data tutorial added

docs/acknowledgements.md

@@ -1,3 +1,19 @@
-# Acknowledgements
+# Acknowledgements and links
 
-This project is supported by the ESA Living Planet Fellowship (4000136382/21/I-DT-lr) entitled "Examining Greenland's Ice Marginal Lakes under a Changing Climate". Further support is provided by [PROMICE](https://promice.org], funded by the [Geological Survey of Denmark and Greenland (GEUS)](https://www.geus.dk/) and the Danish Ministry of Climate, Energy and Utilities under the Danish Cooperation for Environment in the Arctic (DANCEA). 
+## Acknowledgements
+
+The inventory series of ice marginal lakes in Greenland has been produced as part of the European Space Agency (ESA) Living Planet Fellowship project "Examining GReenland’s Ice Marginal Lakes under a changing climate (GrIML)", which is a follow-on effort to the 2017 inventory of ice marginal lakes created under the European Space Agency (ESA) Climate Change Initiative (CCI) in Option 6 of the Glaciers_cci project (4000109873/14/I-NB). 
+
+Upkeep and continuation of the inventory series is supported by [PROMICE](https://promice.org], funded by the [Geological Survey of Denmark and Greenland (GEUS)](https://www.geus.dk/) and the Danish Ministry of Climate, Energy and Utilities under the Danish Cooperation for Environment in the Arctic (DANCEA), conducted in collaboration with DTU Space (Technical University of Denmark) and Asiaq Greenland Survey.
+
+
+## Relevant links
+
+- The GrIML code repository on [Github](https://github.com/GEUS-Glaciology-and-Climate/GrIML) and the code readme on [readthedocs](https://griml.readthedocs.io)
+- The ESA GrIML [project outline](https://eo4society.esa.int/projects/griml/) and [fellow information](https://eo4society.esa.int/lpf/penelope-how/)
+- Information about the [ESA Living Planet Fellowship](https://eo4society.esa.int/communities/scientists/living-planet-fellowship/)
+- The GrIML [project description](https://pennyhow.github.io/blog/investigating-griml/)
+- The original 2017 ice marginal lake inventory [Scientific Reports paper](https://www.nature.com/articles/s41598-021-83509-1) and [dataset](https://catalogue.ceda.ac.uk/uuid/7ea7540135f441369716ef867d217519)
+- The [MEaSUREs GIMP ice mask](https://nsidc.org/data/NSIDC-0714/versions/1) and associated publications, [Howat (2017)](https://doi.org/10.5067/B8X58MQBFUPA) and [Howat, Negrete and Smith (2014)](https://doi.org/10.5194/tc-8-1509-2014)
+- The [Oqaasileriffik placename database](https://asiaq.maps.arcgis.com/apps/View/index.html?appid=c5c7d9d52a264980a24911d7d33914b5)
+- QGreenland v3.0.0 dataset reference, [Moon et al. (2023)](https://doi.org/10.5281/zenodo.12823307)

docs/index.rst

@@ -6,14 +6,27 @@
 GrIML
 =====
 
-A Python package for classifying lakes and compiling lake inventories, under the GrIML project (Investigating Greenland's ice marginal lakes under a changing climate).
+The **GrIML** processing package is for classifying water bodies from satellite imagery using a multi-sensor, multi-method remote sensing approach. It has been used to produce the Greenland ice marginal lake inventory series, which maps the presence and extents of water bodies across Greenland that share a margin with the Greenland Ice Sheet and/or the surroudning ice caps and periphery glaciers since 2016. This workflow is part of the `ESA GrIML project <https://eo4society.esa.int/projects/griml/`_ (Investigating Greenland's ice marginal lakes under a changing climate).
+\
+If the GrIML package or the Greenland ice marginal lake inventory series are presented or used to support results of any kind, please include references to the applicable publications:
+
+- *How, P. et al. (2024) "Greenland Ice Marginal Lake Inventory annual time-series Edition 1". GEUS Dataverse. `https://doi.org/10.22008/FK2/MBKW9N <https://doi.org/10.22008/FK2/MBKW9N>`_*
+- *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 <https://doi.org/10.1038/s41598-021-83509-1>`_*
+- *How, P. et al. "Greenland ice marginal lake inventory series from 2016 to 2023". In Prep.*
+- *How, P. "A Python package for investigating Greenland's ice marginal lakes under a changing climate". In Prep.*
+
+And include the following statement in the acknowledgments:
+
+*"Ice marginal lake data provided by the European Space Agency (ESA), and the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) at the Geological Survey of Denmark and Greenland (GEUS) (`https://doi.org/10.22008/FK2/MBKW9N <https://doi.org/10.22008/FK2/MBKW9N>`_)."*
+
 
 .. toctree::
    :maxdepth: 2
    :caption: Contents:
 
    installation
-   tutorials
+   tutorials-processing
+   tutorials-data
    background
    contributing
    acknowledgments

docs/tutorial-data.md

@@ -0,0 +1,61 @@
+# Dataset tutorials
+
+The GrIML package is used for the production of the Greenland ice marginal lake inventory series, which is freely available through the [GEUS Dataverse](https://doi.org/10.22008/FK2/MBKW9N). This dataset is a series of annual inventories, mapping the extent and presence of lakes across Greenland that share a margin with the Greenland Ice Sheet and/or the surrounding ice caps and periphery glaciers. 
+
+Here, we will look at how to load and handle the dataset, and provide details on its contents.
+
+## Dataset contents
+
+This ice marginal lake dataset is a series of annual inventories, mapping the extent and presence of lakes across Greenland that share a margin with the Greenland Ice Sheet and/or the surrounding ice caps and periphery glaciers. The annual inventories provide a comprehensive record of all identified ice marginal lakes, which have been detected using three independent remote sensing techniques:
+
+- DEM sink detection using the ArcticDEM (mosaic version 3)
+- SAR backscatter classification from Sentinel-1 imagery
+- Multi-spectral indices classification from Sentinel-2 imagery
+
+All data were compiled and filtered in a semi-automated approach, using a modified version of the [MEaSUREs GIMP ice mask](https://nsidc.org/data/NSIDC-0714/versions/1) to clip the dataset to within 1 km of the ice margin. Each detected lake was then verified manually. The methodology is open-source and provided in the associated [Github repository](https://github.com/GEUS-Glaciology-and-Climate/GrIML) for full reproducibility.
+
+The inventory series was created to better understand the impact of ice marginal lake change on the future sea level budget and the terrestrial and marine landscapes of Greenland, such as its ecosystems and human activities. The dataset is a complete inventory series of Greenland, with no absent data.
+
+### Data format
+
+The detected lakes are presented as polygon vector features in shapefile format (.shp), with coordinates provided in the WGS NSIDC Sea Ice Polar Stereographic North (EPSG:3413) projected coordinate system.
+
+### Metadata
+
+Each inventory in the inventory series contains the following metadata information:
+
+| Variable name       | Description         | Format | 
+|---------------------|---------------------|---------|
+| `row_id`  	| Index identifying number for each polygon   | Integer  |
+| `lake_id` 	| Identifying number for each unique lake  	| Integer  |
+| `lake_name`| Lake placename, as defined by the [Oqaasileriffik (Language Secretariat of Greenland)](https://oqaasileriffik.gl) placename database which is distributed with [QGreenland](https://qgreenland.org/)  | String   |
+| `margin`	| Type of margin that the lake is adjacent to (`ICE_SHEET`, `ICE_CAP`)   | String |
+| `region`	| Region that lake is located, as defined by Mouginot and Rignot (2019) (`NW`, `NO`, `NE`, `CE`, `SE`, `SW`, `CW`)       	| String |
+| `area_sqkm`	| Areal extent of polygon/s in square kilometres  | Float |
+| `length_km`	| Length of polygon/s in kilometres         		| Float |
+| `temp_aver`	| Average lake surface temperature estimate (in degrees Celsius), derived from the Landsat 8/9 OLI/TIRS Collection 2 Level 2 surface temperature data product  | Float |
+| `temp_min`	| Minimum pixel lake surface temperature estimate (in degrees Celsius), derived from the Landsat 8/9 OLI/TIRS Collection 2 Level 2 surface temperature data product  | Float |
+| `temp_max`	| Maximum pixel lake surface temperature estimate (in degrees Celsius), derived from the Landsat 8/9 OLI/TIRS Collection 2 Level 2 surface temperature data product  | Float |
+| `temp_stdev`	| Average lake surface temperature estimate standard deviation, derived from the Landsat 8/9 OLI/TIRS Collection 2 Level 2 surface temperature data product  | Float |
+| `method`		| Method of classification (`DEM`, `SAR`, `VIS`)  | String |
+| `source`     | Image source of classification (`ARCTICDEM`, `S1`, `S2`)    | String  |
+| `all_src`     | List of all sources that successfully classified the lake (i.e. all classifications with the same `lake_name` value)  | String         |
+| `num_src`          | Number of sources that successfully classified the lake (`1`, `2`, `3`)     | String | 
+| `certainty`     | Certainty of classification, which is calculated from `all_src` as a score between `0` and `1`          | Float | -                             |
+| `start_date` | Start date for classification image filtering 	| String  |
+| `end_date` 	| End date for classification image filtering     | String |
+| `verified` | Flag to denote if the lake has been manually verified (`Yes`, `No`)   | String |
+| `verif_by`  | Author of verification | String  |
+| `edited`  | Flag to denote if polygon has been manually edited (`Yes`, `No`)  | String   |
+| `edited_by` | Author of manual editing   | String  |
+
+## Getting started
+
+Loading the dataset: Data available at [GEUS Dataverse](https://doi.org/10.22008/FK2/MBKW9N).
+
+Quicklook plotting of the dataset
+
+
+## Generating statistics
+
+Extracting statistics

docs/tutorials.md → docs/tutorials-processing.md

@@ -1,4 +1,4 @@
-# Tutorials
+# Processing tutorials
 
 The following tutorial steps make up the full workflow for post-processing of raster classifications to a compiled, production-ready inventory of ice marginal lakes.