Edinburgh Research Explorer

Satellite Earth observation of socioeconomic conditions for improved poverty reporting

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings of SPIE
Subtitle of host publicationSpace, Satellites and Sustainability
EditorsMurray Collins
PublisherSPIE
Volume11527
DOIs
Publication statusPublished - 16 Sep 2020

Abstract

The operational integration of Earth observation (EO) into the analysis of rural poverty and broader dynamics of human wellbeing is in its early stages. There is considerable scope for novel applications given the current proliferation of technological and computational capabilities. To develop this research agenda, it is necessary to synthesise scholarly contributions to the field in order to disseminate findings and stimulate debate, while catalysing uptake and development of methodologies. We conducted a systematic review of the scientific literature that investigates the novel applications of satellite EO for monitoring socioeconomic conditions and poverty in rural spaces of the Global South. We consider the challenges and opportunities for achieving evidence-based policymaking at finer temporal and spatial scales than is currently practised when measuring socioeconomic conditions. We investigate these challenges and the opportunities for integrating EO into monitoring poverty and human wellbeing in the context of sustainable rural development. Overall evidence suggests that the extensive spatial coverage and accessibility of data at different resolutions, paired with near real-time observations and a five-decade temporal legacy of satellite EO primes these data products for monitoring rural wellbeing. Our findings indicate a requirement to develop EO approaches for monitoring poverty dimensions across multiple spatial and temporal scales. Further requirements include testing the performance of methodologies in different social-ecological systems, to interrogate the performance of EO metrics when predicting different measures of rural poverty and wellbeing, and to operationalise the integration of disparate datasets.

ID: 173095955