Skip to content

Crop Identification Using Satellite Data Analytics

Accurately monitoring production across the United States is going to be more crucial this growing season than ever as we manage several new unknown factors. From uncertainties around crops tour restrictions to accuracy of prospective planting reports in your area, it will be important to know what crops are planted and how yields are trending. Using our advanced satellite data analytics, we can help organizations with crop identification across the Midwest for a clearer view on corn and soybean yields.

As AgPro notes “North America’s biggest farm suppliers are accelerating shipments of fertilizer, seeds and agricultural chemicals to crop-growing regions in an unprecedented race against the coronavirus that threatens to disrupt planting season.” While planting data will provide an early view of what the year could bring, the risk factors presented between the pandemic and extreme weather events makes closely (or remotely, no pun intended) monitoring fields a necessary precaution.

The Normalized Difference Vegetation Index (NDVI) has proven to be a valuable index. It can be calculated from data acquired by many earth observation satellites to enable comparisons between counties or grain origination areas and between years. But it is always best to know what you are looking at: identifying crops makes measurements and yield modeling much more robust.

showing how Geosys crop mask improves NDVI data for specific crops

Last year, we released the crop mask into our Agriquest tool. Using the 2018 Iowa corn season as an example, you can clearly see the benefits of being able to identify crops from a state down to a county level.

Leveraging our extensive historical database of 30+ years of satellite imagery and machine learning, we’ve been able to test the crop masks for accuracy at properly identifying pixels as corn or soybean and for its ability to capture all the pixels for the given crop. The results of this testing for 2019 is illustrated in the graphic below showing F1-score results for 2019. A Score of 1 (the darkest green) indicated a perfect prediction.

F1 scores for Geosys crop identification analytics for 2019

By empowering automated crop identification, and measuring growing conditions for each crop separately, our clients have a better understanding for the actual production potential. This feeds models with more accurate data and delivers better yield forecasts.

You can access the analytics from the crop mask through our Agriquest tool, by subscribing to our Expert Service offerings or through Geosys API integrations. To learn more or see precise F1-scores for counties where your elevators are located, contact us today.

Share This Post

Share on twitter
Share on linkedin
Share on facebook
Share on email

More To Explore