In this letter, a first-order Moderate Resolution Imaging Spectroradiometer time-series simulator, which uses a colored simple harmonic oscillator, is proposed. The simulated data can be used to augment data sets so that data intensive classification and change detection algorithms can be applied without enlarging the available ground truth data sets. The simulator's validity is tested by simulating data sets of natural vegetation and human settlement areas and comparing it with the ground truth data in Gauteng province located in South Africa. The difference found between the real and simulated data sets, which is reported in the experiments, is negligent. The simulated and real-world data sets are compared by using a wide selection of class and pixel metrics. In particular, the average temporal Hellinger distance between the real and simulated data sets is 0.2364 and 0.2269 for the vegetation and settlement classes, respectively, whereas the average parameter Hellinger distance is 0.1835 and 0.2554, respectively.
['T. L. Grobler', 'E. R. Ackermann', 'A. J. van Zyl', 'Jan C. Olivier', 'Waldo Kleynhans', 'Brian P. Salmon']
An Inductive Approach to Simulating Multispectral MODIS Surface Reflectance Time Series