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Area of Science:

  • Urban studies
  • Geospatial analysis
  • Demography

Background:

  • Accurate measurement of urbanization is vital for policy and planning.
  • Official Indian government statistics estimate only 31% of the population as urban.
  • Existing definitions may underestimate the true extent of urbanization in India.

Purpose of the Study:

  • To re-evaluate India's urbanization level using a novel methodology.
  • To create high-resolution population grids for improved urban characterization.
  • To identify and map urban agglomerations across India.

Main Methods:

  • Development of a random forest-based model to generate high-resolution population grids (approx. 100m).
  • Utilized Indian Census district-level data from 2001 and 2011.
  • Application of a community-detection clustering algorithm to define urban agglomerations.

Main Results:

  • An estimated 12% higher urban population compared to 2011 official statistics.
  • Identification of fewer mid-size cities than previously reported.
  • Discovery of trans-jurisdictional urban agglomerations in Kerala and the Gangetic Plain.

Conclusions:

  • India's urbanization level is underestimated by current definitions.
  • High-resolution population grids and advanced algorithms offer a more accurate picture of urban development.
  • Urban agglomerations often transcend administrative boundaries, requiring integrated planning approaches.