“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty.

iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry and academia, will share their datasets to help create ever more accurate maps. If you would like to access the resource ahead of the session, please visit the iSDAsoil website: https://isda-africa.com/isdasoil/

This interactive session will include a detailed demonstration of the resource, panel member feedback on use and prospects of iSDAsoil, answering FAQ received ahead of the session, and an open discussion with session participants on user experience and further developments. If you have any questions or feedback please send these to: info@isda-africa.com

The session will be structured as follows:

Demonstration

• Matt Miller - Lead Data Scientist, iSDA

Feedback from panel members and Q&A with audience

• Those who have already made use of iSDAsoil API in Africa
• Fertilizer manufacturers and soil analysis companies working in Africa
• Soil and agronomy researchers working in Africa

Q&A between participants and iSDA team

• Matt Miller - Lead Data Scientist, iSDA
• Jamie Collinson - CTO, iSDA
• Keith Shepherd - Head of Diagnostics & Decision Science, iSDA
• Jonathan Crouch – CEO, iSDA (session chair)