Data Processing

When you fly over a crop using UAV imagery, you can collect hundreds of photos that cover the entire field. These images are not useful on their own, so part of data processing is to stitch all these images together. There is software readily available and user-friendly that can do this. One common software is Pix4D. To create a mosaic from your images, you just need to upload them to the software and change the settings to your preference. This is where the GCP coordinates are used to correct any distortions.

 Every one of these images you create is actually a matrix containing information. If you zoom in on any point within the matrix, the value of that pixel is an element in an array. The final processed image from an RGB sensor is 3 – 2D arrays laid on each other to create a matrix. Each array contains a number that corresponds with the reflectance in that wavelength. For example, in the red array, each pixel contains the value of the red reflectance within that pixel. In the green array, each pixel contains the value of the green reflectance within the area of that pixel. In the blue array, each pixel is assigned the value of the blue reflectance within the area of that pixel. Similarly, an image from the multispectral sensor is 5 - 2D arrays laid on each other to create a matrix. Each array containing the values for the NIR and red-edge reflectance in addition to the RGB reflectance values. This is how the images can be used to extract objective information rather than subjective information.

The RGB file that is created from stitching all the continuous images together can be used to create a shapefile using a polygon grid. A polygon grid is just a grid that divides a file into cells based on the coordinate system. This polygon grid will allow us to systematically ‘clip’ the NDVI raster file to extract NDVI for each individual plot. There are many accessible software programs for users interested in creating a shapefile. Two commonly used programs to do this are ArcGIS and QGIS. The main difference between the two is that ArcGIS is proprietary software whereas QGIS is an open-source software. Every software has benefits and detriments, so it is up to the user to determine which is the best fit for their analysis.

One of the biggest areas of interest when using a multispectral sensor is the ability to calculate vegetation indices. Calculating these indices is quite simple once you have mastered the technical skills needed to extract the data from images. We can calculate the vegetation indices for the entire field using software called ArcGIS. There are a series of steps to go through to process the initial image and calculate a vegetation index.

The processed image will be saved as a raster file which allows us to extract information. The way a raster file works is that it is a matrix of pixels. If you zoom in enough on a small section of a selected plot, you will end up with a bunch of pixels. Every pixel is going to have its own value. To extract the vegetation index for an entire plot, we use the shapefile with a polygon grid created earlier. The shapefile will clip the vegetation index raster file into individual plots. The average vegetation index then is calculated using every pixel within the area of a specific plot.

Some common indices calculated include the Normalized Difference Vegetative Index (NDVI), Normalized Difference Red Edge (NDRE), and the Green Normalized Difference Vegetative Index (GNDVI).

All three of these indices will fall between a range of -1 to +1. Think back to when we discussed the plant structures wavelengths reflect off. In the visible spectrum, green wavelengths are going to reflect off the plant, causing the vegetation to look green. Red and blue wavelengths of light are used to drive photosynthesis. This provides plants with food to grow, and aids in chlorophyll production. NIR bands are also reflected by the chlorophyll in the plant. When calculating the vegetation indices for a healthy plant, there is going to be high chlorophyll production resulting in a higher amount of light reflectance. This provides vegetative index close to +1. If a plant is not healthy or experiencing stress, there is going to be less chlorophyll production which in turn lowers the amount of light reflectance. This would give a vegetative index close to 0. Extracting the vegetation index for individual plots provides the plant breeder with the information they need to make decisions.