Identifying Urban Areas by Combining Data from the Ground and from Outer Space: An Application to India

34 Pages Posted: 30 Oct 2018 Last revised: 31 Oct 2018

See all articles by Virgilio Galdo

Virgilio Galdo

Michigan State University - Economics

Yue Li

World Bank

Martin Rama

World Bank

Date Written: October 29, 2018

Abstract

This paper develops a tractable method to identify urban areas and applies it to India, where urbanization is messy. Google Earth images are assessed subjectively to determine whether a stratified large sample of Indian cities, towns and villages, as officially defined, are urban or rural in practice. Based on these assessments, a regression analysis combines two sources of information?data from georeferenced population censuses and data from satellite imagery?to identify the correlates of units in the sample being urban. The resulting model is used to predict whether the other units in the country are urban or rural in practice. Contrary to frequent claims, India is not substantially more urban than implied by census data. And the speed of urbanization is only marginally higher than official statistics suggest. But a considerable number of locations are misclassified in the midrange between villages and state capitals. The results confirm the value of combining subjective assessments with data from these different sources.

Suggested Citation

Galdo, Virgilio and Li, Yue and Rama, Martin, Identifying Urban Areas by Combining Data from the Ground and from Outer Space: An Application to India (October 29, 2018). World Bank Policy Research Working Paper No. 8628. Available at SSRN: https://ssrn.com/abstract=3275046

Virgilio Galdo (Contact Author)

Michigan State University - Economics ( email )

Agriculture Hall
East Lansing, MI 48824-1122
United States
517-203-8372 (Phone)

HOME PAGE: http://search.msu.edu/people/index.php?uid=488171&prev=Galdo,%20Virgilio

Yue Li

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Martin Rama

World Bank ( email )

1818 H. Street, N.W.
Washington, DC 20433
United States

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