🗺️ Urban Accessibility Analysis - Qazvin Public Transport

An interactive web-based dashboard for analyzing and visualizing public transport accessibility in Qazvin, Iran.

📖 Overview

This project provides a Streamlit-powered dashboard for evaluating urban accessibility via public transport in the city of Qazvin.
It implements gravity-based accessibility models using exponential and Gaussian impedance functions, and supports:

• 🗺️ Interactive choropleth maps of accessibility for each type of destination
• ⚙️ Adjustable impedance function parameters (β, μ, σ)
• 🎯 Aggregated multi-destination accessibility analysis with weighted trip generation rates
• 🚌 Optional visualization of public transport routes
• 📊 Interactive statistics and map-based analytics

The dashboard enables urban planners and transport analysts to explore accessibility inequalities and spatial patterns efficiently.

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🧰 Technologies Used

• Streamlit — Web-based interactive dashboard
• GeoPandas — Geospatial data processing
• Plotly (Graph Objects & Express) — Dynamic map visualizations
• Matplotlib — Impedance function plots
• NumPy / Pandas — Data manipulation and analysis
• SciPy (norm.cdf) — Gaussian impedance computation

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🗂️ Destination Types

The application analyzes accessibility to 14 destination categories:

Category	Emoji	Description
Chain Stores	🛒	Major retail chains and supermarkets
Fruit Markets	🍒	Fresh produce markets
Clothing Complexes	👔	Shopping centers for clothing
Mobile Complexes	📲	Electronics and mobile phone shops
Cinemas	🎬	Movie theaters
Parks	🛝	Public parks and green spaces
Sports Complexes	🏟️	Sports facilities and gyms
Banks	🏦	Banking institutions
Schools	🏫	Educational institutions
Cultural Centers	🏛️	Community and cultural facilities
Mosques	🕌	Places of worship
Health Centers	🩺	Primary healthcare facilities
Public Hospitals	🏨	Public healthcare institutions
Private Hospitals	🏥	Private healthcare institutions

🚀 Installation

Prerequisites

• Python 3.8 or higher
• pip package manager

Setup Steps

1. Clone the repository

   git clone https://github.com/Ali8D/acc_dashboard.git
   cd acc_dashboard

2. Install dependencies

   pip install -r requirements.txt

3. Verify data structure Ensure your project structure looks like this:

   qazvin-accessibility/
   ├── access_streamlit.py          # Main application
   ├── requirements.txt              # Dependencies
   ├── README.md                     # This file
   │
   └── data_qaz/
       ├── zones_areas2.geojson
       ├── BusRoutes_for_Streamlit.geojson
       ├── img_TransitNetwork.png
       │
       └── input/
           ├── traveltime_cen_to_opps/
           │   ├── qaz_mx_chainstores.csv
           │   ├── qaz_mx_FruitMarkets.csv
           │   └── ... (other CSV files)
           │
           └── opps_points/
               ├── chain_stores/geojson/
               ├── fruit_markets/geojson/
               └── ... (other geojson folders)
   

🎮 Usage

Running the Application

streamlit run qaz_acc_dashboard.py

The app will automatically open in your browser at http://localhost:8501 .

Contact: alidarvishvand28@gmail.com