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A methodology to modify land uses in a transit oriented development scenario.

Akshay Sahu1

  • 1Ranbir & Chitra Gupta School of Infrastructure Design and Management, IIT Kharagpur, Kharagpur, West Bengal, India.

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|January 3, 2018
PubMed
Summary

Developing nations can optimize urban planning with a new soft computing methodology for transit-oriented development (TOD). This approach modifies land use plans to better integrate transit, improving density and diversity for decongested transportation systems.

Keywords:
Distance to transitDiversityLand useNaya RaipurTransit oriented development

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Area of Science:

  • Urban Planning and Transportation Science
  • Soft Computing and Artificial Intelligence
  • Geographic Information Systems

Background:

  • Developing nations increasingly adopt transit-oriented development (TOD) to alleviate transportation congestion.
  • Existing land use plans often precede TOD strategy implementation, creating a planning gap.
  • Effective land use modification is crucial for successful TOD integration.

Purpose of the Study:

  • To develop a soft computing methodology for modifying existing land use plans to align with TOD objectives.
  • To create alternate land use plans that enhance TOD characteristics in developing urban contexts.
  • To provide a framework for integrating expert knowledge and multi-objective optimization in land use planning.

Main Methods:

  • Incorporation of global TOD parameters (density, diversity, distance to transit) with expert-defined weights and ranges for an Indian context.
  • Development of land use allocation rules and objective functions focused on maximizing density, shaping diversity, minimizing land use change, and increasing compactness.
  • Application of a genetic algorithm (GA) for generating and refining alternate land use plans based on an initial population of random plans.

Main Results:

  • A novel methodology was successfully applied to two sectors in Naya Raipur, India, demonstrating its practical applicability.
  • The genetic algorithm effectively generated numerous alternate land use plans, with the best plan showing potential merits compared to existing TOD implementations.
  • Empirical validation through comparison with initial land use plans confirmed the methodology's effectiveness in generating relevant TOD land use scenarios.

Conclusions:

  • The developed soft computing methodology offers a viable approach for creating effective TOD-aligned land use plans in developing nations.
  • This approach allows for the systematic modification of land use to meet multiple, often competing, urban development objectives.
  • The study provides a replicable framework for optimizing land use planning in conjunction with transit infrastructure development.