Presia’s Canopy Model

Presia’s Canopy Model

Presia’s Canopy Model, developed through extensive research and collaboration with industry leaders, is transforming potato crop management. Unlike traditional methods based on guesswork and manual assessment, the Canopy Model provides a precise, reliable way to monitor potato crop performance automatically and at scale, already proven effective on over one million acres.
 

Article Highlights

Challenges in Potato Crop Monitoring: 

  • Traditional methods are labor-intensive and often unreliable due to reliance on manual assessments and estimations
  • Standard remote sensing measures like fCover and NDVI are not effective for potato-specific assessments

Advantages of the Canopy Model:

  • Tailored specifically for potato crops
  • Utilizes multiple spectral bands, optical satellite imagery, and SAR satellite data
  • Continuously adapts to new sensors, varieties, regions and historical data

Benefits of Remote Canopy Monitoring for Potato Suppliers:

  • Enables proactive management by identifying problem areas early
  • Ensures accuracy of field assessments by pinpointing optimal sampling locations
  • Tracks canopy decline to optimize harvest scheduling

Benefits of Remote Canopy Monitoring for Potato Processors:

  • Predicts supply variability to allow timely adjustments in raw material allocation
  • Helps mitigate supply chain disruptions

Proven Impact: Effective on over one million acres across growing regions and potato varieties

What is the Canopy Model?

Monitoring potato crop health is challenging because potatoes grow underground. Traditional methods involve agronomists manually scouting fields and assessing tubers, which is time-consuming and often unreliable due to its dependence on estimations and sampling non-representative areas of fields. Remote sensing technologies, like satellite-based analytics, offer scalable and objective field data. However, generic measures like fCover and NDVI fall short for potato-specific assessments.

To address this, Presia developed the Canopy Model, specifically designed to model the development of a potato crop’s canopy. It quantifies ground coverage as a percentage, providing an intuitive scoring system for field comparisons. Alternative measures such as NDVI,  which reports values between -1 and 1, are difficult to understand in the context of real-world conditions . Over the past decade, Presia has built the most comprehensive potato-specific dataset to develop, test, and validate the Canopy Model across regions and potato varieties.

The model integrates multiple spectral bands, optical satellite imagery, and SAR satellite data to reduce cloud coverage impact. Our model is trained with leading and emerging sensors, as well as variety- and region-specific data, allowing it to continuously adapt to new technologies, environments and client needs.

The graph above shows the development of a single potato crop variety across multiple fields, normalized to Days After Emergence (DAE). Day 0 marks the first emergence of the crop in each field. This allows operators to easily identify underperforming fields needing attention, such as fields 19 and 23, and those performing well, such as fields 15, 16 and 22. By comparing the same variety across different regions, operators are able to better plan for future seasons based on varietal performance across regions. 

How Can the Canopy Model Improve Decision Making?

The Canopy Model enhances decision-making by offering objective data throughout critical growth stages. For potato suppliers, it enables proactive management by identifying problem areas early, ensuring timely interventions to prevent yield losses. It also pinpoints representative sampling locations for precise assessments and tracks canopy decline to optimize harvest scheduling.

For potato processors, the model provides a comprehensive understanding of their supply, comparing crop performance across various parameters including variety, growing region, and historical data. This data-driven approach helps predict supply variability, allowing timely adjustments in raw material allocation to meet manufacturing demands and mitigate supply chain disruptions.

Presia’s Canopy Model is a game-changer in potato crop management. By providing precise, reliable crop performance data, it supports better decision-making and operational efficiency. If you’re interested in learning how Canopy data can impact your operation, contact sales@presia.ca.