Skip to main content

Reflectance of floodplain waterbodies using EO-1 Hyperion data from high and receding flood periods of the Amazon River

Buy Article:

$63.00 plus tax (Refund Policy)

The potential of Hyperion images acquired on September 2001 (receding flood period of the Amazon River) and June 2005 (high flood) was investigated for reflectance characterization of selected Amazon floodplain waterbodies using a linear spectral mixture model. The results show the ability of Hyperion to measure adequately the major variation in water reflectance spectral features in response to the annual flood pulse of the Amazon River. Mixture model fraction values were correlated with measured inorganic suspended solids (ISS) but not with chlorophyll (Chl) in the high flood period. Inspection of the fractions across the two images revealed variation in water composition. Small changes in ISS- and Chl-bearing water fractions between the images indicated relatively stable spectral conditions for low (Tapajos River and Lake Juruparipucu) and high (Amazon River) turbidity waterbodies. Large changes indicated reflectance variation in some lakes when the water receded due to algal blooms (Lake Curumu) and sediment resuspension in shallow regions (Lake Aritapera). Although not all water constituents were modelled adequately for quantification purposes, spectral mixture modelling is still an interesting approach for spectral-temporal reflectance characterization of Amazonian floodplains with hyperspectral data.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Affiliations: Instituto Nacional de Pesquisas Espaciais (INPE), Divisao de Sensoriamento Remoto, Sao Jose dos Campos, SP, Brazil

Publication date: 2009-01-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more