Abstract
The present study aimed at analyzing the spatio-temporal variability of the Pantanal vegetation cover, the largest tropical wetland in the world. A principal component analysis (PCA) was applied to a complete annual dataset of filtered EVI2 images (based on a 12-year average over the 2001–2012 period). There was about 99 % variance concentration in the first three components, with the respective loading responses and distributions (maximum, minimum and changes in the sign of the eigenvector loadings) matching the most significant seasonal interruptions. The first three principal components showed the essential aspects of the spatio-temporal variability of the local phenology, i.e. the cumulative greenness throughout the year, the later and more generalized senescence associated with the drought season climax, and the early senescence associated with sandy portions. Our results enabled the detection of homologous areas regarding vegetation density and the time and intensity of senescence. As the water availability throughout the year—the most important parameter for regional vegetation—is largely a function of geology (sediment grain size and vertical neotectonic), a geobotanic analysis of the Pantanal wetlands was also possible. Our PCA-based approach was able to capture the essentials of the phenological/environmental variability, with potential for application in other ecosystems with complex vegetation cover and functioning.
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References
Abdon MM, Silva JSV, Pott VJ, Pott A, Silva MP (1998) Utilização de dados analógicos do Landsat-TM na discriminação da vegetação de parte da sub-região da Nhecolândia no Pantanal. Pesq Agropec Bras 33:1799–1813
Allem AC, Valls JFM (1987) Recursos forrageiros nativos do Pantanal Mato-grossense. Empresa Brasileira de Pesquisa Agropecuária, Brasília
Assine ML, Soares PC (2004) Quaternary of the Pantanal, west-central Brazil. Quatern Int 114:23–34
Assine ML, Corradini FA, Pupim FN, McGlue MM (2014) Channel arrangements and depositional styles in the São Lourenço fluvial megafan, Brazilian Pantanal wetland. Sediment Geol 301:172–184
Byrne GF, Crappe PF, Mayo KK (1980) Monitoring land-cover change by principal component analysis of multitemporal Landsat data. Rem Sens Environ 10:175–184
Collischonn B, Allasia D, Collischonn W, Tucci CEM (2011) Desempenho do satélite TRMM na estimativa de precipitação sobre a bacia do Paraguai superior. Rev Bras Cart 59:93–99
Conservation International (2009) Monitoring alterations in vegetation cover and land use in the upper Paraguay river basin, Brazilian portion. Conservation International, Brasília
Corradini FA, Assine ML (2012) Compartimentação geomorfológica e processos deposicionais no megaleque fluvial do rio São Lourenço, Pantanal mato-grossense. Rev Bras Geocienc 42:20–33
Eastman JR, Fulk M (1993) Long sequence time series evaluation using standardized principal components. Photogramm Eng Rem S 59:991–996
Eklundh L, Jönsson P, Kuusk A (2007) Investigating modelled and observed Terra/MODIS 500-m reflectance data for viewing and illumination effects. Adv Space Res 39:119–124
Ferreira LG, Huete AR (2004) Assessing the seasonal dynamics of the Brazilian Cerrado vegetation through the use of spectral vegetation indices. Int J Rem Sens 25:1837–1860
Garcia EAC (1984) O clima no Pantanal Mato-Grossense. EMBRAPA, Corumbá
Hall-Beyer M (2003) Comparison of single-year and multiyear NDVI time series principal components in cold temperate biomes. IEEE Trans Geosci Rem Sens 41:2568–2574
Hamilton SK, Sippel SJ, Melack JM (1996) Inundation patterns in the Pantanal wetland of South America determined from passive microwave remote sensing. Arch Hydrobiol 137:1–23
Hamilton SK, Sippel SJ, Melack JM (2002) Comparison of inundation patterns among major South American floodplains. J Geophys Res Atmos 107:5–14
Hirosawa Y, Marsh SE, Kliman DH (1996) Application of standardized principal component analysis to land-cover characterization using multitemporal AVHRR data. Rem Sens Environ 58:267–281
Huete AR, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Rem Sens Environ 83:195–213
Jiang Z, Huete AR, Didan K, Miura T (2008) Development of a two-band enhanced vegetation index without a blue band. Rem Sens Environ 112:3833–3845
Jönsson P, Eklund L (2004) TIMESAT—a program for analyzing time-series of satellite sensor data. Comput Geosci 30:833–845
Junk WJ, Brown M, Campbell IC, Finlayson M, Gopal B, Ramberg L, Warner BG (2006) The comparative biodiversity of seven globally important wetlands: a synthesis. Aquat Sci 68:400–414
Litherland M, Bloomfield K (1981) The proterozoic history of eastern Bolivia. Prec Res 15:157–179
Padovani CR (2010) Dinâmica espaço-temporal das inundações do Pantanal. Dissertation, University of São Paulo
Pearson K (1901) On lines and planes of closest fit to systems of points in space. Lond Edinb Dublin Philos Mag J Sci 2:559–572
Penatti NC, Almeida TIR (2012) Subdivision of Pantanal quaternary wetlands: MODIS NDVI timeseries in the indirect detection of sediments granulometry. ISPRS Int Arch Photogramm Rem Sens Spatial Inf Sci 1:311–316
Pott A (1982) Pastagens das sub-regiões dos Paiaguás e da Nhecolândia do Pantanal Mato-Grossense. EMBRAPA, Rio de Janeiro
Silva JSV, Abdon MM (1998) Delimitação do Pantanal brasileiro e suas sub-regiões. Pesq Agropec Bras 33:1703–1711
Silva MD, Mauro R, Mourão G, Coutinho M (2000) Distribuição e quantificação de classes de vegetação do Pantanal através de levantamento aéreo. Rev Bras Bot 23:143–152
Small C (2012) Spatiotemporal dimensionality and time-space characterization of multitemporal imagery. Rem Sens Environ 124:793–809
Solano R, Didan K, Jacobson A, Huete AR (2010) MODIS vegetation index user’s guide (MOD13 series), Version 2.0, May 2010 (Collection 5). Available online http://vip.arizona.edu/documents/MODIS/MODIS_VI_UsersGuide_01_2012.pdf
Townshend JR, Goff TE, Tucker CJ (1985) Multitemporal dimensionality of images of normalized difference vegetation index at continental scales. IEEE Trans Geosci Rem Sens 23:888–895
Ussami N, Shiraiwa S, Dominguez JML (1999) Basement reactivation in a sub-Andean foreland flexural bulge: the Pantanal wetland, SW Brazil. Tectonics 18:25–39
van Leeuwen WJ, Huete AR, Laing TW (1999) MODIS vegetation index compositing approach: a prototype with AVHRR data. Rem Sens Environ 69:264–280
Acknowledgments
The authors thank the Foundation for Research Support in the State of São Paulo (FAPESP) for research funding (process 2010/52614-4). Laerte Guimarães Ferreira and Teodoro Isnard Ribeiro de Almeida thank CNPq for individual research Grants. Arielle Arantes, Cibele Hummel do Amaral, and Natasha Costa Penatti are grateful, to CNPq, FAPESP, and CAPES for their graduate student scholarships, respectively.
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de Almeida, T.I.R., Penatti, N.C., Ferreira, L.G. et al. Principal component analysis applied to a time series of MODIS images: the spatio-temporal variability of the Pantanal wetland, Brazil. Wetlands Ecol Manage 23, 737–748 (2015). https://doi.org/10.1007/s11273-015-9416-4
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DOI: https://doi.org/10.1007/s11273-015-9416-4