Welcome to Infrastructure Mapper! This repository contains guidelines and conventions for a spatial database intended to be used managing infrastructure-related data.

• 🌐 Infrastructure Mapper
  • 📖 Table of Contents
  • 🚀 Project Overview
  • QA Status
  • 📜 License
  • 📂 Folder Structure
  • 🤖 Using 'AI' (Large Language Models)
  • 🌿 Design Aesthetic
  • Data Model
  • ⚒️ Using
  • 🛠️ Scripts Overview
  • 🧊 Using the Nix Flake
  • ✨ Contributing
  • 📧 Contact
  • Contributors

Test	Description
	Check all files have license, copyright and attribution.
	Check that PostgreSQL / PostGIS fixtures load.
	Check that all markdown files are well formed.
	Python code QA checks.
	General codebase QA checks.
	Check spelling in all files containing text.
	Check that all SQL files
	Check that all yaml files are well formed.

This project consists of:

1. a SQL Schema for PostgreSQL,
2. a set of fixtures to load that schema with default values (particularly for lookup tables)
3. a set of QGIS forms and layer styles for visualising the data

This project is licensed under the MIT License. See the LICENSE file for details.

InfrastructureMapper/
├── img/               # Images and media resources used in this documentation
├── qml/               # QGIS layer style and form definitions
├── diagrams/          # Documentation and ERD diagrams
├── presentations/     # Presentations for this project and each model created using Marp
├── sql/               # Schema and fixtures to load into postgres
├── scripts/           # Helper scripts
└── README.md          # Project overview and conventions

We are fine with using LLM's and Generative Machine Learning to act as general assistants, but the following three guidelines should be followed:

1. Repeatability: Although we understand that repeatability is not possible generally, whenever you are verbatim using LLM or Generative Machine Learning outputs in this project, you must also provide the prompt that you used to generate the resource.
2. Declaration: Sharing the prompt above is implicit declaration that a machine learning assistant was used. If it is not obvious that a piece of work was generated, include the robot (🤖) icon next to a code snippet or text snippet.
3. Validation: Outputs generated by a virtual assistant should always be validated by a human and you, as contributor, take ultimate responsibility for the correct functionality of any code and the correct expression in any text or media you submit to this project.

Our design aesthetic is an isometric style with a nature and environment inspired palette. We use an the color palette in the table below. The design approach can be personified by:

• Clean vector isometric projection
• Layered terrain with shadows
• Gentle color blending without gradients
• Minimal outlines for clarity
• Selective use of texture (like grass patterns or water ripples)

You can use the notes above and the table below if you are prompt engineering additional graphics for this project using tools like ChatGPT.

Our colour swatch looks like this:

🤖 Prompt: Generate me a beautiful circular swatch with these colours. Invent nice unique, human names for each colour:

#7C9C75 #A9825A #E0D2B2 #A4DDED #2B7A78 #C1E1C1 #9FA8A3 #F5F5F2

These colors are soft but grounded, avoiding over-saturation while maintaining a naturalistic feel that suits isometric vector work.

This section describes each component of the infrastructure mapper data model. You can also find a complete diagram of the data model in diagrams/Schema.drawio (image render).

Icon	Description
	Electricity infrastructure such as power lines, transformers, and substations.
	General infrastructure elements like bridges, dams, and towers.
	Water-related infrastructure including pipes, tanks, and pumps.
	Vegetation features such as trees, hedges, and planted areas.
	Monitoring devices and their observations (e.g., sensors, cameras).
	Buildings and associated structures.
	Fencing and enclosure features, including standalone gates.
	Points of Interest (POI) for notable locations or features.
	Land use areas such as agricultural, residential, or conservation zones.
	Gates as access points for properties or enclosures.
	Poles for lighting, signage, or utility support.
	Culinary facilities like kitchens, canteens, and food storage.
	Roads, tracks, and paths for transportation infrastructure.

Simply take the sql files in the sql folder and load them into postgres.

The scripts/ folder contains utility scripts to assist with database setup, data loading, and project maintenance. Below is a summary of each script:

✏️ Note: Run each script from the project root. Some scripts may require environment variables or configuration—see comments within each script for usage details.

You can use the provided flake.nix to get a fully reproducible development environment and to run QGIS with the correct profile.

1. Install Nix (if you haven’t already).
2. Enter the development shell:

nix develop

This gives you all the tools and dependencies you need for working on this project.

1. Run QGIS with the project profile:

  nix run .#qgis

Or, for the long-term release version:

nix run .#qgis-ltr

1. VSCode users:

You can launch a ready-to-use VSCode environment:

./scripts/vscode.sh

This makes it easy to get started and ensures everyone is using the same environment!

We welcome contributions! Please read the CONTRIBUTING.md for guidelines on how to get started.

Have questions or feedback? Feel free to reach out!
📧 Email: [email protected]
🌐 Website: kartoza.com

• Tim Sutton - project lead

Made with ❤️ by Tim Sutton (@timlinux) and Kartoza Interns.