FIELDimageR | R package to analyze orthomosaic images

FIELDimageR is a R library. FIELDimageR has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Taking the first step:. It is necessary to first reduce the image/mosaic size around the field boundaries for faster image analysis. Function to use: fieldCrop. The following example uses an image available to download here: EX1_RGB.tif. To build the plot shape file first we need to make sure that the image base line (dashed in red) has a correct straight position (vertical or horizontal). If not, it is necessary to find the right-angle theta to rotate the field, fieldRotate allows you to click directly on the image and select two points on where you want to base your field and return the theta value to finally rotate the image. The presence of soil can introduce bias in the data extracted from the image. Therefore, removing soil from the image is one of the most important steps for image analysis in agricultural science. Function to use: fieldMask. Once the field has reached a correct straight position, the plot shape file can be drawn by selecting at least four points at the corners of the experiment. The number of columns and rows must be informed. At this point the experimental borders can be eliminated, in the example bellow the borders were removed in all the sides. Function to use: fieldShape. Attention: The plots are identified in ascending order from left to right and top to bottom being evenly spaced and distributed inside the selected area independent of alleys. One matrix can be used to identify the plots position according to the image above. The function fieldMap can be used to specify the plot ID automatic or any other matrix (manually built) also can be used. For instance, the new column PlotName will be the new identification. You can download an external table example here: DataTable.csv. Important: Code showing how to make ShapeFile using original GIS.