Towards achieving the UNs data revolution: combining earth observation and socioeconomic data for geographic targeting of resources for the sustainable development goals

Abstract The UN has called for a ‘data revolution’ to help overcome the low quality and lack of regularly updated statistical data available in developing countries. But how do we achieve this with limited financial resources and insufficient capacity in national statistical offices around the world? Recent studies have demonstrated how information captured by satellite imagery can be combined with social datasets to increase our understanding of socioeconomic systems. Thus, in the future, satellite data may offer a cost-effective way to reliably measure and monitor progress towards development goals. We examine how satellite data can be linked with household and census datasets to provide information on socioeconomic conditions. We suggest that the Sustainable Livelihoods Approach provides an appropriate framework for which to develop remotely sensed earth observation (EO) data proxies for key socioeconomic conditions because it will allow the linking of data in a way that reflects more the way in which populations interact with landscapes. The aim of using EO data for mapping and predicting socioeconomic conditions is not to replace survey data but to provide more frequent information on likely socioeconomic conditions between census and survey enumeration. Timely recalibration of models predicting poverty from EO data would be necessary to reflect often rapid social, economic and political changes. However, if we are to acheive the SDGs more frequent data at finer spatial scales will be required and EO data provides a cos effective solution.