The Geospatial Neighborhood Analysis Package
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Updated
Dec 12, 2025 - Python
The Geospatial Neighborhood Analysis Package
City Energy Analyst (CEA) is an open-source urban building energy modeling (UBEM) platform and computation tool for the design of low-carbon and highly efficient cities.
A library to download, process and visualize high resolution urban data.
A Python package for street view image perception analysis, providing tools for feature extraction and comfort prediction.
CitySurfaces semantic segmentation of sidewalk surfaces
DashMap is an open source web platform that gathers, analyses and visualises urban data.
GeoJSON to Modelica Translator that is focused on district energy system design and analysis.
Surface Urban Energy and Water Balance Scheme
Calculate Open Street Maps road length for any polygon
Implementation of a multi-agent system for the modeling of carpooling in a city with one-way streets. Used Python and the Mesa package for multi-agent modeling.
Multi-class classification model for predicting the types of crimes in Toronto
Set of tools based on Python, GeoPandas and Shapely to achieve urban geoprocessing
A Python package for merging GTFS data with OSM street network in NetworkX, facilitating time-dependent analysis of transport networks.
AwaP QGIS plugin, enables analysis of permeability within urban morphologies
IC QGIS plugin, calculates interface catchment within urban morphologies
Urban-WORM (Workflow Of Reproducible Multimodal Inference) is a user-friendly high-level interface that is designed for adding rich and meaningful captions for crow-sourced data with geotags using multimodal models.
Measures to spatial agglomeration for industries
GeoFeatureKit: From coordinates to geospatial features and travel-time accessibility for ML, urban analytics, and location intelligence.
This repository contains the data and code associated with the paper titled "Facebook City: Place-named groups as urban communication infrastructure in Greater London". This is part of the "Localising Content Governance" project, funded by Facebook Research.
A machine learning pipeline for classifying building types in urban areas
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