A Novel Python Program to Automate Soil Colour Analysis and Interpret Surface Moisture Content

Most of the previous researchers used manual image processing approach through a public domain tool (ImageJ) to interpret soil surface moisture content. However, the manual processing could not be possible, when the number of images is significantly large. In addition, results could not be reproduced with conventional manual image processing. This technical note introduces a novel technique to automate the quantification process of soil surface moisture content. A stepwise strategy was demonstrated to remove user dependency for soil colour analysis using an autonomous Python script. The images of the compacted soil were captured using a commercially available camera model. The image analysis was conducted using conventional manual image processing approach and newly developed technique. The difference between the mean gray values obtained from the above mentioned two approaches was very low (< 3%). Hence, the newly developed technique is cost-effective and feasible for programming with drones to monitor soil surface moisture content in large areas.