Python, as a one-stop-shop for Machine Learning, Geospatial Analytics, Optimization Algorithms, and Visualization Tools, can be leveraged to create a simple yet effective sustainability decision-making methodology with just four steps: Geospatial Indexing, Feature Engineering, Predictive Scoring, and Score Optimization.

With it, it's possible to tackle distinct sustainable development issues, from mobility transition to light pollution in a way that decision-makers can quickly implement it to take action for the Sustainable Development Goals.