A high-frequency mobile phone data collection approach for research in social-environmental systems: Applications in climate variability and food security in sub-Saharan Africa

Stacey A. Giroux, Inna Kouper, Lyndon D. Estes, Jacob Schumacher, Kurt Waldman, Joel T. Greenshields, Stephanie L. Dickinson, Kelly K. Caylor, Tom P. Evans

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Collecting high-frequency social-environmental data about farming practices in sub-Saharan Africa can provide new insight into environmental changes that farmers face and how they respond within smallholder agro-ecosystems. Traditional data collection methods such as agricultural censuses are costly and not useful for understanding intra-annual and real-time decisions. Short-message service (SMS) has the potential to transform the nature of data collection in coupled social-ecological systems. We present a system for collecting, managing, and synthesizing weekly data from farmers, including data infrastructure for management of big and heterogeneous datasets; probabilistic data quality assessment tools; and visualization and analysis tools such as mapping and regression techniques. We discuss limitations of collecting social-environmental data via SMS and data integration challenges that arise when linking these data with other social and environmental data. In combination with high-frequency environmental data, such data will help ameliorate issues of scale mismatch and build resilience in environmental systems.

Original languageEnglish (US)
Pages (from-to)57-69
Number of pages13
JournalEnvironmental Modelling and Software
Volume119
DOIs
StatePublished - Sep 2019

Keywords

  • Farming
  • Food security
  • High frequency data
  • Short Message Service (SMS)
  • Sub-Saharan Africa

ASJC Scopus subject areas

  • Software
  • Environmental Engineering
  • Ecological Modeling

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