Cyanobacteria detection in Guarapiranga Reservoir (São Paulo State, Brazil) using Landsat TM and ETM+ images

  • Igor Ogashawara Instituto Nacional de Pesquisas Espaciais (INPE)
  • Enner Herenio de Alcântara Universidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP)
  • José Luiz Stech Instituto Nacional de Pesquisas Espaciais (INPE)
  • José Galizia Tundisi Instituto Internacional de Ecologia (IIE)
Keywords: phytoplankton, water quality, environmental health, satellite imagery


Algae bloom is one of the major consequences of the eutrophication of aquatic systems, including algae capable of producing toxic substances. Among these are several species of cyanobacteria, also known as blue-green algae, that have the capacity to adapt themselves to changes in the water column. Thus, the horizontal distribution of cyanobacteria harmful algae blooms (CHABs) is essential, not only to the environment, but also for public health. The use of remote sensing techniques for mapping CHABs has been explored by means of bio-optical modeling of phycocyanin (PC), a unique inland waters cyanobacteria pigment. However, due to the small number of sensors with a spectral band of the PC absorption feature, it is difficult to develop semi-analytical models. This study evaluated the use of an empirical model to identify CHABs using TM and ETM+ sensors aboard Landsat 5 and 7 satellites. Five images were acquired for applying the model. Besides the images, data was also collected in the Guarapiranga Reservoir, in São Paulo Metropolitan Region, regarding the cyanobacteria cell count (cells/mL), which was used as an indicator of CHABs biomass. When model values were analyzed excluding calibration factors for temperate lakes, they showed a medium correlation (R2=0.81, p=0.036), while when the factors were included the model showed a high correlation (R2=0.96, p=0.003) to the cyanobacteria cell count. The empirical model analyzed proved useful as an important tool for policy makers, since it provided information regarding the horizontal distribution of CHABs which could not be acquired from traditional monitoring techniques.

Author Biographies

Igor Ogashawara, Instituto Nacional de Pesquisas Espaciais (INPE)
Remote Sensing Division
Enner Herenio de Alcântara, Universidade Estadual Paulista “Júlio de Mesquita Filho” (UNESP)
Departamento de Cartografia
José Luiz Stech, Instituto Nacional de Pesquisas Espaciais (INPE)
Remote Sensing Division