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Do the most vulnerable people live in the worst slums? A spatial analysis of Accra, Ghana.

, , and . Ann. GIS, 17 (4): 221-235 (2011)

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Do the most vulnerable people live in the worst slums? A spatial analysis of Accra, Ghana., , and . Ann. GIS, 17 (4): 221-235 (2011)The Role of Earth Observation in an Integrated Deprived Area Mapping "System" for Low-to-Middle Income Countries., , , , , , , , , and 2 other author(s). Remote. Sens., 12 (6): 982 (2020)A Methodology for Georeferencing and Mosaicking Corona Imagery in Semi-Arid Environments., , and . Remote. Sens., 14 (21): 5395 (2022)Evaluating the Ability to Use Contextual Features Derived from Multi-Scale Satellite Imagery to Map Spatial Patterns of Urban Attributes and Population Distributions., , , and . Remote. Sens., 13 (19): 3962 (2021)Mapping slums using spatial features in Accra, Ghana., , , , , , and . JURSE, page 1-4. IEEE, (2015)Open data for algorithms: mapping poverty in Belize using open satellite derived features and machine learning., , and . Inf. Technol. Dev., 27 (2): 263-292 (2021)Evaluating the Ability to Use Contextual Features to Map Deprived Areas 'Slums' in Multiple Cities., , , , , and . IGARSS, page 3620-3623. IEEE, (2023)Evaluating the relationship between spatial and spectral features derived from high spatial resolution satellite data and urban poverty in Colombo, Sri Lanka., , , , and . JURSE, page 1-4. IEEE, (2017)Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine., , , , and . Remote. Sens., 10 (8): 1226 (2018)Determining the Relationship Between Census Data and Spatial Features Derived From High-Resolution Imagery in Accra, Ghana., and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 9 (5): 1970-1977 (2016)