Full text: Technical Commission VIII (B8)

a previous knowledge of the region to be studied is 
indispensable and that auxiliary methods should be used, such 
the MODIS triplets and fieldwork samples 
The good results do not eliminate the perspective to test the 
model with other spectral indices than NDVI in the remote 
assessment of sediments granulometry. Likewise, it would be 
interesting to test the method for different geographic regions 
with similar environmental characteristics, as well as other 
scales and images at Pantanal. 
6. REFERENCES 
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Moreira, M.A., 2008. Estudo da dinämica espaco-temporal do 
bioma Pantanal por meio de imagens MODIS. Pesquisa 
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Adämoli, J., 1981. O Pantanal e suas relaçôes fitogeogräficas 
com os cerrados. Discussäo sobre o conceito de “Complexo do 
Pantanal.” Anais do XXXII Congresso Nacional de Botânica. 
Sociedade Brasileira de Botánica, Teresina, Brasil, pp. 109- 
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Alho, C.J., Lacher, T.E., Gonçalves, H.C., 1988. Environmental 
degradation in the Pantanal ecosystem. Bioscience, 38, pp. 164- 
171. 
Assine, M.L., Soares, P.C. 2004. Quaternary of the Panatanal, 
west-central Brazil. Quaternary International, 114: 23-24. 
Assumpcáo, M., 1998. Focal mechanisms of small earthquakes 
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high biomass ecosystems, Remote Sensing of Environment., 
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Camargo, O.A., Moniz, A.C., Jorge, J.A., Valadares, J.M.A.S., 
2009. Métodos de análise química e fisica de solos do Instituto 
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Eklundh, L., Jônsson, P., 2011, Timesat 3.1 Software Manual, 
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Eklundh, L., Jónsson, P., Kuusk, A., 2007. Investigating 
modelled and observed Terra/ MODIS 500-m reflectance data 
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Gu, Y.X., Hunt, E., Wardlow, B., Basara, J.B., Brown, J.F., 
Verdin, J.P., 2008. Evaluation of MODIS NDVI and NDWI for 
vegetation drought monitoring using Oklahoma Mesonet soil 
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Jensen, J.R., 2009. Sensoriamento Remoto do Ambiente: Uma 
perspectiva em Recursos Terrestre. Säo José dos Campos: 
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Ji, L., Peters, A.J., 2003. Assessing vegetation response to 
drought in the northern Great Plains using vegetation and 
drought indices. Remote Sensing of Environment, 87, pp. 85-98. 
Jónsson, P., Eklundh, L., 2002, Seasonality extraction and noise 
removal by function fitting to time-series of satellite sensor 
data, IEEE Transactions of Geoscience and Remote Sensing, 
40, pp. 1824-1832. 
Jonsson, P., Eklundh, L., 2004. TIMESAT - a program for 
analysing time-series of satellite sensor data, Computers and 
Geosciences 30, pp. 833-845. 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
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analysing time-series of satellite sensor data, Computers and 
Geosciences, 30, pp. 833-845. 
Kogan, F.N., 1998. Global drought and flood-watch from 
NOAA polar-orbiting satellites. Advances in Space Research, 
21(3), pp. 477-480. 
Lourival R., Drechsler M., Watts M.E., Game E.T., Possingham 
H.P.. 2011. Planning for reserve Adequacy in dynamic 
landscapes; maximizing future representation of vegetation 
communities under flood disturbance in the Pantanal wetland. 
Diversity and Distributions, 17, pp. 297-310. 
McVicar, T.R., Jupp, D.L.B., 1998. The current and potential 
operational uses of remote sensing to aid decisions on drought 
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Penatti, N.C., Marques, H.G., Almeida, T.I.R., 2011. Imagens 
MODIS aplicadas ao estudo da subdivisäo do Pantanal em áreas 
geolögica | e  ambientalmente  homdlogas: resultados 
preliminares. Anais XV Simpósio Brasileiro de Sensoriamento 
Remoto - SBSR, Curitiba, Brasil, INPE, pp. 3559-3566. 
RADAMBRASIL, 1982. Project RADAMBRASIL. Folha 
SE.21 Corumbá. Geologia, geomorfologia, solos, vegetaçäo uso 
potencia da terra. Min. Mines Energy, Rio de Janeiro. pp. 448. 
Redo, D. J., Millington, A.C., 2011. A hybrid approach to 
mapping land-use modification and land-cover transition from 
MODIS time-series data: A case study from the Bolivian 
seasonal tropics. Remote Sensing of Environment, 115, pp. 353- 
372. 
Wardlow, B.D., Egbert, S.L., Kastens, J.H., 2007. Analysis of 
time-series MODIS 250m vegetation index data for crop 
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7. ACKNOWLEDGEMENTS 
The authors acknowledge FAPESP (Process 2010/52614-4) for 
financial support, Natasha Costa Penatti to CAPES for the 
Ph.D. scholarship and Teodoro Isnard Ribeiro de Almeida to 
CNPq for the grant. 
  
  
    
    
  
  
  
    
   
   
    
   
    
   
   
   
   
   
   
   
   
    
   
   
   
   
   
   
   
   
   
    
   
  
    
    
   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
    
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