Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil)

• Autor(a) principal: Watanabe, Fernanda [UNESP]
• Data de Publicação: 2018
• Outros Autores: Alcantara, Enner [UNESP], Rodrigues, Thanan [UNESP], Rotta, Luiz [UNESP], Bernardo, Nariane [UNESP], Imai, Nilton [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1590/0001-3765201720170125; http://hdl.handle.net/11449/164540
• topic: algal bloom; inland water color; spectral index; water quality; satellite imagery

In this present research, we assessed the performance of band algorithms in estimating chlorophyll-a (Chl-a) concentration based on bands of two new sensors: Operational Land Imager onboancl Landsat-8 satellite (OLI/Landsat-8), and MultiSpectral Instrument onboard Sentinel-2A (MSI/Sentinel-2A). Band combinations designed for Thematic Mapper onboard Landsat-5 satellite (TM/Landsat-5) and MEdium Resolution Imaging Spectrometer onboard Envisat platform (MERIS/Envisat) were adapted for OLI/Landsat-8 and MSUSentinel-2A bands. Algorithms were calibrated using in situ measurements collected in three field campaigns carried out in different seasons. The study area was the Barra Bonita hydroelectric reservoir (BBHR), a highly productive aquatic system. With exception of the three-band algorithm, the algorithms were spectrally few affected by sensors changes. On the other hands, algorithm perfonnance has been hampered by the bio-optical difference in the reservoir sections, drought in 2014 and pigment packaging.