From 5d1e302c6137d5dbec68101d08c911046cd14492 Mon Sep 17 00:00:00 2001
From: Farzaneh-prime <farzaneh-sadeghi91@outlook.com>
Date: Sun, 19 Jan 2025 21:01:13 +0100
Subject: [PATCH] lesson numbers corrected
---
Lesson 1_Setting up your workspace.html | 2 +-
Lesson 2_Feature_Collections_Basics.ipynb | 28 +++++++++++++++++--
... Lesson 7_GEE_Air_Quality_Assessment.ipynb | 0
...b => Lesson 8_Nighttime_Lights_Trend.ipynb | 0
smart_data.yml | 2 +-
5 files changed, 27 insertions(+), 5 deletions(-)
rename Lesson 8_GEE_Air_Quality_Assessment.ipynb => Lesson 7_GEE_Air_Quality_Assessment.ipynb (100%)
rename Lesson 7_Nighttime_Lights_Trend.ipynb => Lesson 8_Nighttime_Lights_Trend.ipynb (100%)
diff --git a/Lesson 1_Setting up your workspace.html b/Lesson 1_Setting up your workspace.html
index 97c6a46..e044e61 100644
--- a/Lesson 1_Setting up your workspace.html
+++ b/Lesson 1_Setting up your workspace.html
@@ -1,4 +1,4 @@
-<p style="text-align: justify;">Welcome to the Smart Data coding course, where you'll unlock vital spatial coding skills that will empower your journey and open new horizons. To be able to follow through the chapters of this course, a few technical prerequisites must be followed. In detail, we need to install Python, the coding language we will use, Jupyter Lab/Notebook, our IDE (or integrated development environment) of choice, and a few Python libraries along the way, that can be seen as add-ons to what Python can do with our commands.</p>
+<p style="text-align: justify;">Welcome to part one of the Smart Data coding course "Python and Earth Observation Data", where you'll unlock vital spatial coding skills that will empower your journey and open new horizons. To be able to follow through the chapters of this course, a few technical prerequisites must be followed. In detail, we need to install Python, the coding language we will use, Jupyter Lab/Notebook, our IDE (or integrated development environment) of choice, and a few Python libraries along the way, that can be seen as add-ons to what Python can do with our commands.</p>
<p style="text-align: justify;">💡If you are taking this course directly from the NFDI4Earth educational portal, you will work with a dedicated Jupyter Lab workspace that is already set up with all necessary libraries and data. This means you can bypass installing Python or Jupyter locally on your computer. Instead, simply log into the portal, and you’ll be ready to jump right into the coding. However, if you prefer to set up your own environment for practice or future use, follow the instructions below.</p>
<h3 style="text-align: justify;">📖Choosing a path</h3>
<p style="text-align: justify;">When installing Python and Jupyter Lab (and other packages), you can either use your native system or create a<strong> virtual environment</strong>, which gives you the ability to create an isolated environment on your machine from where you can start your projects. The big advantage here is that some libraries have dependencies on what is installed and how – and a virtual environment gives you the ability to install or deinstall everything as you go, or just start over if everything goes south. <strong>It is therefore recommended that a virtual environment be created and the needed libraries installed there</strong>. You can use Anaconda Navigator to do this. It is software you can use to avoid typing commands in a command box but instead manage environments and libraries in an easy-to-use user interface. Visit <a href="https://docs.anaconda.com/navigator/" target="_blank" rel="noopener">Anaconda Navigator</a> and its <a href="https://docs.anaconda.com/navigator/tutorials/manage-environments/" target="_blank" rel="noopener">doc </a>for Managing Environments to get more information on how to set up a virtual environment.</p>
diff --git a/Lesson 2_Feature_Collections_Basics.ipynb b/Lesson 2_Feature_Collections_Basics.ipynb
index 72f1e27..8665699 100644
--- a/Lesson 2_Feature_Collections_Basics.ipynb
+++ b/Lesson 2_Feature_Collections_Basics.ipynb
@@ -20,10 +20,32 @@
},
{
"cell_type": "code",
- "execution_count": 1,
- "id": "ea742ffb",
+ "execution_count": null,
+ "id": "cc3faf61",
"metadata": {},
"outputs": [],
+ "source": [
+ "!mamba env create -f smart_data.yml"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "ea742ffb",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "ModuleNotFoundError",
+ "evalue": "No module named 'ee'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
+ "Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mee\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgeemap\u001b[39;00m\n",
+ "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'ee'"
+ ]
+ }
+ ],
"source": [
"import ee\n",
"import geemap"
@@ -196,7 +218,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "lms",
+ "display_name": "gee",
"language": "python",
"name": "python3"
},
diff --git a/Lesson 8_GEE_Air_Quality_Assessment.ipynb b/Lesson 7_GEE_Air_Quality_Assessment.ipynb
similarity index 100%
rename from Lesson 8_GEE_Air_Quality_Assessment.ipynb
rename to Lesson 7_GEE_Air_Quality_Assessment.ipynb
diff --git a/Lesson 7_Nighttime_Lights_Trend.ipynb b/Lesson 8_Nighttime_Lights_Trend.ipynb
similarity index 100%
rename from Lesson 7_Nighttime_Lights_Trend.ipynb
rename to Lesson 8_Nighttime_Lights_Trend.ipynb
diff --git a/smart_data.yml b/smart_data.yml
index f4d425a..cb6251a 100644
--- a/smart_data.yml
+++ b/smart_data.yml
@@ -135,7 +135,7 @@ dependencies:
- libgdal=3.2.2=ha6cada3_7
- libglib=2.68.3=h1e62bf3_0
- libiconv=1.16=he774522_0
- - libkml=1.3.0=h9859afa_1013
+ - libkml=1.3.0
- liblapack=3.9.0=9_mkl
- libnetcdf=4.8.0=nompi_hf689e7d_103
- libpng=1.6.37=h1d00b33_2
--
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