Voronoi Satellite Maps with Python

This report outlines a Python-based method for analyzing satellite imagery using Voronoi tessellation. The approach leverages computer vision techniques to identify objects in an image, treating them as nucleation points for a Voronoi diagram. By applying a pixel thresholding technique, the algorithm isolates key features, such as rooftops or other structures, and calculates their centroids. These centroids are then used to generate a Voronoi tessellation, effectively partitioning the image area into regions of influence for each identified object. This method offers a novel way to visualize urban density and spatial relationships, providing a powerful tool for geographical and urban studies.