Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter

Satellite-derived vegetation indices and their resulting surface parameters, such as the leaf area index (LAI), are inevitably affected by the atmosphere. Errors in the atmospheric corrections can often be easily identified in a seasonal trajectory of a surface parameter because the atmospheric effect generally causes erratic reductions in vegetation indices. A locally adjusted cubic-spline capping (LACC) method is developed here to screen affected data points in a pixel and to replace them through temporal interpolation. In LACC, a variable local smoothing parameter, which controls the local smoothness of the fitted curve, is automatically determined according to the local curvature of the original seasonal variation pattern. An iteration procedure is designed to produce a seasonal capping curve by progressively replacing abnormally low values with fitted values. This method has two advantages over existing methods based on harmonics, namely: 1) cubic splines are flexible for simulating a wide range of seasonal variation patterns and 2) a variable local smoothing parameter allows the fitted capping curve to mimic either rapid or slow variation patterns in various seasons. The capping curve is also mathematically differentiable for further applications. The effectiveness of this method is demonstrated through case studies for several cover types in China and processing a series of Moderate Resolution Imaging Spectroradiometer LAI images of China in 2001.