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Understanding soil organic carbon (SOC) response to global change has been hindered by an inability to map SOC at horizon scales relevant to coupled hydrologic and biogeochemical processes. Standard SOC measurements rely on homogenized samples taken from distinct depth intervals. Such sampling prevents an examination of fine‐scale SOC distribution within a soil horizon. Visible near‐infrared hyperspectral imaging (HSI) has been applied to intact monoliths and split cores surfaces to overcome this limitation. However, the roughness of these surfaces can influence HSI spectra by scattering reflected light in different directions posing challenges to fine‐scale SOC mapping. Here, we examine the influence of prescribed surface orientation on reflected spectra, develop a method for correcting topographic effects, and calibrate a partial least squares regression (PLSR) model for SOC prediction. Two empirical models that account for surface slope, aspect, and wavelength and two theoretical models that account for the geometry of the spectrometer were compared using 681 homogenized soil samples from across the United States that were packed into sample wells and presented to the spectrometer at 91 orientations. The empirical approach outperformed the more complex geometric models in correcting spectra taken at non‐flat configurations. Topographically corrected spectra reduced bias and error in SOC predicted by PLSR, particularly at slope angles greater than 30°. Our approach clears the way for investigating the spatial distributions of multiple soil properties on rough intact soil samples.

Rooting depth is an ecosystem trait that determines the extent of soil development and carbon (C) and water cycling. Recent hypotheses propose that human‐induced changes to Earth's biogeochemical cycles propagate deeply into Earth's subsurface due to rooting depth changes from agricultural and climate‐induced land cover changes. Yet, the lack of a global‐scale quantification of rooting depth responses to human activity limits knowledge of hydrosphere‐atmosphere‐lithosphere feedbacks in the Anthropocene. Here we use land cover data sets to demonstrate that root depth distributions are changing globally as a consequence of agricultural expansion truncating depths above which 99% of root biomass occurs (D99) by ∼60 cm, and woody encroachment linked to anthropogenic climate change extending D99 in other regions by ∼38 cm. The net result of these two opposing drivers is a global reduction of D99 by 5%, or ∼8 cm, representing a loss of ∼11,600 km³of rooted volume. Projected land cover scenarios in 2100 suggest additional future D99 shallowing of up to 30 cm, generating further losses of rooted volume of ∼43,500 km³, values exceeding root losses experienced to date and suggesting that the pace of root shallowing will quicken in the coming century. Losses of Earth's deepest roots—soil‐forming agents—suggest unanticipated changes in fluxes of water, solutes, and C. Two important messages emerge from our analyses: dynamic, human‐modified root distributions should be incorporated into earth systems models, and a significant gap in deep root research inhibits accurate projections of future root distributions and their biogeochemical consequences.