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The Rapid Carbon Assessment, conducted by the U.S. Department of Agriculture,was implemented in order to obtain a representative sample of soil organiccarbon across the contiguous United States. In conjunction with a statisticalmodel, the dataset allows for mapping of soil carbon prediction across theU.S., however there are two primary challenges to such an effort. First, thereexists a large degree of heterogeneity in the data, whereby both the first andsecond moments of the data generating process seem to vary both spatially andfor different land-use categories. Second, the majority of the sampledlocations do not actually have lab measured values for soil organic carbon.Rather, visible and near-infrared (VNIR) spectra were measured at mostlocations, which act as a proxy to help predict carbon content. Thus, wedevelop a heterogeneous model to analyze this data that allows both the meanand the variance to vary as a function of space as well as land-use category,while incorporating VNIR spectra as covariates. After a cross-validation studythat establishes the effectiveness of the model, we construct a complete map ofsoil organic carbon for the contiguous U.S. along with uncertaintyquantification.

A Heterogeneous Spatial Model for Soil Carbon Mapping of the Contiguous United States Using VNIR Spectra