canopycorrection

Canopy correction, sometimes encountered as canopycorrection in datasets or literature, refers to the set of techniques used to adjust measurements and analyses to account for the effect of a plant canopy on signals and fluxes between the atmosphere and the ground. It is applied in remote sensing, micrometeorology, and ecosystem physiology to separate surface properties from canopy-mediated modulation such as shading, scattering, and storage.

In remote sensing, canopy correction aims to retrieve accurate surface reflectance and biophysical variables by accounting for optical interactions within the canopy, including light attenuation, multiple scattering, and leaf angle distribution. Radiative transfer models like PROSAIL or simplified Beer–Lambert schemes are commonly used, often in combination with atmospheric correction, to separate canopy effects from surface signals.

In flux and microclimate studies, canopy correction addresses the distortion of measured variables such as photosynthetically active radiation, soil temperature, and evapotranspiration caused by shading and canopy storage of water and momentum. For eddy covariance studies, corrections may include canopy height, storage terms, and adjustments for realistic stomatal and aerodynamic responses.

Key concepts include the attenuation and redistribution of light within varying canopy structures, the influence of leaf area density, and the role of canopy clumping and leaf angle distribution on signal propagation. Challenges arise from canopy heterogeneity, rapidly changing phenology, and parameterization uncertainties, which can limit correction accuracy when the structure is poorly characterized.

Overall, canopy correction seeks to reduce canopy-induced biases to enable consistent comparisons across space and time, improving estimates of surface properties, energy fluxes, and ecological processes.