Envisat-MERIS vegetation decline analysis: Comparison with Terra-MODIS vegetation indices over the lower Amy Darya River Basin (Northern Uzkekistan)

30 July 2014

Land surface dynamics is one of the key drivers for the assessment of global environmental change and remote sensing based methods are the most important tools for its accurate monitoring. Here, the scientists use an Envisat-MERIS full resolution time series for vegetation decline monitoring as an alternative to more commonly used MODIS data using as a case study irrigated croplands located in the lower Amu Darya River Basin in Northern Uzbekistan, Central Asia.

Long-term (2003-2011) medium resolution time series of different vegetation indices (VIs) from MERIS FR (300 m resolution) and Terra-MODIS (250 m resolution) are compared evaluating their utility for detecting vegetation productivity decline in irrigated agro-ecosystems. In particular, Mann-Kendall trend analysis was conducted to detect vegetation trends and examine the capabilities of each sensor using 3 different VIs: Normalized Differenced Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and MERIS-based Terrestrial Chlorophyll Index (MTCI). VIs derived from both sensors were useful in detecting negative vegetation trends. Although all indices identified the same spatial patterns of decreasing vegetation average values of NDVI and SAVI were slightly higher when measured by MERIS than by MODIS.

The results lead scientists to the conclusion that further analyses of the differences between MERIS and MODIS will be necessary to allow an effective fusion of the different datasets for the monitoring of long-term vegetation dynamics. Moreover, the scheduled launch of the Ocean and Land Color Instrument (OLCI) onboard the Sentinel-3 satellites (Sentinel-3A is expected to be launched in mid-2015 and Sentinel-3B will follow about 18 months later) represent on this purpose a great potential and stimulus to go on with investigating MERIS capabilities to help assure data continuity and to encourage the use of OLCI data also for land applications like monitoring of vegetation dynamics over multi-decade time periods.

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