A Comprehensive Guide to Calculating and Visualizing Metro Accessibility in Delhi NCR Using 3D Mapping
Comprehensive Guide on Medium: From Minutes to Maps: 3D Visualization of Metro Accessibility in Delhi, India
🌍 Interactive Map 🌍
Efficient public transportation is crucial in Delhi NCR. This article explores how to calculate and visualize metro accessibility using 3D mapping techniques, providing insights into travel times to the nearest metro station.
For this tutorial, we will cover the following steps:
- Getting Started: Overview of Python, Pandana, and OSMnx libraries.
- Data Collection: Fetching metro station locations and road networks using OSMnx.
- Data Preparation: Cleaning and visualizing data on a 2D map.
- Calculating Accessibility: Using Pandana to calculate travel times.
- 3D Visualization: Visualizing accessibility data in 3D
We use OSMnx to fetch metro station locations and the road network of Delhi NCR, forming the basis for our accessibility calculations.
Determining metro accessibility in an urban city is essential for effective urban planning, real estate valuation, and economic development. It helps identify underserved areas, reduce traffic congestion, and lower carbon emissions. Additionally, it enables residents to make informed decisions about where to live and work, enhancing overall quality of life.
We demonstrated how to calculate and visualize metro accessibility in Delhi NCR using Python libraries like OSMnx, Pandana, H3, and Pydeck, contributing to more connected and sustainable urban environments.
data/: Contains the pre-processed GIS data for metro stations and road networks.notebooks/: Jupyter notebooks with step-by-step code and explanations.scripts/: Python scripts for data processing and visualization.README.md: This file.
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