Sentinel-3A OLCI Global Binned CyAN Project, True Color (TC) - Near Real-Time (NRT) Data, version 5.0

공공데이터포털

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Sentinel-3B OLCI Global Mapped CyAN Project, True Color (TC) - Near Real-Time (NRT) Data, version 5.0

공공데이터포털

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Sentinel-3A OLCI Global Mapped CyAN Project, True Color (TC) - Near Real-Time (NRT) Data, version 5.0

공공데이터포털

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Merged Sentinel-3A and Sentinel-3B OLCI Global Binned CyAN Project, True Color (TC) - Near Real-Time (NRT) Data, version 5.0

공공데이터포털

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Sentinel-3B OLCI Global Binned CyAN Project, True Color (TC) Data, version 5.0

공공데이터포털

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Sentinel-3A OLCI Global Binned CyAN Project, True Color (TC) Data, version 5.0

공공데이터포털

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Merged Sentinel-3A and Sentinel-3B OLCI Global Mapped CyAN Project, True Color (TC) - Near Real-Time (NRT) Data, version 5.0

공공데이터포털

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Sentinel-3B OLCI Global Mapped CyAN Project, True Color (TC) Data, version 5.0

공공데이터포털

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Sentinel-3A OLCI Global Mapped CyAN Project, True Color (TC) Data, version 5.0

공공데이터포털

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. This effort has resulted in the production of satellite remote sensing products using the cyanobacteria index (CI) algorithm to estimate cyanobacteria concentrations (CI_cyano) in lakes across the contiguous United States (CONUS) and Alaska. The Merged S3 product combines Sentinel-3A and Sentinel-3B OLCI data.

Merged Sentinel-3A and Sentinel-3B OLCI Global Binned CyAN Project, True Color (TC) Data, version 5.0

공공데이터포털

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. The sensor spatial resolution is 300m. The CONUS images use a 50m land mask, while the Alaska product uses a less refined 500m land mask. The temporal resolution depends on the sensor and date with best coverage since 2018, as images utilize sensors on two Sentinel-3 satellites.