Beer Sheva Mobility Analysis

A comprehensive mobility data analysis and visualization platform for Beer Sheva, focusing on Points of Interest (POIs) and travel patterns.

Project Components

1. ETL & Analytics Pipeline (@EDA)

Tools for analyzing and visualizing specific Points of Interest:

• ETL scripts for loading, preprocessing, and exploring mobility data
• Advanced geospatial analytics including:
  • Origin-destination matrices
  • Temporal trip pattern analysis
  • Catchment area calculations
  • Trip density clustering
  • Modal split analysis
• Static maps of trip patterns
• Detecting and summarizing trip patterns

2. Interactive Dashboard (@Dashboard)

Web interface for exploring mobility data:

• Interactive maps showing trip distributions
• Charts for visualizing trip modes, purposes, and frequencies
• Time-based analysis of trip patterns

3. Advanced Visualizations (@roads)

Dynamic visualizations of mobility patterns:

• Animated trip flows
• Walking route analysis
• Road usage heatmaps
• Temporal distribution analysis
• Building-level visualizations

Dataset

The analysis uses mobility data for Beer Sheva prepared by PGL Transportation Engineering and Planning Ltd. and collected by Decell:

• Time Period: November 2019 - February 2020, July 2021
• Coverage: Hundreds of thousands of unique users (18+)
• Scope: 13 Points of Interest
• Data Points:
  • Origin/Destination
  • Trip Purpose
  • Travel Mode
  • Travel Time
  • Entry/Exit times
  • Trip Frequency

Required Data Sources

1. Trip Data:

   • Excel files containing trip data (Proprietary)
   • Statistical area spatial data (GDB format)
   • POI coordinates (CSV from Google Maps API)

2. Spatial Data:

   • Building footprints (OpenStreetMap)
   • Road network data (OTP model built locally)
   • Statistical area boundaries

Note on Data Privacy

This project uses sensitive mobility data. Raw data files are not included in the repository. Ensure you have necessary permissions before using or sharing any data.