Urban mapping in Dar es Salaam using AJIVE

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Carrington, Rachel J., Dryden, Ian L., Ellis, Madeleine, Goulding, James O., Preston, Simon P., Sirl, David J.
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912425928818688
author Carrington, Rachel J.
Dryden, Ian L.
Ellis, Madeleine
Goulding, James O.
Preston, Simon P.
Sirl, David J.
author_facet Carrington, Rachel J.
Dryden, Ian L.
Ellis, Madeleine
Goulding, James O.
Preston, Simon P.
Sirl, David J.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_09014
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Urban mapping in Dar es Salaam using AJIVE
Carrington, Rachel J.
Dryden, Ian L.
Ellis, Madeleine
Goulding, James O.
Preston, Simon P.
Sirl, David J.
Applications
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.
title Urban mapping in Dar es Salaam using AJIVE
topic Applications
url https://arxiv.org/abs/2403.09014