Time series of vegetation indices like NDVI are used in numerous applications
ranging from ecology to climatology and agriculture. Often, these time series have
to be filtered before application. The smoothing removes noise introduced by
undetected clouds and poor atmospheric conditions. Ground reference measurements
are usually difficult to obtain due to the medium/coarse resolution of the
imagery. Hence, new filter algorithms are typically only (visually) assessed against
the existing smoother. The present work aims to propose a range of quality
indicators that could be useful to qualify filter performance in the absence of
ground-based reference measurements. The indicators comprise (i) plausibility
checks, (ii) distance metrics and (iii) geostatistical measures derived from variogram
analysis. The quality measures can be readily derived from any imagery. For
illustration, a large SPOT VGT dataset (1999–2008) covering South America at
1 km spatial resolution was filtered using the Whittaker smoother.
ATZBERGER Clement;
EILERS Paul;
2011-09-07
TAYLOR & FRANCIS LTD
JRC65749
0143-1161,
https://publications.jrc.ec.europa.eu/repository/handle/JRC65749,
10.1080/01431161003762405,
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