Neatnet
A Python toolkit for simplifying street network geometry by converting transportation-focused representations to morphological centerlines.
What is Neatnet?
neatnet is a Python toolkit for processing and simplifying street network geometry. It transforms transportation-focused street representations (like those from OpenStreetMap) into morphological centerlines by removing dual carriageways, simplifying roundabouts, and preserving network continuity. The tool addresses the need for street networks that better represent urban space morphology rather than just transportation infrastructure.
Urban researchers, GIS analysts, and data scientists working with street network data who need simplified, morphologically accurate representations for spatial analysis, urban studies, or network science applications.
Developers choose neatnet because it provides a specialized, scientifically-grounded approach to street network simplification that preserves topological continuity while converting transportation geometries to morphological representations, filling a gap in existing GIS tooling for urban analysis.
Overview
Street geometry processing toolkit
Use Cases
Best For
- Converting OpenStreetMap street data into morphological representations for urban analysis
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