The Global South (GS) is currently facing rapid urbanization rates. This rapid urban growth will induce major changes in human population distribution, with important consequences on the environment, health and socio-economic development. Satellite remote sensing offers an effective solution for mapping settlements, monitoring urbanisation at different spatial and temporal scales and better understanding socio-economic patterns and their evolution. While a large part of the literature is dedicated to the mapping of urban areas in developed countries, studies focusing on the GS remain a minority. Intrinsic differences between cities in the GS, such as disparaging socio-economic fragmentation, extremely high population density, proliferation of deprived urban areas and data scarcity, require the use of specifically tailored approaches. This session will focus on novel remote sensing methods for improving our understanding of the urban environment in the GS, such as Machine and Deep learning, data fusion, new sensors or unconventional data. Along with applications that focus on the classification of the built environment (i.e land cover and land use) other types of remote sensing applications will be explored (ecosystem services, socio-economic, epidemiologic and demographic mapping).