Using GeoPandas for Geospatial Analysis in Python

Module 1: Introduction to GeoPandas & Geospatial Concepts

⏳ 1 hour

• Topics: GIS fundamentals, CRS overview, installation and environment setup.

• Hands-on: Load sample shapefiles and inspect geometries in a GeoDataFrame.

Module 2: Reading and Writing Spatial Data

⏳ 1.5 hours

• Topics: Supported file formats, drivers, and file I/O methods.

• Hands-on: Read GeoJSON and Shapefile data; write filtered results to new files.

Module 3: Geometric Operations

⏳ 2 hours

• Topics: Buffering, intersection, union, and difference operations on geometries.

• Hands-on: Compute buffers around point features and intersect polygons for analysis.

Module 4: Spatial Joins and Overlays

⏳ 2 hours

• Topics: Spatial indexing, join types, overlay methods (union, intersection).

• Hands-on: Join point data to polygon boundaries and summarize attributes by region.

Module 5: Attribute and Query Operations

⏳ 1.5 hours

• Topics: Filtering by attributes, spatial queries, custom predicate functions.

• Hands-on: Query features within a certain distance and filter by attribute values.

Module 6: Visualization of Geospatial Data

⏳ 1.5 hours

• Topics: Thematic mapping, choropleth plots, Matplotlib integration, legends.

• Hands-on: Create maps showing population density and land-use classifications.

Module 7: Advanced Analysis & Metrics

⏳ 1.5 hours

• Topics: Calculating area, length, centroids, and reprojection techniques.

• Hands-on: Reproject datasets to a common CRS and compute feature areas in km².

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