Nairobi Traffic Congestion Analysis

A Comprehensive GIS-Based Study for Urban Mobility Solutions

By Daniel Manyasa - BSc. Geomatic Engineering & GIS
Dedan Kimathi University of Technology

Project Overview

GIS Analysis

Comprehensive spatial analysis of Nairobi's road network using QGIS and Python

Traffic Patterns

Identification of congestion hotspots and traffic flow patterns

Public Transport

Analysis of public transport efficiency and BRT system proposals

Data-Driven Solutions

Evidence-based recommendations for urban mobility improvement

Key Findings

4.2/5

Thika Road Congestion

Highest congestion level recorded during peak hours

25-35%

Potential Improvement

Expected congestion reduction with proposed solutions

KES 2.5-4B

Annual Economic Impact

Estimated savings from reduced congestion

Interactive Traffic Analysis

Congestion Legend

Very High (4.0-5.0)
High (3.0-3.9)
Moderate (2.0-2.9)

Dedan Kimathi University of Technology

Department of Geomatic Engineering & Geospatial Information Systems

This project demonstrates the application of geospatial technologies in solving real-world urban challenges, showcasing skills developed through the Geomatic Engineering curriculum.