Big data analytics to identify and overcome scaling limitations to climate-smart agricultural practices in South Asia (BigData2CSA)
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 however employed manipulative experiments analyzing limited agronomic variables, or survey data from project-driven initiatives. This can obscure the identification of relevant factors limiting CSA, at times leading to inappropriate extension, policy, and inadequate institutional alignments to address and overcome constraints. Alternative big data and data mining approaches utilizing heterogeneous datasets, however, remain insufficiently explored, though they can represent a powerful alternative source of technology and management practice performance information. In partnership with national research and extension systems (NARES) and the private sector, this project responds by developing systems to rapidly collect, process, analyze and interpret a wide variety of primary agronomic management and socioeconomic data from tens of thousands farmers. Fusing data with spatially-explicit soils and hydrological datasets, remote sensing, and gridded climate products, location-, age- and gender-specific factors contributing to or limiting CSA indicators (yield, profitability, GHG emission intensity, resilience) will be identified and represented through interactive web-based dashboards. Alignment with bilaterals and established institutional partnerships will assist in digitally reaching 500,000 farmers with customized management advice on CSA. Alongside the collaborative development of analytical tools, we expect these processes to be institutionalized by next-users, with research affecting agricultural policy and development decisions to enable the improved application of CSA.
Project Deliverables
Data portal/Tool/Model code/Computer software
Report from a regional workshop with key collaborators on institutional use of big data and CSA advisories
Infographic
Project informational graphic “Big data analytics for climate-smart agriculture in South Asia (Big Data 2 CSA)”
Journal Article (peer reviewed)
Major Climate risks and Adaptation Strategies of Smallholder Farmers in Coastal Bangladesh
Journal Article (peer reviewed)
Conservation agriculture for sustainable intensification in South Asia
Journal Article (peer reviewed)
Assess economic and environmental impacts of sustainable intensification of rice-wheat cropping systems through FarmDESIGN
Data portal/Tool/Model code/Computer software
Initial database integrating crop cut, management practice, remotely sensed and farmer survey information to evaluate and inform CSA technologies and practices
Data portal/Tool/Model code/Computer software
Completed digital data collection platform enabling rapid field survey and telephonic collection of crop management information to evaluate contributions to CSA
Journal Article (peer reviewed)
Portfolios of Climate Smart Agriculture Practices in Smallholder Rice-Wheat System of Eastern Indo-Gangetic Plains—Crop Productivity, Resource Use Efficiency and Environmental Foot Prints
Journal Article (peer reviewed)
Adoption and economic impacts of laser land leveling in the irrigated rice‐wheat system in Haryana, India using endogenous switching regression
Journal Article (peer reviewed)
Does women’s participation in agricultural technology adoption decisions affect the adoption of climate‐smart agriculture? Insights from Indo‐Gangetic Plains of India
Lecture/Training Course Material
Big Data for Climate Smart Agriculture: Training modules and tools for machine learning and interpretation of structured and semi-structured data
Journal Article (peer reviewed)
Learning adaptation to climate change from past climate extremes: evidence from recent climate extremes in Haryana, India
Article for media/Magazine/Other (not peer-reviewed)
Informational graphics on big data analytics and the Big Data 2 CSA project