walkability

NetAScore - Network Assessment Score Toolbox for Sustainable Mobility

ArcGIS Python Toolbox for creating 3D walking networks

AwaP QGIS plugin, enables analysis of permeability within urban morphologies

generating various measures of urban form, built environment, and walkability for the Toronto region

IC QGIS plugin, calculates interface catchment within urban morphologies

A geospatial dataset focusing on walkability and pedestrian access

Full-stack web application for the visualization of road attributes and route planning in Amsterdam using area avoidance, focusing on the needs of the elderly and vulnerable people.

Temperature, humidity and pollution levels monitoring in the campus.

Packaged repository for the final studio project for the Artificial Intelligence seminar at the MACAD Masters

Development of a high-resolution walkability index for Europe

Ready-to-use MCP extensions for Gemini CLI and Claude Desktop - neighborhood intelligence, school ratings, flood risk, air quality, and more.

Can features of the built environment be used to predict the locations of pedestrian crashes at the street level in Uptown Charlotte, North Carolina?

City Information Modeling with QGIS and Python

An end-to-end data pipeline analyzing walkability and service voids in a local community with OSM data and building footprints as a population proxy.

Don't open, data about pedestrian accessibility inside

Pedestrian network quality tool for Brussels — walkability scores, missing crossings & sidewalk gap detection, built from and for OpenStreetMap data.

An interactive agent-based simulation that models how pedestrians naturally carve desire paths across terrain. Place origin and destination nodes on real-world maps, then watch friction fields form and emergent foot traffic patterns emerge from the interaction of agents navigating through walkable surfaces.

This project analyzes walkability data to explore relationships between urban design, accessibility, and quality of life metrics.

Python geospatial analysis project exploring Liverpool walkability and street network connectivity using OSMnx, GeoPandas, and Folium.

Walkability scoring model for urban areas. Built with a 5-person team, presented to stakeholders. Role: Project Manager.