Geospatial Python: Expanded Project Guides

Generated from: GEOSPATIAL_PYTHON_LEARNING_PROJECTS.md

This folder contains deep-dive guides for each geospatial project in the learning path.

Overview

These projects cover the core of geospatial Python: vector and raster data, coordinate systems, spatial joins, network analysis, and map visualization. Each project is designed to produce a real artifact you can inspect and share.

Project Index

# Project Difficulty Time Key Focus
1 Real-Time Earthquake Monitor Beginner Weekend GeoJSON, mapping, filtering
2 Neighborhood Walkability Analyzer Intermediate 1-2 weeks OSMnx, network analysis, isochrones
3 Property Value Choropleth with Price Prediction Intermediate 1-2 weeks Choropleths, spatial features, modeling
4 Delivery Route Optimizer Advanced 2-3 weeks Routing, geocoding, optimization
5 Satellite Image Land Cover Classifier Advanced 3-4 weeks Raster workflows, indices, classification

Prerequisites

  • Solid Python basics
  • Comfort with JSON/CSV data
  • Basic understanding of maps (latitude/longitude)

Learning Paths

  • Visualization First: Project 1 -> Project 3 -> Project 5
  • Routing and Networks: Project 1 -> Project 2 -> Project 4
  • Full Path: Project 1 -> Project 2 -> Project 3 -> Project 4 -> Project 5