50x2030 at World Data Forum: Showcasing how ground data can augment satellite and other tech-based data collection
Through a series of short, rapid-fire presentations, five experts will share innovative work that is tackling the challenge of adding value to both traditional survey data and innovative data sources via their integration. Examples will include (a) using ground data to improve crop and yield maps at high resolution in smallholder production systems; (b) collecting objective plant, weather, and soil data through low-cost multiple-sensor stations; (c) setting-up an open infrastructure to make ground truthing datasets accessible at scale; (d) linking traditional and spatial data for official statistics, and (e) how to translate all this into benefits for smallholder farmers.
“From the Ground Up” will be chaired by Haishan Fu, director of the World Bank's Development Data Group and chair of the 50x2030 Partnership Council. She will draw the connection between the presentations and the ways in which the Initiative’s work program enables surveys to feed into remote sensing applications that produce actionable, high-resolution data of key indicators at-scale.
Presentations will be made by Talip Kilic, senior economist, World Bank; Hamed Alemohammad, chief data scientist, Radiant Earth Foundation; Jess Bollinger, vice president of strategic partnerships, Arable Labs; Dominik Rozkrut, president, Statistics Poland; and Keith Ahumuza, senior statistician, Uganda Bureau of Statistics (UBOS). These experts are each playing multiple roles as agricultural data producers, users, distributors, developers of new technologies or agents of integration of different data sources.
The session responds to a trend that sees the potential of satellites, machine learning, and artificial intelligence increasing the value of ground data that can be used to calibrate and validate remotely sensed estimates. It will coincide with the beginning of a work program spearheaded by the 50x2030 Initiative to facilitate the production, use and suitability of survey-based training datasets – constituting a public resource for other initiatives.
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