Paper updates

paper/paper.bib

@@ -1,4 +1,32 @@
 
+@article{carrivick_ice-marginal_2022,
+	title= {{Ice-Marginal} {Proglacial} {Lakes} across {Greenland}: Present status and a possible future},
+	volume={49},
+	url= {https://doi.org/10.1029/2022GL099276},
+	doi= {10.1029/2022GL099276},
+	number={12},
+	language = {en},
+	urldate = {2022-06-06},
+	journal = {Geophysical Research Letters},
+	author = {Carrivick, Jonathan L. and How, Penelope and Lea, James. M. and Sutherland, Jenna L. and Grimes, M. and Tweed, Fiona S. and Cornford, S. and Quincey, Duncan J. and Mallalieu, J.},
+	month = jun,
+	year = {2022},
+	pages = {e2022GL099276},
+}
+
+@article{wiesmann_2017_2021,
+	title= {ESA Glaciers Climate Change Initiative (Glaciers_cci): 2017 inventory of ice marginal lakes in Greenland (IIML)},
+	volume={v1},
+	url= {https://dx.doi.org/10.5285/7ea7540135f441369716ef867d217519},
+	doi= {10.5285/7ea7540135f441369716ef867d217519},
+	language = {en},
+	urldate = {2021-02-19},
+	journal = {Centre for Environmental Data Analysis},
+	author = {Wiesmann, A. and Santoro, M. and Caduff, R. and How, P. and Messerli, A. and Mätzler, E. and Langley, K. and Høegh Bojesen, M. and Paul, F. and Kääb, A.M.},
+	month = feb,
+	year = {2021},
+}
+
 @article{wilkinson_fair_2016,
 	title = {The {FAIR} {Guiding} {Principles} for scientific data management and stewardship},
 	volume = {3},
@@ -17,7 +45,6 @@ @article{wilkinson_fair_2016
 	note = {Publisher: Nature Publishing Group},
 	keywords = {Publication characteristics, Research data},
 	pages = {160018},
-	file = {Full Text PDF:/home/pho/Zotero/storage/2YD97CTA/Wilkinson et al. - 2016 - The FAIR Guiding Principles for scientific data ma.pdf:application/pdf},
 }
 
 @article{how_greenland-wide_2021,
@@ -38,7 +65,6 @@ @article{how_greenland-wide_2021
 	note = {Publisher: Nature Publishing Group},
 	keywords = {Cryospheric science, Hydrology},
 	pages = {4481},
-	file = {Full Text PDF:/home/pho/Zotero/storage/48EXCPRT/How et al. - 2021 - Greenland-wide inventory of ice marginal lakes usi.pdf:application/pdf},
 }
 
 @article{shugar_rapid_2020,
@@ -61,6 +87,35 @@ @article{shugar_rapid_2020
 	pages = {939--945},
 }
 
+@software{wehrle_earthspy_2023,
+	title = {earthspy},
+	url = {https://github.com/AdrienWehrle/earthspy},
+	language = {English},
+	number = {v0.3.0},
+	journal = {The Cryosphere},
+	author = {Wehrle, A.},
+	year = {2023},
+}
+
+@software{kelsey_geopandas_2020,
+  author       = {Kelsey Jordahl and Joris Van den Bossche and Martin Fleischmann and Jacob Wasserman and James McBride and Jeffrey Gerard and Jeff Tratner and Matthew Perry and Adrian Garcia Badaracco and Carson Farmer and Geir Arne Hjelle and Alan D. Snow and Micah Cochran and Sean Gillies and Lucas Culbertson and Matt Bartos and Nick Eubank and maxalbert and Aleksey Bilogur and Sergio Rey and Christopher Ren and Dani Arribas-Bel and Leah Wasser and Levi John Wolf and Martin Journois and Joshua Wilson and Adam Greenhall and Chris Holdgraf and Filipe and François Leblanc},
+  title        = {geopandas/geopandas: v0.8.1},
+  month        = jul,
+  year         = 2020,
+  publisher    = {Zenodo},
+  version      = {v0.8.1},
+  doi          = {10.5281/zenodo.3946761},
+  url          = {https://doi.org/10.5281/zenodo.3946761}
+}
+
+@software{gillies_rasterio_2019,
+  author =    {Sean Gillies and others},
+  organization = {Mapbox},
+  title =     {Rasterio: geospatial raster I/O for {Python} programmers},
+  year =      {2013--},
+  url = "https://github.com/rasterio/rasterio"
+}
+
 @article{rick_dam_2022,
 	title = {Dam type and lake location characterize ice-marginal lake area change in {Alaska} and {NW} {Canada} between 1984 and 2019},
 	volume = {16},
@@ -77,5 +132,4 @@ @article{rick_dam_2022
 	year = {2022},
 	note = {Publisher: Copernicus GmbH},
 	pages = {297--314},
-	file = {Full Text PDF:/home/pho/Zotero/storage/SW8L4RIG/Rick et al. - 2022 - Dam type and lake location characterize ice-margin.pdf:application/pdf},
 }

paper/paper.md

@@ -20,13 +20,14 @@ bibliography: paper.bib
 
 ---
 
+
 # Summary
 
 The `GrIML` Python package is for the post-processing of classified water bodies from satellite imagery. Initial rasterised binary classifications denoting water bodies can be inputted to `GrIML` to convert, filter and merge into a cohesive ice marginal lake vector dataset, populated with useful metadata and analysed with relevant statistical information (\autoref{fig:workflow}).
 
 ![An overview of the GrIML Python package workflow \label{fig:workflow}](https://github.com/PennyHow/GrIML/blob/main/other/reporting/figures/griml_workflow_without_gee.png?raw=true)
 
-This package is part of the [ESA GrIML project](https://eo4society.esa.int/projects/griml/) (Investigating Greenland's ice marginal lakes under a changing climate), whose aim is to map and monitor ice marginal lakes across Greenland through a series of annual ice marginal lake inventories (2016-2023). This workflow was used to make the inventory series, and will continue to be used to generate inventories in the future.
+This package is part of the [ESA GrIML project](https://eo4society.esa.int/projects/griml/) (Investigating Greenland's ice marginal lakes under a changing climate), whose aim is to map and monitor ice marginal lakes across Greenland through a series of annual ice marginal lake inventories (2016-2023). In 2017, 3347 ice marginal lakes were identified in Greenland along the ice margin [@how_greenland-wide_2021;wiesmann_2017_2021]. Globally, these ice marginal lakes hold up to 0.43 mm of sea level equivalent, which could have a marked impact on future predictions [@shugar_rapid_2020;@carrivick_ice-marginal_2022]. Therefore, they need to be monitored to understand how changes in ice marginal lake water storage affect melt contribution, and how their dynamics evolve under a changing climate. The GrIML workflow was used to make the 2017-2023 inventory series, and will continue to be used to generate inventories in the future.
 
 
 # Statement of need
@@ -38,31 +39,18 @@ This package is part of the [ESA GrIML project](https://eo4society.esa.int/proje
 3. Showcase a transparent workflow that, in turn, produces an open and reproducible ice marginal lake dataset that adheres to the FAIR principles [@wilkinson_fair_2016]
 4. Produce inventories that map the areal extent and frequency of ice marginal lakes across Greenland, which demonstrate ice marginal lake evolution under a changing cliamte
 
-
-- Many different approaches to classifying ice marginal lakes [@shugar_rapid_2020;@rick_dam_2022]
-- Previously this workflow was a closed method [@how_greenland-wide_2021]
-
-
-Sea level is predicted to rise drastically by 2100, with significant contribution from the melting of the Greenland Ice Sheet (GrIS). In these predictions, melt runoff is assumed to contribute directly to sea level change, with little consideration for meltwater storage at the terrestrial margin of the ice sheet; such as ice marginal lakes. 
-
-In 2017, 3347 ice marginal lakes were identified in Greenland along the ice margin ([How et al., 2021](https://www.nature.com/articles/s41598-021-83509-1), see map figure for all mapped lakes). Globally, these ice marginal lakes hold up to 0.43 mm of sea level equivalent, which could have a marked impact on future predictions ([Shugar et al., 2021](https://www.nature.com/articles/s41558-020-0855-4)). Therefore, they need to be monitored to understand how changes in ice marginal lake water storage affect melt contribution, and how their dynamics evolve under a changing climate.
-
-`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.
-
-1. Greenland-wide inventories of ice marginal lakes will be generated for selected years during the satellite era, building upon established classification methods in a unified cloud processing workflow
-2. Detailed time-series analysis will be conducted on chosen ice marginal lakes to assess changes in their flooding dynamics; focusing on lakes with societal and scientific importance
-3. The findings from this work will be validated against in situ observations - namely hydrological measurements and terrestrial time-lapse images - to evaluate whether the remote sensing workflow adequately captures ice marginal lake dynamics
+There have been many different approaches to classifying ice marginal lakes with remote sensing techniques [@shugar_rapid_2020;@rick_dam_2022]. Packages exist for handling satellite and spatial data, such as GrIML's two key dependencies, Geopandas [@kelsey_geopandas_2020] and Rasterio [@gillies_rasterio_2019], as well as others (e.g. SentinelHub, Google Earth Engine). Remote sensing object classification and post-processing routines are usually available in connection with scientific publications, however, few are available as open, deployable packages. The GrIML post-processing Python package addresses this gap, for the benefit of the future generation of ice marginal lake inventories and for others in the scientific community to adapt and use themselves.
 
 
 # Usage
 
-![The GrIML workflow](https://github.com/PennyHow/pennyhow.github.io/blob/master/assets/images/griml_workflow.png?raw=true)
 
-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:
+![The GrIML Python package structure \label{fig:workflow}](https://github.com/PennyHow/GrIML/blob/main/other/reporting/figures/griml_package_structure.png?raw=true)
+
+- Installation overview
+- Basic structure, steps put into separate modules, flexible data loading
+- Analysis functionality
 
-- 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 
 
 # Acknowledgements