Using Artificial Neural Networks to Produce High- Resolution Soil Property Maps (2021)
High-resolution maps of soil property are considered as the most important inputs for decision support and policy-making in agriculture, forestry, flood control, and environmental protection. Commonly, soil properties are mainly obtained from field surveys. Field soil surveys are generally time-consuming and expensive, with a limitation of application throughout a large area. As such, high-resolution soil property maps are only available for small areas, very often, being obtained for research purposes. In the chapter, artificial neural network (ANN) models were introduced to produce high-resolution maps of soil property. It was found that ANNs can be used to predict high-resolution soil texture, soil drainage classes, and soil organic content across landscape with reasonable accuracy and low cost. Expanding applications of the ANNs were also presented.