Commodity Crop Verification

Leveraging remote sensing to verify producer reported commodity Crop.

🛰️ How are commodity crops detected ?

Monitor API uses machine learning to identify the crop growing in a field, leveraging satellite imagery and historical data. By analyzing multi-spectral Sentinel-2 satellite data from throughout the season, the model can detect crops and predict the crop type. CropID is trained to predict the crop near the end of the commodity growing season. This means that the model can detect the crop type near harvest even if the crop is still in the ground, or any time after.

Trained on datasets from government reports and farmer-submitted data, the model recognizes distinct reflectance patterns for different crops. Commodity crop type detection is the core of all Monitor practice detection, as tillage and cover crop practices are determined based on the commodity.

Conflict detection summary table

Some programs may choose to verify the type of commodity crop that was planted during the intervention year, in addition to the tillage and cover cropping practice. You may want to consider including a commodity crop check if:

Your program pays farmers for a specific type of commodity
An eligible intervention for your program is diversifying the crop rotation
Your program’s protocol requires it

Producer-reported commodity crop during the program reporting period are compared with Monitor API observed commodity crop. A prioritization framework is applied to categorize conflicts based on their impact, severity, and confidence level.

Farmer practice	Monitor practice	Monitor confidence	Common crop 'confusion' considerations	Conflict priority
Any commodity	Same commodity	<75%	N/A	✅ verified
Winter cereals	Same winter cereal	<75%	Any of: barley, winter wheat, rye, oats, triticale, winter cereals, triticale grain, other_small_grain can be 'verified' here	✅ verified - Low risk, similar crop detected
Spring cereals	Same spring cereal	<75%	Any of: barley, spring wheat, durum wheat, oats, sorghum, millet, rye_spring, sorghum_silage can be 'verified' here	✅ verified - Low risk, similar crop detected
Root vegetables	Same root vegetable	<75%	Any of: potatoes, sugar beets, sweet potato can be 'verified' here	✅ verified - Low risk, similar crop detected
Oilseeds	Same oilseed	<75%	Any of: canola, oilseed can be 'verified' here	✅ verified - Low risk, similar crop detected
Legumes	Same legume	<75%	Any of: dry beans, chickpeas, lentils can be 'verified' here	✅ verified - Low risk, similar crop detected
Any crop	Fallow	<75%		⚠️ Warning -fallow field detected during growing season
Any crop	Any different crop (not covered above)	<75%		❗Conflict
Any commodity	Monitor detected the reported cover crop type (ie winter wheat)	<75%		🏳️ Monitor detected the cover crop, but could not detect the commodity - Alternate verification method required
Any commodity	Any commodity	> 75%		🏳️ Low confidence - Alternate verification method required
Any commodity	No data	N/A		🏳️ No data - Alternate verification method required

*For MRV Customers: Only fields and practices marked with this flagged will be displayed in the program data review dashboard.

For MRV customers: Only MRV fields with signed contracts and complete data collection are analyzed.

Step by Step process to flag conflicts

This section is mostly relevant for API customers, or MRV customers wanting to understand more about Regrow's conflict flagging logic.

1. Align farmer-reported crop(s) with Monitor’s crop determination.

Tips to help align farmer data with Monitor data:

It can be helpful to assign crops to a year. We recommend using the year of the harvest date.

2. Identify fields where Monitor detected the farmer-reported cover crop.

Monitor's CropID model is trained to detect all common commodity crops. This includes crops that can be grown as both a cover crop and a commodity (such as winter wheat and rye). When Monitor can detect the crop type, it will report it as a commodity crop. For example, if Monitor 'sees' winter wheat it will always be reported as a 'main crop' by Monitor even if it was planted as a cover crop. The PDR logic takes this into account.

First, check if the farmer-reported cover crop is the same (or very similar) to what Monitor detected for the commodity crop.
If so, you can consider the cover crop to be verified but should consider an alternative form of verification to confirm the commodity. 🏳️

3. Identify fields where Monitor had low confidence in the crop type determination.

Monitor may not be able to predict the main commodity crop on a field when there is not enough high-quality data available to make a determination (ex: high frequency of cloud cover). This can show up in the Monitor field results in two ways:

Main crop confidence is low. Confidence is reported on a scale of 0-100. Regrow recommends using Monitor’s crop prediction when confidence is 75 or higher.
There is no commodity crop reported for a cultivation cycle. In this case, Monitor will report no data, indicating that there was not enough remote sensing data available to make a determination.

In these cases, you may choose to use an alternative method of practice verification.

4. Flag practices to review

Background on Monitor crop detection:

Monitor crop detection leverages a Machine Learning model to evaluate remote sensing imagery over a field and predict the crop type. There are cases where the Monitor model 'confuses' similar crops. This can happen when for crops that have a similar growing pattern or spectral signature, making them appear similar or the same via remote sensing.

We refer to these as ‘common confusions’ with Monitor’s ML Model, and we don’t typically consider them a conflict. Here’s a general guide of common confusions that don’t indicate conflict.

Winter cereals: winter wheat, barley, oats, and rye are often confused with each other.
- If Monitor reports one of these and the farmer reports a winter cereal, you can consider that verified.
Root vegetables: Potatoes and sugar-beets are often confused, due to their similarities.
- If the farmer reports a root vegetable, and one of these two crops is provided from Monitor, consider the crop verified.

Pro tip: API customers should work with an agronomist to determine if there are other crops in your program that would fit into this category.

Decision tree for flagging practices:

The section below explains how we arrive to the summary table described at the top of the page.

First, identify fields where Monitor and the farmer agree. If the farmer-reported crop matches the Monitor detected crop, the practice can be considered verified.

Pro tip: It can be helpful to review the crop types in your program first to identify potential duplicates, or crops that may have different names, spellings, etc. but represent the same thing (ex: soy vs. soybean vs, soybeans). Additionally, crops that are used for different purposes but are the same crop fall into this category too (ex: corn, sweet corn, corn silage).
Check for 'common confusion'. If the Monitor-detected crop is a 'common confusion' with the farmer reported crop type, the practice can be considered verified.
Check for fallow during the growing season. If Monitor detected fallow on the field we recommend reaching out to the farmer to clarify, or getting additional proof-of-practice. ⚠️
If there is a disagreement between the farmer-reported practice and Monitor:

If the are not similar types of crops, then it’s considered a conflict. If your program includes crop rotation as an intervention practice, you may need to consider an additional method of verification. If you are verifying crop type for non-crediting reasons, you may want to reach out to the farmer to clarify the reported practices. ❌