AI Article Synopsis
- The research evaluated how well band algorithms estimate chlorophyll-a (Chl-a) levels using two satellite sensors: Landsat-8's Operational Land Imager (OLI) and Sentinel-2A's MultiSpectral Instrument (MSI).
- Researchers adapted band combinations from older satellites (Landsat-5 and Envisat) for use with the new sensors and calibrated the algorithms with on-site measurements from different seasons.
- The study found that most algorithms were minimally affected by sensor differences, but their effectiveness was notably reduced due to variations in the reservoir's bio-optical properties, a drought in 2014, and issues related to pigment packaging.
Article Abstract
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 onboard 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 MSI/Sentinel-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 performance has been hampered by the bio-optical difference in the reservoir sections, drought in 2014 and pigment packaging.
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| http://dx.doi.org/10.1590/0001-3765201720170125 | DOI Listing |
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Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil).
An Acad Bras Cienc
August 2018
Department of Cartography, São Paulo State University, Rua Roberto Simonsen, 305, 19060-900 Presidente Prudente, SP, Brazil.
Article Synopsis
- The research evaluated how well band algorithms estimate chlorophyll-a (Chl-a) levels using two satellite sensors: Landsat-8's Operational Land Imager (OLI) and Sentinel-2A's MultiSpectral Instrument (MSI).
- Researchers adapted band combinations from older satellites (Landsat-5 and Envisat) for use with the new sensors and calibrated the algorithms with on-site measurements from different seasons.
- The study found that most algorithms were minimally affected by sensor differences, but their effectiveness was notably reduced due to variations in the reservoir's bio-optical properties, a drought in 2014, and issues related to pigment packaging.
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