Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings

Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings

Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify the residential status of urban buildings in low and...

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Bibliographic Details
Main Authors: Christopher T. Lloyd, Hugh J. W. Sturrock, Douglas R. Leasure, Warren C. Jochem, Attila N. Lázár, Andrew J. Tatem
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
machine learning
building classification
superlearner
residential
building footprint
Online Access:https://www.mdpi.com/2072-4292/12/23/3847

Internet

https://www.mdpi.com/2072-4292/12/23/3847

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