title: Satellite-aided survey sampling and implementation in low- and middle-income contexts: a low-cost/low-tech alternative.
abstract: BACKGROUND
  The increasing availability of online maps, satellite imagery, and digital technology can ease common constraints of survey sampling in low- and middle-income countries. However, existing approaches require specialised software and user skills, professional GPS equipment, and/or commercial data sources; they tend to neglect spatial sampling considerations when using satellite maps; and they continue to face implementation challenges analogous to conventional survey implementation methods. This paper presents an alternative way of utilising satellite maps and digital aides that aims to address these challenges.
  
  
  RESULTS
  The case studies of two rural household surveys in Rajasthan (India) and Gansu (China) compare conventional survey sampling and implementation techniques with the use of online map services such as Google, Bing, and HERE maps. Modern yet basic digital technology can be integrated into the processes of preparing, implementing, and monitoring a rural household survey. Satellite-aided systematic random sampling enhanced the spatial representativeness of the village samples and entailed savings of approximately £4000 compared to conventional household listing, while reducing the duration of the main survey by at least 25 %.
  
  
  CONCLUSIONS
  This low-cost/low-tech satellite-aided survey sampling approach can be useful for student researchers and resource-constrained research projects operating in low- and middle-income contexts with high survey implementation costs. While achieving transparent and efficient survey implementation at low costs, researchers aiming to adopt a similar process should be aware of the locational, technical, and logistical requirements as well as the methodological challenges of this strategy.
authors.affiliation: Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK ; CABDyN Complexity Centre, Saïd Business School, University of Oxford, Oxford, UK ; Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: Marco J
authors.identifier: 0000-0002-5849-7131
authors.initials: MJ
authors.lastname: Haenssgen
keywords: Bing Maps; China; Google Maps; Implementation; India; Rural; Sampling; Survey