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 language | English (US) |
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Pages (from-to) | 57-69 |
Number of pages | 13 |
Journal | Environmental Modelling and Software |
Volume | 119 |
DOIs | |
State | Published - 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