A policy framework for non-motorised transport in Rajkot, India

Public transport and non-motorized transport can be up to 20 times more space-efficient than private cars. This is particularly relevant in an urban context where space is a constrained resource. Yet space use is rarely assessed explicitly in urban transport planning, the connection between low carbon transport planning agendas and the wider concept of ecological footprint is not widely understood or appreciated. And there exists no standard method for quantifying the use of space in complex urban settings in developing countries.

The provision of transport space and availability of transport modes allows for individual mobility and thereby access to jobs and other essential activities like shopping, social, health and recreation. Access to jobs, markets and recreation places are tied to residential land prices. Proximity to busy roads can expose residents to air pollution, thus having a negative influence on residential land price. The presence of footpaths, adequate streetlight and trees in the neighbourhood can also influence land prices.

This research project:

1. Builds on the space-time concept to propose a method for quantifying and comparing the circulation space, parking space and ecological space between transport modes

2. Models residential land prices for Rajkot city in western India using a Hedonic Price Regression (HPR) and Geographically Weighted Regression (GWR) modelling techniques to identify how accessibility, neighbourhood environment and neighbourhood type affect land prices

3. Quantifies the rental cost of space occupied by each mode and equates it with what each mode pays back in taxes (fuel tax and vehicle tax) and in the form of land value appreciation due to increased accessibility

4. Showcases these methods by evaluating a Low-carbon Comprehensive Mobility Plan (LCMP) scenario against a business-as-usual (BAU) scenario in the city of Rajkot, India. This is based on a multi-modal transport model elaborated for the design of the LCMP.