Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations

Author:

Checchi Francesco,Stewart Barclay T,Palmer Jennifer J,Grundy Chris

Abstract

Abstract Background Estimating the size of forcibly displaced populations is key to documenting their plight and allocating sufficient resources to their assistance, but is often not done, particularly during the acute phase of displacement, due to methodological challenges and inaccessibility. In this study, we explored the potential use of very high resolution satellite imagery to remotely estimate forcibly displaced populations. Methods Our method consisted of multiplying (i) manual counts of assumed residential structures on a satellite image and (ii) estimates of the mean number of people per structure (structure occupancy) obtained from publicly available reports. We computed population estimates for 11 sites in Bangladesh, Chad, Democratic Republic of Congo, Ethiopia, Haiti, Kenya and Mozambique (six refugee camps, three internally displaced persons’ camps and two urban neighbourhoods with a mixture of residents and displaced) ranging in population from 1,969 to 90,547, and compared these to “gold standard” reference population figures from census or other robust methods. Results Structure counts by independent analysts were reasonably consistent. Between one and 11 occupancy reports were available per site and most of these reported people per household rather than per structure. The imagery-based method had a precision relative to reference population figures of <10% in four sites and 10–30% in three sites, but severely over-estimated the population in an Ethiopian camp with implausible occupancy data and two post-earthquake Haiti sites featuring dense and complex residential layout. For each site, estimates were produced in 2–5 working person-days. Conclusions In settings with clearly distinguishable individual structures, the remote, imagery-based method had reasonable accuracy for the purposes of rapid estimation, was simple and quick to implement, and would likely perform better in more current application. However, it may have insurmountable limitations in settings featuring connected buildings or shelters, a complex pattern of roofs and multi-level buildings. Based on these results, we discuss possible ways forward for the method’s development.

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health,General Business, Management and Accounting,General Computer Science

Reference30 articles.

1. United Nations High Commissioner for Refugees: A year of crises: UNHCR Global Trends 2011. 2012, Geneva: UNHCR, http://www.unhcr.org/4fd6f87f9.html,

2. Noji EK: Estimating population size in emergencies. Bull World Health Organ. 2005, 83 (3): 164-

3. United Nations General Assembly: Statute of the Office of the High Commissioner for Refugees: General Assembly Resolution 428 (V). 1950, New York: United Nations

4. The Sphere Project: Sphere Handbook. 2004, Geneva: The Sphere Project, http://www.sphereproject.org,

5. United Nations High Commissioner for Refugees: Handbook for Emergencies: Second Edition. 2000, Geneva:UNHCR

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