Normalisation of directional effects in 10-day global syntheses derived from VEGETATION/SPOT: II. - validation of an operational method on actual data sets

摘要

Since April 1998, the VEGETATION/SPOT-4 sensor has provided global reflectances on a daily basis. Its large field-of-view makes the observations strongly dependent on the Sun-target-sensor geometry. This paper presents the "BiDirectional Composiring" (BDC) method we designed for the VEGETATION operational line to normalise directional effects in 10-day global syntheses. For each spectral band and each pixel, BDC results every 10 days in one nadir view datum derived from the observations acquired at every orbit pass. BDC is based on two main ideas. Firstly, the length of the time window devoted to Bidirectional Reflectance Distribution Functions (BRDFs) retrieval is conceived as a variable in such a way that a constant number of cloud-free data is always available to fit the BRDF model. Secondly, BRDF retrieval is separated from data normalisation and compositing, which operates only on 10-day windows before the date of syntheses in order to keep the reflectances level of the most recent observations. As a reliable BROF is always available from VEGETATION data, BDC is filly productive at a 10-day step. It allows to use one single method to derive global syntheses, which can be easily adapted for any large field-of-view optical sensor. Using VEGETATION data sets acquired on four regions of the world, we finally compare 10-day syntheses obtained by BDC to the ones derived with two versions of Maximum Value Compositing (MVC) differing by the performance in detection of clouds and aerosols. The seasonal and spatial coherence of reflectances and Normalised Difference Vegetation Index (NDVI) are much larger on BDC than on MVC syntheses, both at a regional and pixel (km{sup}2) scale. Compared to the version of MVC that is presently used in the VEGETATION operational line, BDC smoothes 10-day fluctuations of reflectances and NDVI time series by a factor 2.8 on average.