Study of a Geo Map Optimisation Use Case Using Python

Overview

This article presents one of the first approaches to finding road distance based on suburb coordinates in Brisbane, Australia. The goal is to find the closest polygon — representing a suburb — to a user's address.

If the address is inside the polygon, the software detects it and indicates that it is inside; otherwise, it identifies the closest polygon and finds the shortest path from the user's address coordinates to the nearest edge of that polygon.

Business Value

Finds the nearest office or service automatically, helping users — especially older individuals — quickly access the closest location without confusion.

Saves time and reduces travel effort by calculating the shortest route, avoiding unnecessary distance and heavy traffic.

Simple and user-friendly experience, making it easy for all users, including those less familiar with technology, to navigate and make decisions confidently.

This enables route finding for businesses that aim to identify the best services, facilities, and opportunities for people who reside in a particular suburb, or for those who want to find the closest suburb for their needs.

Python Packages Used

Shapely / GeoMap: Used to handle geometric operations such as detecting whether a point lies inside a polygon and calculating distances to boundaries.

KML Parser: Used to read and extract suburb boundary data from KML files into usable formats.

JSON: Used to structure and store geospatial data and intermediate results in a flexible, readable format.

Geocoder: Used to convert user addresses into geographic coordinates (latitude and longitude).

Haversine: Used to calculate the distance between two geographic points based on their coordinates.

GeoPandas: Used to manage, analyse, and visualise geospatial data efficiently in a tabular structure.

How the Pipeline Works

1. User provides their address.

2. The address is converted to geocodes (latitude, longitude).

3. The system checks if the address is inside any polygon — if so, it prints "inside" and ends.

4. If not inside, for each polygon the system calculates using the Shapely algorithm and Dijkstra's algorithm.

5. Results are sorted across all polygons.

6. The shortest path and destination are depicted on the map.

Please feel free to reach out if you have any questions or would like to discuss any part of this solution in more detail.