Assessing land productivity and value by applying state-of-the-art machine learning and artificial intelligence techniques to remotely-sensed data.
CIBO Stability Score
Not all farm fields behave the same, and an individual field’s unique, sub-field behavior is hard to predict without significant operator experience and data, collected over a number of growing seasons. And the typical data used to explain in-field behavior, such as combine yield and precision maps—is almost never available in farm listings.
CIBO’s Stability Score and Performance Zone maps work to clearly communicate and visualize within-field variability over time. We use satellite imagery to look at the field variability over a 10-year period, then map out zones of high, medium, and low performance, as well as zones of significant variability (i.e. inconsistent performance).
What is field stability?
CIBO uses public and proprietary imagery and remotely sensed data to better understand land use, field-level variability, and land performance over time.
We provide deeper insight to those interested in farm land, so they understand what drives on-farm performance and can assess risks throughout the year.
Why is field stability important at CIBO?
Producers need field-level insight into yield expectations to more accurately predict optimum harvest dates and the inputs that are needed to help increase yield. More critically, stakeholders need to understand what drives yield patterns within a field, and how much yield risk accrues in any given year.
How is field stability calculated?
When properly interpreted, aerial photographs and satellite imagery provide a wealth of information. CIBO has invested in technology to download, ingest, and process such data at large scales. We then apply machine learning and artificial intelligence techniques to infer the stability zones within a field. Using these methods, CIBO can provide compelling insights into the stability of fields and differences in crop productivity.
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