ADAPTIVE RECONSTRUCTION OF NDVI TIME SERIES WITH MULTI-PERIODIC HARMONIC MODEL

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. A multiple harmonic model is used to adaptively reconstruct remotely-sensed image series which have missing observation or noises resulted from mechanical problems or environmental conditions. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.