How to Become a Net Zero Company
Carbon Offsetting for Businesses Explained
How Businesses Can Purchase Carbon Removals
Speak to our Farming Manager
The Kingston Wollastonite Rebate 2026
UNDO Farmers Program in Canada
How Silicon Boosts Crop Health
All Resources
Farmer & Landowner FAQs
Our Science
Our Technology
Our Partners
Climate Glossary
Downloads
Podcasts
In the Media
" />
Every farmer in Ontario knows that no two sections of a field are exactly alike. Managing those subtle differences is a big part of the daily work, and finding the right balance to help every row perform its best is key to a successful season.
While traditional crop scouting remains the backbone of good management, remote sensing tools such as the Normalized Difference Vegetation Index (NDVI) are increasingly being explored as an additional source of field insight. At UNDO, we are investigating the use of satellite data as part of a 2026 pilot project to support monitoring of on-farm trials. By using high-resolution imagery to monitor our Split Field Monitoring Sites (SFMS), we can observe patterns in crop canopy development across large areas without adding significant operational costs.
Rather than viewing satellite imagery as proof of yield or treatment effects, we treat NDVI as a complementary monitoring tool. It allows us to identify subtle physiological changes in the crop canopy, such as emerging stress patterns or drainage inconsistencies, often before they are detectable by the human eye. By highlighting differences in canopy development across a field, this technology helps guide where further field investigation may be most useful within our pilot program. It also helps prioritize where deeper, in-person investigations, such as tissue analysis or soil testing, will yield the most valuable insights for both our team and our farming partners.
Understanding What NDVI Measures
NDVI is a proxy for crop greenness derived from reflected light. Healthy, active vegetation absorbs most visible red light while reflecting a significant portion of near infrared radiation. By measuring this ratio, satellites can map canopy development and photosynthetic vitality across a field.
For our current analysis in Ontario, we utilize Sentinel-2 satellite data, which offers a horizontal resolution of 10 meters by 10 meters. While images are collected every 3 to 5 days, cloud cover remains a significant factor in the region. After filtering for cloud interference, images in our study area are available on average every 28 days over the growing season.
It is important to note that while NDVI is a useful indicator of canopy greenness, it cannot prove yield outcomes or isolate the cause of variability within a field. Differences observed in satellite imagery may arise from many factors, including soil texture, drainage patterns, crop variety, planting date, or nutrient availability. Instead, it serves as a signal that tells us where to look more closely, with in-person investigations required to determine why certain zones behave differently.
NDVI monitoring at UNDO is currently being explored as part of a 2026 pilot to support internal research and field monitoring. During this period, we are primarily using the data to prioritize internal sampling efforts and identify which research trials are showing the strongest response to wollastonite applications. These early observations can help indicate where further investigation or harvest checks may be most worthwhile. This approach allows us to evaluate site performance throughout the season while improving internal cost efficiency and reducing unnecessary coordination with farming partners during busy periods.
Reducing Noise Through Historical Baselines
A significant challenge in field monitoring is the inherent noise created by soil variability. Factors such as low spots, waterlogging, shifts in soil texture, or compaction zones can easily distort the results of an on-farm trial. NDVI can help highlight consistent high and low performing zones within a field before comparisons are made.
When we conduct our SFMS on-farm trials, we are essentially creating a large-scale check strip by comparing a spread area directly beside an unspread area of the same field.
By accessing historical imagery dating back to 2016, we establish a multi-year baseline for every site. This approach helps us distinguish between persistent soil characteristics and seasonal anomalies. Within our 2026 pilot project, this historical context ensures we are analysing crop response to a management change rather than simply measuring pre-existing soil differences.
To ensure high data integrity, we define our applied and control boundaries using precise records from mapped fields on our internal platform, NEWTON. We then apply a 20-meter internal buffer within these field shapes. This safety distance filters out noise from headlands and ensures the data is not skewed by boundary effects or historically abnormal zones.
By isolating these comparison zones, we aim to reduce some of the environmental noise that can distort field observations. This allows us to examine whether differences between zones persist after wollastonite application, while recognising that multiple environmental factors may still influence crop response.
Drought Resilience in Ontario
Resilience to weather variability is a top priority for local producers, with 65% of Ontario growers expressing concern over drought risk affecting their yields. Survey data suggest this is a much larger motivator for trying new practices than soil degradation alone.
Enhanced rock weathering (ERW) using silicate rock such as wollastonite has the potential to bolster plant health during periods of stress, such as drought. Because NDVI tracks canopy greenness, differences between field zones may sometimes appear in satellite imagery before they are investigated through standard agronomic tests.
During the 2025 growing season, which included significant dry periods, our NDVI analysis focused on identifying signals of resilience during the peak vegetative months of June, July, and August.
By monitoring crop greenness during dry periods, we can observe whether differences between treated and untreated areas emerge, although NDVI alone cannot determine the underlying cause of those differences. Any observed differences in greenness remain exploratory signals that require further field investigation before conclusions about crop performance can be drawn.
Measuring Crop Response Over Time
To maintain high data integrity within our monitoring site design, our NDVI analysis is currently constrained to June, July, and August. This ensures we capture data when crops are in their peak vegetative state while avoiding the noise associated with early-season bare soil or late-season harvest residues.
We identify a detectable improvement by comparing the monthly greenness of the applied area against the unspread control area, while also accounting for how those two sections performed historically. This comparative approach helps us examine whether crop greenness patterns change after spreading compared with historical imagery.
For fields where wollastonite is applied in the fall, we intentionally wait until the following June to begin our analysis. This delay allows sufficient time for the mineral to begin weathering in the soil, ensuring satellite data reflects genuine crop response rather than temporary seasonal variation.
Advanced Monitoring for the 2026 Season
As we look toward scaling for the 2026 season, we are evaluating several advanced analytical and processing tools designed to refine our understanding of crop response. These improvements are intended to help isolate the specific impact of wollastonite application from the many environmental variables present in a typical Ontario field.
Our current roadmap includes exploring the following capabilities:
– Time Series Analysis: We are assessing methods such as BFAST (Breaks for Additive Seasonal and Trend) to help identify specific changepoints in crop health trends following rock application.
– Topographic and Drainage Controls: To improve comparison accuracy, we are exploring the integration of terrain data and tile drainage records. This would help account for how elevation and slope influence a field’s natural susceptibility to drought.
Together, these developments may help improve how satellite data is used to prioritise where additional field measurements are most useful. By focusing resources on sites showing the most dynamic responses, we can validate program benefits for both our team and our farming partners.
Currently, NDVI is primarily used internally for site prioritization, but we are exploring ways to make these satellite insights directly accessible to farmers for field diagnostics and management decisions.
Insights for Farms
NDVI acts as a powerful tool for identifying representative areas of a field for deeper investigation. By guiding sampling toward the most responsive zones, satellite data helps make in-person checks and tissue testing more targeted and efficient.
This approach reduces unnecessary sampling, minimizes disruption during busy periods, and allows our scientific resources to be used more effectively.
Farmers based in Eastern Ontario are now invited to join the 2026 UNDO farmer program. Participants can take part in ongoing field monitoring trials while accessing a range of agronomic co-benefits designed to support long-term soil health.
Joining the program is a straightforward way to enhance your land and slots around your usual operations, with UNDO covering the material and spreading costs. Local support initiatives may also apply, including the wollastonite rebate offered by the City of Kingston for farmers operating within its municipal boundaries.
Explore The UNDO Farmer Program In Ontario
Looking at ways to strengthen your soil and support long-term crop performance? Join a growing network of Canadian farmers using wollastonite to improve soil health, boost yields, and cut costs.
