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A workflow for classifying lakes from satellite imagery and compiling lake inventories

Project description

Investigating Greenland's ice marginal lakes under a changing climate (GrIML)

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The GrIML processing package for classifying water bodies from satellite imagery using a multi-sensor, multi-method remote sensing approach. This workflow is part of the ESA GrIML project, and this repository also holds all project-related materials.


The GrIML post-processing Python package can be installed using pip:

$ pip install griml

Or cloned from the Github repository:

$ git clone
$ cd GrIML
$ pip install .

Workflow outline

The GrIML workflow.

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 on 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 post-processing Python package, including raster-to-vector conversion, filtering, merging, metadata population, and statistical analysis.

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