Setup | Code Organization | Data | Acknowledgements

Geospatial Modeling of Access to Water and Sanitation

This repository accompanies our research work for Geospatial Modeling of WASH Access in Colombia.

The goal of this project is to provide a means for faster, cheaper, and more scalable survey of survey of the state of WASH access using satellite images and machine learning.

Setup

To get started, create a conda environment as follows:

pip install -r requirements.txt

Notable dependencies include:

• Anaconda3-2019.10
• earthengine-api==0.1.223
• gdal==3.1.0

Code Organization

This repository is divided into three main parts:

• notebooks/: contains all Jupyter notebooks for data processing and model experimentation
• scripts/: contains scripts that are part of the main workflow in notebooks/
• utils/: contains utility scripts for geospatial data pre-processing and modeling

Data

If you need the dataset used for training, please contact ThinkingMachines or IMMAP at hello@thinkingmachin.es, info@immap.org.

Acknowledgments

This work is supported by the iMMAP Colombia.