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Proceedings Paper

The impact of the day of observation of image composites on adequate time series generation
Author(s): Rene R. Colditz; Rainer A. Ressl
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Paper Abstract

Many remote sensing products that are useful for time series analysis and seasonal monitoring studies are offered in form of composites. A composite combines a number of observations of a defined period and selects or computes one value. This results in observations sampled at varying time intervals that rules out a high number of time series analysis techniques. This study investigates the impact of either using the actual day of observation to generate a time series from composites or assuming the starting or middle day of the compositing period. For this study 16-day MODIS VI composites of 1km spatial resolution from Terra and Aqua were employed. A 1100x500km region in central Mexico served as study site. Statistical measures including temporal cross-correlation and the root mean square error were used for time series analysis. A temporal shift of approximately seven days with a high variability is introduced when using the starting day of the compositing period. The middle day mitigates the mean error close to zero but still shows a high error variability. Only time series that take into account the day of observation and estimate from that samples at equidistant intervals can be used for a correct estimation of temporal characteristics.

Paper Details

Date Published: 24 October 2013
PDF: 6 pages
Proc. SPIE 8893, Earth Resources and Environmental Remote Sensing/GIS Applications IV, 88930Y (24 October 2013); doi: 10.1117/12.2029498
Show Author Affiliations
Rene R. Colditz, CONABIO (Mexico)
Rainer A. Ressl, CONABIO (Mexico)


Published in SPIE Proceedings Vol. 8893:
Earth Resources and Environmental Remote Sensing/GIS Applications IV
Ulrich Michel; Daniel L. Civco; Karsten Schulz; Manfred Ehlers; Konstantinos G. Nikolakopoulos, Editor(s)

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