Scoring the Land
We are on a mission to “decode” the landscape by leveraging our unique technology platform to generate simple scores that can be used to efficiently evaluate and compare parcels of land.
We use expert data science, robust modeling, and a little common sense to come up with our best estimate of an agricultural parcel’s fair market value.
Decoding a parcel’s history is critical to understanding its agronomic potential and economic value. Unfortunately, a general lack of transparency into a parcel’s past performance, management history, and resource requirements prevents buyers & sellers, lenders & brokers, and owners & operators from determining the fair market value of a piece of land.
CiBO is working to bring transparency and efficiency to the way land is valued. Our parcel Valuations attempt to capture the true economic value of land, independent of hard to come by operator data. We utilize objective and transparent methodologies that incorporate factors such as productivity potential and local economic conditions to determine the fair dollar value of a parcel.
CiBO Productivity Score
We simulate the day-to-day growth of a crop to estimate past yields and assess overall productivity of a parcel, independent of a farmer’s data.
Deciphering the history and potential of a parcel is critical to understanding its inherent productivity and ultimate economic value. Unfortunately, this type of information is typically not available outside of hard to come by operator data. Without access to this data, those interested in valuing a parcel are typically limited to public soil maps and state-level productivity rankings, which are inadequate for representing actual field conditions.
CiBO understands that the agronomic potential of a parcel is dependent on more than just a soil map. Using remote sensing, artificial intelligence, crop growth simulation, and a little old fashioned farm knowledge, we infer how the land was managed and what it could have yielded over the past 10 growing seasons. This information is distilled into a single Productivity Score that is specific to each parcel.
CiBO Field Reliability Score
We break a parcel into performance zones to better understand which areas of a field perform consistently, year-over-year.
Not all farm fields behave the same, and an individual parcel’s unique in-field behavior is hard to predict without significant operator experience and data. Reliable data used to explain in-field behavior, such as combine yield and precision maps, are not typically publicly available, preventing operators and owners from easily onboarding new parcels.
CiBO’s Field Reliability Score and zone map work to clearly communicate and visualize field level variability. We use satellite imagery, machine learning, and artificial intelligence to assess the performance within an individual parcel year-over-year. Looking back over a 10-year period, we map out high-to-low performing zones as well as those areas in a field where performance varies significantly year-to-year, depending on seasonal conditions.
CiBO Sustainability Score
By modeling the complex interactions of crops, soil, weather, and management we can measure the environmental impact of farming an individual parcel.
Farming the landscape requires time, energy, and inputs — like nitrogen fertilizer. Complex interactions between the land, the weather, and the way a crop is managed determine the required inputs to maximize crop yield and the impact those inputs have on the environment. Understanding the overall sustainability of a farm requires a deep understanding of the land itself, as well as how it has been managed over time.
Recognizing that some fields require greater inputs to sustain yields than others, CiBO uses our proprietary technology platform to model the day to day growth of a crop on a particular parcel, together with the nutrients required to sustain it. This allows us to calculate not only the likely yield but also the amount of nitrogen leached into groundwater and the quantity of greenhouse gasses emitted in the production process. We do this uniquely for each field, taking into account local soil and weather conditions and likely management practices.