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Course Outline
Introduction to Python
- Overview of Python and its role in geospatial analysis.
- Setting up Python environments for ArcGIS and QGIS.
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Basic syntax and task execution.
- if, elif, else statements.
- Loops: for, while.
- Functions and modules.
- Error and exception handling.
Introduction to Data Analysis and Visualization
- Working with data in Python using Pandas and Numpy.
- Data manipulation techniques for geospatial datasets.
- Introduction to Matplotlib and Seaborn for visualizing geospatial data.
Vector Data Analysis with Geopandas, Arcpy, and PyQGIS
- Overview of vector data structures.
- Manipulating vector layers using Geopandas in QGIS.
- Performing vector layer analysis with Arcpy in ArcGIS.
- Using PyQGIS for vector operations.
Raster Data Analysis with GDAL/OGR, Rasterio, Geopandas, Arcpy, and PyQGIS
- Overview of raster data.
- Working with raster layers using GDAL/OGR and Rasterio.
- Raster data analysis in ArcGIS using Arcpy.
- Automating raster processing tasks with PyQGIS.
Tool Sequences with Python in QGIS and ArcGIS
- Automating GIS workflows and processes.
- Creating scripts for sequential task automation in ArcGIS and QGIS.
- Building custom geoprocessing tools using Python.
Geospatial Information Management with Python
- Automating report generation and map creation.
- Connecting to geospatial databases and accessing web services (WMS, WFS).
- Automating data retrieval and analysis.
Summary and Next Steps
Requirements
- Basic understanding of GIS concepts and familiarity with ArcGIS/QGIS tools.
Audience
- Professionals in earth sciences.
- Professionals in engineering.
35 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
