update jupyter nbs

.github/workflows/publish-pythia.yaml

@@ -49,7 +49,9 @@ jobs:
           path: |
             ~/.local/share/jupyter/kernels
             ~/.cache/pip
+            /usr/share/miniconda/envs
             ./chapters/courses/.jupyter_cache
+            ./chapters/courses/microwave-remote-sensing/.jupyter_cache
             ./chapters/templates/.jupyter_cache
             ./chapters/tutorials/.jupyter_cache
           key: ${{ runner.os }}-env-${{ hashFiles('./environment.yml', './notebooks/**/*.yml') }}

.github/workflows/publish-quarto.yaml

@@ -36,7 +36,9 @@ jobs:
           path: |
             ~/.local/share/jupyter/kernels
             ~/.cache/pip
+            /usr/share/miniconda/envs
             ./chapters/courses/.jupyter_cache
+            ./chapters/courses/microwave-remote-sensing/.jupyter_cache
             ./chapters/templates/.jupyter_cache
             ./chapters/tutorials/.jupyter_cache
           key: ${{ runner.os }}-env-${{ hashFiles('./environment.yml', './notebooks/**/*.yml') }}

notebooks/Makefile

@@ -56,7 +56,7 @@ post-render:
 preview: $(CONDA_ENV)/envs/eo-datascience $(CONDA_ENV_DIR) $(KERNEL_DIR)
 	$(CONDA_ACTIVATE) eo-datascience
 	- mkdir -p _preview/notebooks
-	python -m pip install -e .
+	python -m pip install .
 	cp ./chapters/references.bib ./_preview/notebooks/
 	cp -r ./chapters/images ./_preview/notebooks
 	wget https://raw.githubusercontent.com/TUW-GEO/eo-datascience-cookbook/refs/heads/main/README.md -nc -P ./_preview

notebooks/courses/microwave-remote-sensing.ipynb

@@ -1,21 +1,25 @@
 {
  "cells": [
   {
-   "cell_type": "raw",
+   "cell_type": "markdown",
    "id": "0",
    "metadata": {},
    "source": [
     "---\n",
     "title: Microwave Remote Sensing\n",
-    "---"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1",
-   "metadata": {},
-   "source": [
-    "This course ..."
+    "jupyter:\n",
+    "  kernelspec:\n",
+    "    name: \"microwave-remote-sensing\"\n",
+    "    language: \"python\"\n",
+    "    display_name: \"microwave-remote-sensing\"\n",
+    "---\n",
+    "\n",
+    "\n",
+    "This course at the TU Wien teaches course, students are able to read, visualize and analyze Synthetic Aperture Radar (SAR) data. This will aid interpretation of SAR data based upon a physical understanding of sensing principles and the interaction of microwaves with natural objects.\n",
+    "\n",
+    "::: {.callout-note}\n",
+    "These notebooks contain interactive elements. The full interactive elements can only be viewed on Binder by clicking on the Binder badge or 🚀 button.\n",
+    ":::"
    ]
   }
  ],