A conceptual approach for the impact of the day of observation of image composites on time series generation

To eliminate atmospheric disturbances and sensor malfunctions many remote sensing products are offered in form of composites that combine multiple observations over a defined period. However, selecting specific observations result in varying interval lengths which affect and limit time series analysis techniques. This study provides a conceptual view on the possibilities to use or define specific composite days and its impact on time series. Often the starting or final day of the compositing period is selected, alternatively the middle day may be chosen. These time series are compared to a series that considers the actual day of observation. An experimental exercise employs 16-day MODIS VI composites of 1000m spatial resolution for a 1100×500km region in central Mexico. Statistical measures such as temporal cross-correlation, harmonic analysis, and difference in start, center, and end of season were used to characterize the temporal shift in time series. A shift of approximately seven days with a high variability is introduced when using the starting day of the compositing period, which is mitigated with assuming the middle day. However, only time series that take into account the day of observation can be used for correct estimation of temporal characteristics.