The measurement and characterization of urbanization crucially depends upon defining what counts as urban. The government of India estimates that only 31% of the population is urban. We show that this is an artifact of the definition of urbanity and an underestimate of the level of urbanization in India. We use a random forest-based model to create a high-resolution (~ 100 m) population grid from district-level data available from the Indian Census for 2001 and 2011, a novel application of such methods to create temporally consistent population grids. We then apply a community-detection clustering algorithm to construct urban agglomerations for the entire country. Compared with the 2011 official statistics, we estimate 12% more of urban population, but find fewer mid-size cities. We also identify urban agglomerations that span jurisdictional boundaries across large portions of Kerala and the Gangetic Plain.

中文翻译：

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失踪的数百万人：低估了印度的城市化进程

城市化的衡量和表征关键取决于对城市的定义。印度政府估计只有 31% 的人口居住在城市。我们表明，这是城市化定义的人为因素，也是对印度城市化水平的低估。我们使用基于随机森林的模型，根据 2001 年和 2011 年印度人口普查提供的地区级数据创建高分辨率（~ 100 m）人口网格，这是此类方法创建时间一致人口网格的新颖应用。然后，我们应用社区检测聚类算法来构建整个国家的城市群。与 2011 年官方统计数据相比，我们估计城市人口增加了 12%，但中型城市数量较少。我们还确定了跨越喀拉拉邦和恒河平原大部分地区管辖边界的城市群。