Small Area Estimation zonal statistics Mozambique 

Remotely sensed data, i.e. data collected from satellites and sensors orbiting the Earth, are increasingly being used in modelling of poverty at small geographical areas. In this guide we show how to leverage remotely sensed data in combination with household surveys to produce spatially disaggregated poverty statistics, using the example of Bangladesh.

Complimenting this guide to Small Area Estimation of poverty, this resource offers ready zonal statistics at administrative level 3 in Mozambique that can be used as inputs into poverty modelling. The statistics were obtained from geo-spatial data on population density, accessibility to urban and health centres, topography, and nightlights. The methodology for combining the covariates from this resource with household survey data in order to produce poverty maps for small geographical areas, are detailed in the guide.