Microlevel structural poverty estimates for southern and eastern Africa.

ABSTRACT: For many countries in the Global South traditional poverty estimates are available only infrequently and at coarse spatial resolutions, if at all. This limits decision-makers' and analysts' ability to target humanitarian and development interventions and makes it difficult to study relationships between poverty and other natural and human phenomena at finer spatial scales. Advances in Earth observation and machine learning-based methods have proven capable of generating more granular estimates of relative asset wealth indices. They have been less successful in predicting the consumption-based poverty measures most commonly used by decision-makers, those tied to national and international poverty lines. For a study area including four countries in southern and eastern Africa, we pilot a two

SUBMITTER: Tennant E 

PROVIDER: S-EPMC11831177 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature