Urban Poverty Mapping with Open Spatial Data: Evidence from Dar es Salaam

Peter Fisker and Kenneth Mdadila
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Peter Fisker: Development Economics Research Group, University of Copenhagen
Kenneth Mdadila: University of Dar es Salaam, School of Economics

No 22-17, DERG working paper series from University of Copenhagen. Department of Economics. Development Economics Research Group (DERG)

Abstract: This paper combines information from a representative household survey with publicly available spatial data extracted from satellite images to produce a high-resolution poverty map of Dar es Salaam. In particular, it builds a prediction model for per capita household consumption based on characteristics of the immediate neighborhood of the household, including the density of roads and buildings, the average size of houses, distances to places of interest, and night-time lights. The resulting poverty map of Dar es Salaam dramatically improves the spatial resolution of previous examples. Extreme Gradient Boosting (XGB) performs best in predicting household consumption levels given the input data. This result demonstrates the simplicity with which policy-relevant information containing a spatial dimension can be generated.

Keywords: Poverty; small-area estimation; building footprints; prediction models (search for similar items in EconPapers)
JEL-codes: O18 Q54 R11 (search for similar items in EconPapers)
Pages: 16
Date: 2022-12-17
New Economics Papers: this item is included in nep-big, nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:kud:kuderg:2217

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