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Course Outline

Introduction to Python

  • Understanding Python’s role and potential in geospatial analysis
  • Configuring Python environments for seamless integration with ArcGIS and QGIS
  • Core syntax and task execution
    • Conditional logic: if, elif, else statements
    • Iteration: for and while loops
    • Structuring code with functions and modules
    • Robust error and exception handling

Foundations of Data Analysis and Visualization

  • Processing and analyzing data using Pandas and NumPy in Python
  • Applying data manipulation techniques tailored for geospatial datasets
  • Visualizing geospatial data effectively with Matplotlib and Seaborn

Vector Data Analysis via Geopandas, Arcpy, and PyQGIS

  • Understanding fundamental vector data structures
  • Managing and editing vector layers using Geopandas within QGIS
  • Executing vector layer analyses using Arcpy in the ArcGIS environment
  • Performing vector operations leveraging PyQGIS capabilities

Raster Data Analysis with GDAL/OGR, Rasterio, Geopandas, Arcpy, and PyQGIS

  • Overview of raster data concepts
  • Handling raster layers using GDAL/OGR and Rasterio
  • Conducting raster analysis in ArcGIS through Arcpy
  • Automating raster processing workflows using PyQGIS

Sequencing Tools with Python in QGIS and ArcGIS

  • Strategies for automating GIS workflows and complex processes
  • Developing scripts for sequential task automation across ArcGIS and QGIS
  • Designing and building custom geoprocessing tools using Python

Geospatial Information Management with Python

  • Automating the generation of reports and the creation of maps
  • Interfacing with geospatial databases and accessing web services (WMS, WFS)
  • Automating data retrieval pipelines and analytical processes

Summary and Strategic Next Steps

Requirements

  • Fundamental knowledge of GIS principles and basic proficiency with ArcGIS or QGIS tools.

Target Audience

  • Specialists in Earth Sciences
  • Engineering Professionals
 35 Hours

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