A New Method to Calculate Soil Water Content by Imaging and Testing the Color of the Soil Surface

Abstract

Soil color changes with water content due to chemical and physical reactions, making it a potential indicator for moisture estimation. By analyzing soil surface images and comparing color variations against laboratory-measured water content, a rapid and cost-effective method for moisture determination can be developed. Traditional moisture measurement techniques are time-consuming, so an imaging-based approach would be highly beneficial for quick decision-making. Soil color is also influenced by factors such as particle coarseness, which creates shadows and alters perceived darkness. This research introduces a novel method to isolate true soil color by analyzing the maximum color response in image pixels, minimizing shadow effects. Several equations were derived to correlate color changes with moisture content and were validated against lab measurements to ensure accuracy and simplicity. The most effective equation can be further adapted for satellite imagery by accounting for atmospheric light scattering differences between ground and satellite sensors, enabling large-scale moisture monitoring. The derived equations can be programmed into a software tool, allowing moisture estimation from simple soil surface images. The study involved controlled experiments where soil samples at varying moisture levels were imaged to establish an empirical color-moisture relationship. This method provides a fast, economical, and practical alternative to conventional techniques. However, the approach requires further refinement to account for different soil types globally. Future work should focus on adjusting the model with variables that adapt the color-moisture relationship for diverse soils, ensuring broader applicability. Once optimized, this could significantly improve moisture assessment in agriculture, environmental monitoring, and land management.