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Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations
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 stud...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3558435/ https://www.ncbi.nlm.nih.gov/pubmed/23343099 http://dx.doi.org/10.1186/1476-072X-12-4 |
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author | Checchi, Francesco Stewart, Barclay T Palmer, Jennifer J Grundy, Chris |
author_facet | Checchi, Francesco Stewart, Barclay T Palmer, Jennifer J Grundy, Chris |
author_sort | Checchi, Francesco |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3558435 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35584352013-01-31 Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations Checchi, Francesco Stewart, Barclay T Palmer, Jennifer J Grundy, Chris Int J Health Geogr Research 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. BioMed Central 2013-01-23 /pmc/articles/PMC3558435/ /pubmed/23343099 http://dx.doi.org/10.1186/1476-072X-12-4 Text en Copyright ©2013 Checchi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Checchi, Francesco Stewart, Barclay T Palmer, Jennifer J Grundy, Chris Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title | Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title_full | Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title_fullStr | Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title_full_unstemmed | Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title_short | Validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
title_sort | validity and feasibility of a satellite imagery-based method for rapid estimation of displaced populations |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3558435/ https://www.ncbi.nlm.nih.gov/pubmed/23343099 http://dx.doi.org/10.1186/1476-072X-12-4 |
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