Bump REMA surface DEM from v1.0 to v1.1, 200m to 100m resolution

Pipfile

@@ -6,6 +6,8 @@ name = "pypi"
 [packages]
 black = "==18.9b0"
 cython = "==0.29.1"
+descartes = "==1.1.0"
+geopandas = {editable = true, ref = "0.4.0-26-g9e584cc", git = "https://github.com/geopandas/geopandas.git"}
 gmt = {editable = true, ref = "0.1a3-131-g9772fa3", git = "https://github.com/weiji14/gmt-python.git"}
 ipython = "==7.1.1"
 jupyterlab = "==0.35.4"

README.md

@@ -12,7 +12,7 @@ Also a convenient [flat file](https://en.wikipedia.org/wiki/Flat-file_database)
 
 <details>
 <summary>Directory structure</summary>
-  
+
 ```
   deepbedmap/
     ├── features/ (files describing the high level behaviour of various features)
@@ -30,11 +30,8 @@ Also a convenient [flat file](https://en.wikipedia.org/wiki/Flat-file_database)
     │    ├── *.tif (Surface DEMs, Ice Flow Velocity, etc. See list in Issue #9)
     │    └── README.md (markdown information on miscellaneous data sources)
     ├── model/ (*hidden in git, neural network model related files)
-    │    ├── logs/ (directory for tensorboard log files)
-    │    └── train/ (a place to store the model training data)
-    │        ├── W*_data.npy (miscellaneous numpy arrays)
-    │        ├── X_data.npy (highres numpy arrays)
-    │        └── Y_data.npy (lowres numpy arrays)
+    │    ├── train/ (a place to store the raster tile bounds and model training data)
+    │    └── weights/ (contains the neural network model's architecture and weights)
     ├── .env (environment config file used by pipenv, supposedly)
     ├── .<something>ignore (files ignored by a particular piece of software)
     ├── Dockerfile (set of commands to reproduce the software stack here into a docker image)
@@ -77,14 +74,14 @@ Note that `pipenv install` won't work directly (see Common problems below).
 You may want to check that `which pipenv` returns something similar to ~/.conda/envs/deepbedmap/bin/pipenv.
 
     conda activate deepbedmap
-    
+
     export LD_LIBRARY_PATH=$CONDA_PREFIX/lib/
     pipenv install --python $CONDA_PREFIX/bin/python
     #or just
     LD_LIBRARY_PATH=$CONDA_PREFIX/lib/ pipenv install --python $CONDA_PREFIX/bin/python
-    
+
 Finally, double-check that the libraries have been installed.
-    
+
     pipenv graph
 
 ### Syncing/Updating to new dependencies
@@ -104,7 +101,7 @@ So after running `conda activate deepbedmap`, and you see an `...error while loa
 
     conda activate deepbedmap
     pipenv shell
-    
+
     python -m ipykernel install --user --name deepbedmap  #to install conda env properly
     jupyter kernelspec list --json                        #see if kernel is installed
     jupyter lab &

data_list.yml

@@ -15,15 +15,19 @@
   citekey: Noh2018REMA
   folder: misc
   location: Antarctica
-  resolution: 200m
+  resolution: 100m
   doi:
     dataset: "https://doi.org/10.7910/DVN/SAIK8B"
     literature: "https://doi.org/10.1016/j.isprsjprs.2017.12.008"
   files:
+    -
+      filename: REMA_100m_dem.tif
+      url: "http://data.pgc.umn.edu/elev/dem/setsm/REMA/mosaic/v1.1/100m/REMA_100m_dem.tif"
+      sha256: 80c9fa41ccc69be1d2cd4a367d56168321d1079e7260a1996089810db25172f6
     -
       filename: REMA_200m_dem_filled.tif
-      url: "http://data.pgc.umn.edu/elev/dem/setsm/REMA/mosaic/v1.0/200m/REMA_200m_dem_filled.tif"
-      sha256: 8ac252e40810ac5e59934879a066f496c847936771f318dab2ab4a257052d964
+      url: "http://data.pgc.umn.edu/elev/dem/setsm/REMA/mosaic/v1.1/200m/REMA_200m_dem_filled.tif"
+      sha256: f750893861a1a268c8ffe0ba7db36c933223bbf5fcbb786ecef3f052b20f9b8a
 -
   citekey: Rignot2011MEASURES
   folder: misc