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Identifying Urban Areas by Combining Human Judgment and Machine Learning : An Application to India

This paper proposes a methodology for identifying urban areas that combines subjective assessments with machine learning, and applies it to India, a country where several studies see the official urbanization rate as an under-estimate. For a repres...

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Bibliographic Details
Main Authors: Galdo, Virgilio, Li, Yue, Rama, Martin
Language:English
Published: World Bank, Washington, DC 2020
Subjects:
URBAN AREA
URBANIZATION
HUMAN JUDGMENT
GOOGLE IMAGES
CROWD SOURCING
POPULATION CENSUS
SATELLITE IMAGERY
MACHINE LEARNING
LOGIT MODEL
LASSO
RANDOM FORESTS METHOD
Online Access:http://documents.worldbank.org/curated/en/920791582554716856/Identifying-Urban-Areas-by-Combining-Human-Judgment-and-Machine-Learning-An-Application-to-India
http://hdl.handle.net/10986/33392

Internet

http://documents.worldbank.org/curated/en/920791582554716856/Identifying-Urban-Areas-by-Combining-Human-Judgment-and-Machine-Learning-An-Application-to-India
http://hdl.handle.net/10986/33392

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