Soil moisture dynamics estimated from MODIS time series images

Abstract

The annual cyclic phenomena of soil surface wetness influences for instance vegetation growth, drought, flooding, and soil properties. This study presents an attempt to define metrics relevant for capturing the soil moisture dynamics from an annual series of wetness estimates derived from global Moderateresolution imaging spectroradiometer (MODIS) images. Different algorithms for both smoothing and gap-filling the time series are tested with the results compared to in-situ data. Neither the smoothing nor the gap-filling improve the capturing of the surface wetness phenology compared to using unsmoothed time series data. The smoothing, however removes the effects of erratic rainfall events and noise, and the smoothed time series was considered more robust for identification of wetness phenology. Metrics capturing the global surface wetness phenology for 2011, extracted after smoothing using a simplified locally weighted scatterplot smoothing (LOWESS) model, are presented at a spatial resolution of 500m for the calendar year 2011.