  Mapping deprivation in urban areas is important, for example for identifying
areas of greatest need and planning interventions. Traditional ways of
obtaining deprivation estimates are based on either census or household survey
data, which in many areas is unavailable or difficult to collect. However,
there has been a huge rise in the amount of new, non-traditional forms of data,
such as satellite imagery and cell-phone call-record data, which may contain
information useful for identifying deprivation. We use Angle-Based Joint and
Individual Variation Explained (AJIVE) to jointly model satellite imagery data,
cell-phone data, and survey data for the city of Dar es Salaam, Tanzania. We
first identify interpretable low-dimensional structure from the imagery and
cell-phone data, and find that we can use these to identify deprivation. We
then consider what is gained from further incorporating the more traditional
and costly survey data. We also introduce a scalar measure of deprivation as a
response variable to be predicted, and consider various approaches to multiview
regression, including using AJIVE scores as predictors.
