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odwardenishnixsion-crypto/urban-mobility-Opit

Domaine:

geospatialmobility

Type de record:

project
Créateur:
odw
Hôte:
OSM Mobility and Accessibility Mapping - Opit, Omoro Uganda Project: Real-Time Urban Mobility and Accessibility Analysis. 1. Context & Objective The Goal of this project was to analyze urban mobility patterns and accessibility challenges in real time using Open-source data. I aimed to answer questions such as: (i) Which areas experience high congestion or mobility delays? (ii) Which areas experience high congestion or mobility delays? (iii) Are key public services like Hospitals, Schools, Transport hubs) easily accessible? (iv) How does infrastructure affect people with limited mobility e.g. wheelchair users? The objective was to generate insights that could support urban planning, transport optimization, and inclusive town design. 2. Osint Methodology I relied entirely on open-source intelligence (OSIN) and publicity available data: Data Sources (i) OpenStreetMap (OSM) - road networks, sidewalks, crossings, wheelchairs tags. (ii) Overpass API - to query accessibility and infrastructure features. (iii) Public transport open data (GIFTS where available) (iv) Traffic data APIs (where publicly accessible) (v) Satellite imagery (Google Earth/ sentinel public imagery for validation) (vi) Government open data portals (road networks, public facility locations) Tools Used (i) Overpass Turbo (OSM queries) (ii) Leaflet.js (Interactive web map visualization) (iii) QGIS (Spatial analysis & Mapping) (iv) Python (Pandas, GeoPandas, Requests) 3. Data Collection & Validation Collection - Queried OSM using Overpass API for: Roads and pathways, Public facilities, Accessibility tags like wheelchair=yes/no/limited. - Collected coordinates and network data for routing analysis. Validation - Cross-checked OSM data with: Satellite imagery, Street-level imagery where available, Government infrastructure datasets. - Removed duplicates and corrected inconsistent tagging. - Flagged missing accessibility tags as data gaps. Challenges - Some areas had incomplete wheelchair accessibility data. - inconsistent tagging standards across regions. - Real- …

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