Poverty mapping innovative approaches to creating poverty maps with new data sources

Geographically disaggregated poverty data are vital for better understanding development issues and ensuring development efforts are directed
to the places where they are most needed. Poverty has traditionally been
measured by data on consumption, income, or assets. However, recent advances in computing power and the emergence of new methods has made
it increasingly feasible to produce reliable, cost-effective, and timely poverty maps by extracting features from novel data sources such as satellite
imagery, call detail records, and internet connectivity indicators.
This paper explores the methodological implications of using both traditional and novel data sources to generate poverty maps. Specifically, it
examines the applications of (i) survey and census data; (ii) Global System
for Mobile Communications, smartphone, and Wi-Fi indicators; (iii) call
detail records; (iv) daytime and nighttime remote sensing imagery; and
(v) the Survey of Well-being via Instant and Frequent Tracking for poverty
mapping. Each section provides a brief overview of the data requirements,
methodology, and applicability considerations of the data source under
consideration. In addition, the paper discusses the usefulness and limitations of each approach in the field of evaluation, providing concrete
examples of poverty maps created from each of the listed data sources.