Land health surveillance is a methodological framework for measuring and monitoring land health—the capacity of land to sustain delivery of ecosystem services—for the purpose of targeting agroforestry and other sustainable land management in landscapes, and assessing their impacts. It is modelled on scientific principles used in surveillance in the public health sector, which has a long history of evidence-informed policy and practice. Key elements of the science methodological framework are (1) probability-based sampling of well-defined populations of sample units; (2) standar dized protocols for data collection to enable statistical analysis of patterns, trends, and associations; and (3) multilevel statistical modelling of land health attributes at different scales, including in relation to satellite imagery for spatial interpolation. The framework was applied in assessing soil carbon in Kenyan rangelands in Laikipia. Systematic probability-based field sampling provided a robust baseline on condition in the study area. Infrared spectroscopy was used in the laboratory as a rapid low-cost tool for estimating soil carbon concentration. The georeferenced soil carbon values were modelled to reflectance values of fine resolution (2 m) satellite imagery and spatially interpolated over the 100-km2 sampling block. The combination of methods makes soil carbon baselines feasible at a landscape level in land management projects and provides much additional information on soil and vegetation health for targeting interventions. The land health surveillance approach could form the basis for evidence-based decision making on land management at project, national, and even continental levels.
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