Mapping Population: Feasibility of Satellite Derived Metrics in Data-Poor Regions

Authors: Amanda Hoffman-Hall*, University of Maryland
Topics: Remote Sensing, Population Geography, Medical and Health Geography
Keywords: population, landsat, remote sensing, myanmar, rakhine, malaria
Session Type: Paper
Day: 4/10/2018
Start / End Time: 2:40 PM / 4:20 PM
Room: Lafayette, Marriott, River Tower Elevators, 41st Floor
Presentation File: No File Uploaded


Many countries and territories across the globe lack the infrastructure and resources to consistently and accurately map their population distributions. However, these maps are crucial to issues of disaster response, global health, environmental conservation, and more. This paper uses Ann Township within Rakhine State, Myanmar as a case study within a global health context. Specifically, in support of the World Health Organization's goal of malaria eradication. Satellite derived metrics are used to map the population distribution of Ann Township to allow for targeted malaria interventions in both space and time. Political instability, civil wars, and boycotts have plagued the Myanmar censuses of 1973, 1983, and 2014. For this reason, a census-independent methodology is employed. Utilizing Landsat OLI imagery, very high resolution imagery, and other satellite derived metrics, a 30 m population distribution map has been created. The methodology presented is place-specific but can be adapted to other data-poor regions needing reliable and timely population data.

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