Remote Sensing Powers New Granular Profitability Insights

Remote sensing, or gathering information about a field or subfield area without actually visiting it, is gaining traction quickly within the ag industry as its accuracy and use cases continue to build. Learn more about remote sensing at Granular, along with how it’s being used in Profit Maps, a joint collaboration between John Deere and Granular, in this Q&A with Michael Asher, Data Science Lead for Granular.


Q: Can you please tell us a bit about your role and background?

A: I’ve always wanted to contribute to ag, but I’m better at numbers and computers than using my hands. I studied math and computer science in my home of Australia and then made my way into agriculture. Our team uses satellite and other sources of continental scale data to model crop growth.

Q: Why is remote sensing such a hot topic in agriculture right now?

A: I think it’s gaining traction for a couple reasons. One, being able to forecast crop yields has potential implications for economics, food security, and human welfare. Having insight into yield months in advance of harvest allows for better logistical and financial planning for growers. Second, the data we can use for remote sensing purposes has improved dramatically in the past decade. With improved data comes improved results, so remote sensing is proving to be an increasingly valuable asset to the ag industry.

Q: What powers remote sensing at Granular?

A: We take all kinds of data points into consideration, including satellite imagery from 6 different satellites, weather data, elevation data, soil data, and historical yields from around a region. By using all those datasets, we model at a high resolution what yield is going to be. It’s something we’ve been working on for years at Corteva, and I’ve been focused on it since I came to Granular.

Q: How can growers use yield modeling?

A: In-season, there’s a few different use cases we’re developing. The obvious one is scouting. You can use this layer the same way you would use crop health imagery to identify issues in field during the seasons. Instead of looking at something abstract like crop health index or NDVI, you’d be looking at a bushels per acre value. It’s not just straight NDVI, it’s more accurate than that. For example, trials should show up early, along with issues related to machinery, irrigation or a particular hybrid in-season. We’re hoping to develop the product down the track further into in-season decisions. For example, you could use it to decide on whether to a fungicide application. There are obvious implications for grain marketing, although I don’t recommend using the model for that at this time.

Q: How will you and the remote sensing team at Granular continue to improve this yield model going forward?

A: Fortunately for our team, the remote sensing space is growing very rapidly, so there’s always more high-resolution data imagery coming online. So, we’re continuously incorporating more data as it becomes available.

Q: Where can growers go to learn more about Profit Maps and these new yield model opportunities?

A: Growers who use John Deere equipment can find Profit Maps in the John Deere Operations Center by finding the Granular logo in the tools section. I would encourage growers to check it out. We’ve all seen how innovation in agriculture can protect yield and profitability, so this year especially is a good time to use all the information you can to make the best decisions possible.


Michael Asher, Remote Sensing Data Science Lead, can be reached at (734) 277-0537 or [email protected]. Learn more about Profit Maps here. For more information about the exclusive Granular Insights discount for John Deere customers here.

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