GIS with Laguerre-Voronoi Diagrams

This project explores the different applications of Laguerre-Voronoi Diagrams to different geospatial datasets

Features

The main features of this project include, * *

Getting Started

The instructions here will get your development environment setup for this project.

Prerequisites

To build this project you need,

• To clone this GitHub Gist
• Then for Linux / MacOS environments set the PYTHONPATH to the directory of the Gist above.
• If you do not have pipenv installed make sure to install it using the instructions found here

Installing

⚠️ The project has to be forked to your own namespace before cloning.

Clone the project

$ git clone [email protected]:dai-mo/gis-laguerre.git

Change directory

$ cd gis-laguerre

Create the .env file with the following entries

DHS_DATA_DIR = "<path_to_dhs_data>"
GADM_DATA_DIR = "<path_to_gadm_36_country_boundary_shapefile>"
OUT_DIR = "<path_to_output_directory>"

Set up the environment for the project

$ pipenv shell
$ pipenv install

Building

Build artifact locally (in the target directory)

$ ...

Testing

Run tests $ ...

Executing

Run the program locally by executing, $ ...

Code style check

...

Publish

To make the artifact available for other dependent projects, install artifact locally.

$ ...

Publish the artifact to a global artifact store.

$ ...

Deployment

This project can be deployed by ....

Configuration / Environment

This project requires the following configuration / environment variables to run, * *

Main Dependencies

The main dependencies of this project include, * *

Versioning

We use Semantic Versioning. For the versions available, see the tags on this repository.

Support

Please open an issue for support.

Releases

Releases for this repository are available here.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Authors

Please refer to the list of contributors who participated in this project.

Acknowledgments

Thanks to,

• the Solve For Good project: Creating a well-being data layer using machine learning, satellite imagery and ground-truth data.
• Gijs van den Dool for extensive discussions related to Voronoi Diagrams and their use in GIS which finally led to weighted Voronoi Diagrams being used for this project.
• Kathleen Buckingham & Rong Fang of the World Resources Institute
• Carlos Mougan & Rohaan Nadeem of the Solve For Good Team.
• GitHub Gist by Devert Alexandre on Laguerre Vornoi Diagrams