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The foundation of global food production is soil, which also serves as a habitat, regulates the hydrological cycle, and mitigates climate change through carbon sequestration. However, precision agriculture, soil mapping, contamination monitoring, and documentation of soil C sequestration all require a high spatial and temporal density of soil information due to the heterogeneous and dynamic nature of soils. In this context, sensors that make use of various parts of the electromagnetic spectrum offer a quicker, less expensive and nondestructive alternative to conventional laboratory procedures. Models can be used to predict a variety of soil properties after they have been calibrated with paired reference data and spectral measurements. However, the prediction mechanisms for the soil property of interest determine the accuracy of the resulting model.
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