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7 changes: 4 additions & 3 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ The **GrIML** processing package for classifying water bodies from satellite ima

## Installation

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

```
$ pip install griml
Expand All @@ -21,16 +21,17 @@ $ pip install .

## Workflow outline

<img src="https://github.com/PennyHow/pennyhow.github.io/blob/master/assets/images/griml_workflow.png?raw=true" alt="The GrIML workflow." width="1500" align="aligncenter" />
<img src="https://github.com/PennyHow/GrIML/blob/main/other/reporting/figures/griml_workflow_with_gee.png?raw=true" alt="The GrIML workflow." width="1500" align="aligncenter" />

**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](https://catalogue.ceda.ac.uk/uuid/7ea7540135f441369716ef867d217519") (Option 6, An Inventory of Ice-Marginal Lakes in Greenland) ([How et al., 2021](https://www.nature.com/articles/s41598-021-83509-1)). Lake extents are defined through a multi-sensor approach using:
Ice marginal lakes are detected using a remote sensing approach, based on offline workflows developed within the [ESA Glaciers CCI](https://catalogue.ceda.ac.uk/uuid/7ea7540135f441369716ef867d217519") (Option 6, An Inventory of Ice-Marginal Lakes in Greenland) ([How et al., 2021](https://www.nature.com/articles/s41598-021-83509-1)). Initial classifications are performed on Google Earth Engine with the scripts available [here](https://github.com/PennyHow/GrIML/tree/main/gee_scripts). 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.

## Project links

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