| Modelling the Wealth Index of Demographic and Health Surveys within Cities Using Very High-Resolution Remotely Sensed Information |
| Authors: |
Stefanos Georganos, Assane Niang Gadiaga, Catherine Linard, Tais Grippa, Sabine Vanhuysse, Nicholus Mboga, Eléonore Wol, Sébastien Dujardin, and Moritz Lennert |
| Source: |
Remote Sensing, 11: 2543; DOI: 10.3390/rs11212543 |
| Topic(s): |
GIS/GPS
Modelling
Poverty
Wealth Index
|
| Country: |
Africa
Senegal
|
| Published: |
OCT 2019 |
| Abstract: |
A systematic and precise understanding of urban socio-economic spatial inequalities in
developing regions is needed to address global sustainability goals. At the intra-urban scale, access
to detailed databases (i.e., a census) is often a dicult exercise. Geolocated surveys such as the
Demographic and Health Surveys (DHS) are a rich alternative source of such information but can be
challenging to interpolate at such a fine scale due to their spatial displacement, survey design and the
lack of very high-resolution (VHR) predictor variables in these regions. In this paper, we employ
satellite-derived VHR land-use/land-cover (LULC) datasets and couple them with the DHSWealth
Index (WI), a robust household wealth indicator, in order to provide city-scale wealth maps. We
undertake several modelling approaches using a random forest regressor as the underlying algorithm
and predict in several geographic administrative scales. We validate against an exhaustive census
database available for the city of Dakar, Senegal. Our results show that the WI was modelled to a
satisfactory degree when compared against census data even at very fine resolutions. These findings
might assist local authorities and stakeholders in rigorous evidence-based decision making and
facilitate the allocation of resources towards the most disadvantaged populations. Good practices for
further developments are discussed with the aim of upscaling these findings at the global scale.
Keywords: wealth index; DHS; very-high-resolution remote sensing; interpolation; machine
learning; poverty |
| Web: |
https://www.google.com/url?rct=j&sa=t&url=https://www.mdpi.com/2072-4292/11/21/2543/pdf&ct=ga&cd=CAEYDCoTODY4Mjk3NjU3MTU4MzE2MzI2ODIcNTZmYjJiMjRhMzEzNmNiNTpjb206ZW46VVM6TA&usg=AFQjCNHlrRf69Thr1BRpIXWf |
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