Knowledge of the soil’s physical and chemical properties in field-scale geographical areas is crucial for farmers and policymakers for agronomic productivity and environmental quality assessment. Proximal sensors can successfully model soil properties for these purposes and offer a way to rapidly acquire data from soil profiles. However, existing data analysis approaches are ill-suited to explore this type of multivariate proximal sensor data over large land areas and in a sizeable three-dimensional volume. Therefore, this work proposes a multifaceted approach with seamless integration of a star pattern for soil sample collection, data acquisition using proximal sensor devices, and an interactive data visualization solution for processing, analyzing, and reporting analysis results. This solution is the result of an interdis- ciplinary project in which data visualizers worked closely with soil scientists and agronomists to develop a tool called iDVS for rapid characterizations of soil profiles over larger geographical areas using proximal sensor technologies.
- Chemical analysis
- X-ray analysis