Heterogeneity in soils, hydrology, climate, and rapid changes in rural economies including fluctuating prices, aging and declining labor forces, agricultural feminization, and uneven market access are among the many factors that constrain climate-smart agriculture (CSA) in South Asia’s cereal-based farming systems.
Most previous research on CSA has employed manipulative experiments analyzing agronomic variables, or survey data from project-driven initiatives. However, this can obscure the identification of relevant factors limiting CSA, leading to inappropriate extension, policy, and inadequate institutional alignments to address and overcome limitations. Alternative big data approaches utilizing heterogeneous datasets remain insufficiently explored, though they can represent a powerful alternative source of technology and management practice performance information.
In partnership with national research systems and the private sector in Bangladesh, India and Nepal, Big data analytics for climate-smart agricultural practices in South Asia (Big Data2 CSA) is developing digital data collection systems to crowdsource, data-mine and interpret a wide variety of primary agronomic management and socioeconomic data from tens of thousands of smallholder rice and wheat farmers.
The project team analyzes these data by stacking them with spatially-explicit secondary environmental, climatic and remotely sensed data products, after which data mining and machine learning techniques are used to identify key factors contributing to patterns in yield, profitability, greenhouse gas emissions intensity and resilience.
These approaches however must be practical in order for them to be useful in agricultural development and policy. As such, the project’s analytical results will be represented through interactive web-based dashboards, with gender-appropriate crop management advisories deployed through interactive voice recognition technologies to farmers in Bangladesh, India and Nepal at a large-scale. Big Data2 CSA is supported by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Flagship 2 on Climate-Smart Technologies and Practices.
Objectives
- Develop ICT tools enabling digital collection of crop management data and a cloud-based database that can be managed by next-users
- Support advanced degree-level students to engage in field and data science research
- Create a digital data collection platform enabling crowd sourcing of crop management information to evaluate contributions to CSA
- Create interactive and customizable web-based dashboards presenting post-season research results and providing CSA management recommendations
- Organize CSA and big data policy briefings on mainstreaming processes and policy workshops
Climate adaptation and mitigation 