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Abstract
Monthly images of Normalized Difference Vegetation Index (NDVI) from the moderate resolution imaging spectroradiometer (MODIS) are used to characterize the spatio-temporal variability of vegetation in a large South American wetland (SAW) (located in the Paraná River floodplain) during the period 2000–2009. While these data do not meet the requirements of classical component extraction techniques (CETs) (e.g. principal component analysis (PCA)), they are suitable for the modern method named independent component analysis (ICA). Hence, ICA is used here to extract three statistically independent modes of inter-annual MODIS-NDVI variability that are successfully interpreted as vegetation responses to hydrological changes. One mode isolates the vegetation response to a severe drought associated with La Niña 2007–2008. Another component reflects the expansion (or contraction) of lagoons owing to high (or low) water level of the Paraná River. The remaining mode captures the vegetation decrease caused by the flood related to El Niño 2006–2007. The results presented here for a particular wetland suggest that ICA of NDVI images is a powerful tool for identifying the physical causes of vegetation changes in other large wetlands.
Acknowledgements
The author thanks T. Warner, C. Cassells and two anonymous reviewers for their constructive comments that greatly improved the manuscript. MODIS-NDVI data and helpful suggestions provided by W. Sione and H. del Valle are also acknowledged. Time series of Paraná River water level were provided by the Subsecretaría de Recusos Hídricos, Argentina. The ICA algorithm was provided by the Institute of Informatics and Mathematical Modelling at the Technical University of Denmark, from its website (http://cogsys.imm.dtu.dk/toolbox/). Precipitation data were provided by the World Data Center for Meteorology, Asheville, NC, USA (http://www.ncdc.noaa.gov/oa/wdc/). The time series of MEI was provided by the Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA (http://www.esrl.noaa.gov/psd/enso/). This study was partially funded by ACTIER-FCyT-UADER, Argentina.