This repository powers the content at courses.spatialthoughts.com

The html pages are built using R Studio as a R Markdown Website.

The content has the following course pages

• Spatial Data Visualization and Analytics
• Advanced QGIS
• Automating GIS Workflows with QGIS
• Python Foundation for Spatial Analysis
• Mapping and Data Visualization with Python
• Customizing QGIS with Python
• Mastering GDAL Tools
• End-to-End Google Earth Engine
• Google Earth Engine for Water Resources Management

Most courses are written using pure MarkDown in the corresponding .Rmd file. You can update the content directly. A few courses embed other .md files generated from Jupyter Notebooks - which need to be generated before building the site.

1. Update the .ipynb files in the code/python_foundation/ directory.
2. Run python-foundation-package.sh to generate .md files for each notebook

1. Update the .ipynb and .py files in the code/python_dataviz/ directory.
2. Run python-dataviz-package.sh to generate .md files for each notebook.
3. The script will also copy updated code to spatialthoughts/python-dataviz-web. Commit and push changes there.

The code for the course comes from a Google Earth Engine repository users/ujavalgandhi/End-to-End-GEE.

1. Clone the users/ujavalgandhi/End-to-End-GEE repository to ~/projects directory.
2. Update the .ipynb files in the code/end_to_end_gee/ directory.
3. Run end-to-end-gee-package.sh to generate .md files from the updated code and notebooks.

The code for the course comes from a Google Earth Engine repository users/ujavalgandhi/GEE-Water-Resources-Management.

1. Clone the users/ujavalgandhi/GEE-Water-Resources-Management repository to ~/projects directory.
2. Update the .ipynb files in the code/gee_water_resources_management/ directory.
3. Run gee-water-resources-management-package.sh to generate .md files from the updated code and notebooks.

We prefer the following style while writing the tutorials.