Urbanization in India: Population and Urban Classification Grids for 2011.

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Data Pub Date : 2019-03-01 DOI:10.3390/data4010035

Deborah Balk, Mark R Montgomery, Hasim Engin, Natalie Lin, Elizabeth Major, Bryan Jones

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引用次数: 42

Abstract

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.

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印度的城市化:2011年人口和城市分类网格。

印度是世界上人口最多的国家，但也是城市化最少的国家之一。人们早就知道，印度官方对城市百分比的估计与从其他城市化概念中得出的估计相冲突。然而，到目前为止，还没有分析和调和这些差异所需的详细空间和聚落边界数据。本文以1公里的分辨率给出了网格化的人口估计值以及城市地区的两个空间效果图——一个基于人口和聚落类型(即法定城镇、外生城镇和人口普查城镇)的官方表格，另一个基于全球人类聚落层对建成区的遥感测量。我们还交叉分类了人口普查数据和遥感数据，构建了城市住区连续体的混合表示。在空间细节方面，这些材料远远超出了以前在公共领域可用的材料，从而为相互竞争的城市化概念模型之间的比较提供了经验基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data Decision Sciences-Information Systems and Management

CiteScore

4.30

自引率

3.80%

发文量

审稿时长

10 weeks