Abstract

Background. Rapid urban growth in low and middle income countries is frequently characterized by informal developments. The resulting social segregation and slums show disparities in health outcomes for the populations of the world’s megacities. To address these challenges, information on the spatial distribution of slums is necessary, yet the data are rarely available. The goal of this study was to use a remote sensing based approach to map urban slums in Dhaka, the second fastest growing megacity in the world. Methods. Slums were mapped through the visual interpretation of Quickbird satellite imagery between the years 2006 and 2010. Ancillary references included the 2005 census and mapping of slums, Google Earth, and geolocated photographs. The 2006 slums were first delineated and filtered in GIS to avoid small, isolated slums. For 2010, changes to the 2006 slums were defined over the latter’s polygons to retain border consistency. Conclusions. The dataset presented here can be considered a stepping stone for further research on slums and urban expansion in Dhaka. The slum distribution dataset is useful to be pooled with other data to reveal trends of informal settlement growth for local health policy advice in Dhaka.

Highlights

  • Within recent decades, high rates of urbanization in low and middle income countries led to the development of megacities with more than 10 million inhabitants [1, 2]

  • The slum distribution dataset is useful to be pooled with other data to reveal trends of informal settlement growth for local health policy advice in Dhaka

  • The mapping process was applied to the Dhaka metropolitan area (DMA), a region encompassing both the wards of the Dhaka city corporation (DCC) and the unions of the DMA

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Summary

Introduction

High rates of urbanization in low and middle income countries led to the development of megacities with more than 10 million inhabitants [1, 2]. With over 15 million inhabitants today, Dhaka is the second fastest growing megacity in the world [1]. The resulting social segregation and slums show disparities in health outcomes for the populations of the world’s megacities. To address these challenges, information on the spatial distribution of slums is necessary, yet the data are rarely available. The goal of this study was to use a remote sensing based approach to map urban slums in Dhaka, the second fastest growing megacity in the world.

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