Balk Deborah, Montgomery Mark R, Engin Hasim, Lin Natalie, Major Elizabeth, Jones Bryan
CUNY Institute for Demographic Research, City University of New York, New York, NY 10010, USA.
Baruch College Marxe School of Public and International Affairs, City University of New York, New York, NY 10017, USA.
Data (Basel). 2019 Mar;4(1). doi: 10.3390/data4010035. Epub 2019 Feb 26.
India is the world's most populous country, yet also one of the least urban. It has long been known that India's official estimates of urban percentages conflict with estimates derived from alternative conceptions of urbanization. To date, however, the detailed spatial and settlement boundary data needed to analyze and reconcile these differences have not been available. This paper presents gridded estimates of population at a resolution of 1 km along with two spatial renderings of urban areas-one based on the official tabulations of population and settlement types (i.e., statutory towns, outgrowths, and census towns) and the other on remotely-sensed measures of built-up land derived from the Global Human Settlement Layer. We also cross-classified the census data and the remotely-sensed data to construct a hybrid representation of the continuum of urban settlement. In their spatial detail, these materials go well beyond what has previously been available in the public domain, and thereby provide an empirical basis for comparison among competing conceptual models of urbanization.
印度是世界上人口最多的国家，但也是城市化程度最低的国家之一。长期以来，人们一直知道印度官方对城市人口百分比的估计与基于其他城市化概念得出的估计存在冲突。然而，迄今为止，分析和协调这些差异所需的详细空间和聚居地边界数据尚未可得。本文呈现了分辨率为1公里的网格化人口估计数据，以及两种城市区域的空间呈现——一种基于人口和聚居地类型的官方统计表格（即法定城镇、郊区和普查城镇），另一种基于源自全球人类聚居层的建成区遥感测量数据。我们还对普查数据和遥感数据进行了交叉分类，以构建城市聚居连续体的混合表示。在空间细节方面，这些资料远超此前公开可得的内容，从而为比较相互竞争的城市化概念模型提供了实证依据。
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