[100% Off] Python For Gis Automation And Geospatial Applications
Automate GIS workflows with ArcPy, PyQGIS and Python – and build real geospatial projects from NDVI to plant detection
What you’ll learn
- Automate repetitive GIS tasks with ArcPy and PyQGIS, turning hours of manual clicking into scripts that run in seconds
- Process vector and raster layers in Python – clipping, reprojecting, buffering and batch-converting across entire folders
- Calculate remote sensing indices such as NDVI and run zonal statistics to measure crop health and environmental change
- Build capstone projects on Leaf Area Index, Land Surface Temperature, and plant detection using computer vision
- Generate and export professional map layouts automatically, without opening the GIS interface
- Handle and summarise geospatial tables with Pandas and NumPy, then visualise the results as charts
Requirements
- A Windows PC – the course uses ArcPy and QGIS, installed step by step in the first section
- No Python experience required; the course starts from variables, loops and functions
- Miniconda, Jupyter Notebook and QGIS are free and set up together in the opening lectures
- An interest in maps, satellite imagery or spatial data – no GIS certification needed
Description
Stop clicking. Start scripting.
If you work with spatial data, you already know the pattern: open the GIS, clip the layer, reproject it, run the same tool on forty files, export the map, repeat next week. This course replaces that routine with Python.
You will start by setting up a clean working environment with Miniconda, Jupyter Notebook and QGIS, then learn just enough Python – variables, loops, functions, and data handling with Pandas – to be productive with geospatial data. From there you move into ArcPy and PyQGIS to automate geoprocessing, batch-process vector and raster layers, and generate finished map layouts without touching the interface.
What you will build
NDVI and other remote sensing indices calculated straight from satellite imagery
Zonal statistics that summarise raster values across your own boundaries
A Leaf Area Index (LAI) analysis workflow
A Land Surface Temperature (LST) analysis workflow
A computer vision script that detects and counts individual plants
What you get
Downloadable scripts and datasets so you can follow along with real data
Quizzes after each major section to check your understanding
Code you can adapt directly to your own projects
No prior Python experience is needed. You will need a Windows PC and an interest in GIS – everything else is installed together in the first section.
Taught by Dr. Azad Rasul, a geospatial data scientist and Assistant Professor, with over 150,000 students enrolled across his Udemy courses.
Enrol now and start turning your manual GIS workflows into scripts that run themselves.
Author(s): Senior Assist Prof Azad Rasul
