e56fe
|
|
BLAKE2b-256 checksum How to use checksums |
ad08c8b25edc5b6e5519a73fcda7f58e7fe9271cfe2d9a1b64074ca0410df961
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.9.25
|