Year: 2025
Type: other
Abstract: 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.
Source: PORTO@Iris
Authors: Sparavigna, Amelia Carolina, Gemini (Modello Linguistico di Google)
Institution: Politecnico di Torino
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7082965512
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