Mapping poverty using mobile phone and satellite data
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2291
- Type
- D - Journal article
- DOI
-
10.1098/rsif.2016.0690
- Title of journal
- Journal of the Royal Society Interface
- Article number
- ARTN 20160690
- First page
- -
- Volume
- 14
- Issue
- 127
- ISSN
- 1742-5689
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
10.1098/rsif.2016.0690
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
14
- Research group(s)
-
-
- Citation count
- 49
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Poverty measurements mainly rely on census data, which is expensive and often out-of-date. We show how aggregated mobile phone and geospatial data can be combined to provide high-accuracy regional poverty estimates, enabling more frequent and finer granularity measurements. This international collaboration included Telenor (www.telenor.com), and the method is used by Flowminder.org in Haiti in collaboration with the World Bank to estimate poverty distribution in Cap Haitien. It is also part of a proposal to the World Bank to map poverty nationally in order to support the national cholera elimination plan (Flowminder, contact: FoEREF@ic.ac.uk). High Altmetrics score (https://royalsociety.altmetric.com/details/16018312/news).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
