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Ryan Kmetz is back to talk with us about

This initiative began in January 2026. It is about analyzing satellite data to predict the monthly World Agricultural Supply and Demand Estimates (WASDE) reports. Ryan proposes a novel approach and shares some eye raising stats about lead times and profitability. This episode is inspiration for how we are all equipped to process the world using free data and AI. What can you do with your geospatial basic training?

Links to items discussed:

1. SatYield https://www.satyield.com/

2. Sentinel

   1. ESA https://sentinels.copernicus.eu/web/sentinel/copernicus/sentinel-2

   2. Google Earth Engine https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED#description

3. Landsat

   1. NASA https://science.nasa.gov/mission/landsat/

   2. Google Earth Engine https://developers.google.com/earth-engine/datasets/catalog/landsat

4. Taylor Geospatial Engine field boundaries

   1. Background https://taylorgeospatial.org/agricultural-field-boundaries-mapped-globally-for-the-first-time/

   2. Web app https://fieldsofthe.world/

5. Field boundaries from Planet https://docs.planet.com/data/planetary-variables/field-boundaries/

6. ‘As the world turns’ Blackrock geospatial podcast https://www.blackrock.com/us/individual/podcasts/the-bid/geospatial-data

7. Novi

This episode elsewhere: