PROJECT OVERVIEW AND KEY FINDINGS
Estimating the size of displaced populations is key to planning and providing appropriate levels of assistance that meet international standards across sectors. Triangulating estimates from a variety of sources is useful for determining actual population size. While analyzing high-resolution satellite imagery can help develop population estimates, it is rarely used by humanitarian responders. For that reason, PRM funded the London School of Tropical Hygiene and Medicine (LSTHM) to carry out a research study on the validity and feasibility of refugee and IDP population estimation with satellite imagery. Key findings include:
· In settings with individual structures (such as non-urban settings) analyzing satellite imagery has reasonable (70-80%) accuracy for the purpose of rapid estimation, was comparatively easy to conduct, and could be further improved over time.
Drawing from this research, LSTHM developed the following recommendations for humanitarian actors interested in satellite imagery for rapid population estimation.
To UN agencies:
· Designate an agency or cluster with responsibility for coordinating efforts to develop and deploy methods for population estimation in emergencies.
· Establish a designated, adequately funded and agile technical unit, housed within an impartial humanitarian agency or a center of excellence, tasked with performing population estimation using any methods determined to be ready for deployment.
To field-based agencies:
· Contribute to efforts to estimate displaced and/or crisis-affected populations as quickly as possible after the onset of an emergency, by facilitating fieldwork, seconding staff for data collection, and advocating for the importance of population estimation.
· Encourage coordination among humanitarian stakeholders as well as leadership by the UN family and/or the relevant humanitarian cluster (camp coordination, shelter or health), so as to ensure that resources and initiatives for satellite imagery use and population estimation are harmonized and streamlined.
· Carry out real-time, opportunistic validation of our proposed remote method in additional sites, ideally IDP settlements and acute emergency scenarios.
· Refine the structure occupancy hierarchy of evidence, with group expert consensus on criteria and sub-scores for each, e.g. based on similar exercises for mortality and nutritional surveys.
· Develop a user-friendly, open-source software application (e.g. as an extension of Google Earth or OpenStreetMap), enabling any online user to analyse images manually and mark structures.
· Undertake further validation of approaches combining remote structure tallying and ground-based occupancy data collection, particularly for urban displaced populations.