Any agronomist who works with UAS in small plot outdoor field trials considers it an accomplishment to:
Capture sharp, well-exposed images with ample overlap
Stitch the images into an orthomosaic
Adjust the orthomosaic to align with the research site layout, including any offsets caused by planter errors, etc.
Having managed these tasks, the rest of the data are left on the proverbial cutting room floor. That is, most of the image data is sacrificed to generate a single orthoimage. But what is lost?
It turns out not every overlapping plot image is the same. Small changes in perspective (position of the UAV relative to the plot's dead center) and exposure differences between frames can cause differences in the final measurements of canopy cover, color, and vegetation indices such as NDVI. So while it may seem like efficiency is gained by discarding overlapping image information, there is actually a loss incurred -- not to mention the technical challenge of achieving adequate orthorectification (geometric correction).
Phenix Generates & Analyzes Multiple Images of Every Plot
Phenix is the only application which generates multiple images of every plot, taken from different camera perspectives during UAV flight. We call these Plot Clips™. And rather than analyze a single orthoimage assumed to represent the entire experiment, we instead analyze the Clips, plot-by-plot. Furthermore, a Phenix algorithm scans the individual Clips for quality, generating sample statistics and even suggests which Plot Clip is closest to nadir (directly over the plot). This process ensures that Phenix outputs are derived from the optimal images.
In an upcoming article I will discuss additional uses of Plot Clips that will be added to Phenix. For more about how to capture UAS images of optimal quality for data extraction please see our webinar or contact us directly, and be on the lookout for our 'Getting Started with Drones in Small Plot Field Trials' guide.
image: Plot Clip™ series consisting of 14 separate images from a corn field trial (courtesy of the Genomes To Fields Initiative)