Data Analysis

Flying a field and collecting data is only one small part in implementing HTP into a breeding program. There are many environmental factors that can affect the quality of images captured by sensors: row angle, sun angle, time of day, consistency over time, etc. Due to these factors, data collected will need to go through a series of data processing steps to remove any inconsistencies before it is useful to a breeder.

One type of information we can extract from sensor data is spectral information. Spectral information is the wavelengths of light measured and the corresponding data they provide. Say, for example, we are gathering information about a cat. We want to identify the animal as a cat, perhaps as a specific breed of cat, and eventually identify it as a specific cat. The spectral information would tell us things like the color of the eyes or color of the hair. Arrangement of color on the body. Sensors can also extract structural information to provide size, proportions of the body, legs and head and hair length. Plant breeders will focus on the spectral information from sensors and supplement it with structural information to gather the best data that reveals the phenotype of the plant at the time of the measurement. Structural information is often used to supplement the vegetation indices. Alone, each type of information is useful, but together we can put together a full picture of the health status of a plant.

There are three main steps that make up processing of the raw data that the UAV collects from sensors in a specific flight: Stitch the images, create a shapefile, extract indices.

Figure 16. The three Data Processing steps. The order of those steps is to stitch images, create shapefile, and extract indices.

Created by C. Mick using Microsoft PowerPoint, 2022.