Use Cases and Applications

Designed specifically for UAV and vegetation mapping

• Plant Counting : Plant counting algorithms require high-resolution imagery. RedEdge-P combines a Panchromatic lens with 5-high-res multispectral lenses enabling high-res RGB and multispectral outputs, allowing plant count even at early growth stages.

• Phenotyping : Manually measuring plant characteristics is time-consuming. RedEdge-P band combination enables high-resolution multispectral outputs, allowing the detection of variability at the leaf level.
• Plant health mapping : RedEdge-P’s high-resolution multispectral outputs allow the generation of indices and composites to see individual chlorophyll levels in the plants and compare over time.
• Fertilizer management : RedEdge-P’s high-res and accurate outputs allow easy identification of areas low in nutrients and help monitor the effects of fertilizer applications throughout the season and determine if, when, and where a new application is needed.
• Disease identification : RedEdge-P captures a critical part of the light spectrum for studying plants (712–722 nm), called the red edge band. It is in this section of the spectrum that the first signs of stress start to show. Using analytics generated with the red edge band, it is possible to identify disease sooner and act faster to stop the spread.
• Species differentiation : Some differences among species may not be visible to the naked eye. High-res multispectral data allows for species differentiation, weeds included, by highlighting characteristics such as chlorophyll content, vigor, and leaf size.
• Advanced crop scouting : High-res multispectral and RGB imagery provides advanced field scouting capabilities. In one flight, it is possible to collect accurate and geotagged information of a problem, making it easy to assess the situation and determine the appropriate intervention.
• High-res 3D point clouds : RedEdge-P’s 5.1 megapixel panchromatic band provides over twice the ground resolution of the industry-standard RedEdge-MX, resulting in 3D point clouds with up to 4 times the point density.