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Mapping Urban Land Use in India and Mexico using Remote Sensing and Machine Learning
2021
WRI Publications
This technical note describes the data sources and methodology underpinning a computer system for the automated generation of land use/land cover (LULC) maps of urban areas based on medium-resolution (10-30 m/pixel) satellite imagery. The system and maps deploy the LULC taxonomy of the Atlas of Urban Expansion-2016 Edition: open, nonresidential, roads, and four types of residential space. We used supervised machine-learning techniques to apply this taxonomy at scale. Distinguishing between
doi:10.46830/writn.20.00048
fatcat:e7uksq2lg5dnjnuse23xvc66di