Using Artificial Neural Networks to Produce High- Resolution Soil Property Maps
Meng, Fan Rui
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Summary in foreign language
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.
Link to resourcehttps://www.intechopen.com/books/advanced-applications-for-artificial-neural-networks/using-artificial-neural-networks-to-produce-high-resolution-soil-property-maps
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