INLA CONUS forecast

공공데이터포털

OLCI satellite data with CI_cyano algorithm quantify cyanobacteria. Air temperature, precipitation data from PRISM Climate group. This dataset is associated with the following publication: Schaeffer, B., N. Reynolds, H. Ferriby, W. Salls, D. Smith, J. Johnston, and M. Myer. Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 349: 119518, (2024).

CONUS extent

공공데이터포털

MERIS and OLCI satellite data with CI_cyano algorithm quantify the spatial extent of cyanobacteria. This dataset is associated with the following publication: Schaeffer, B., E. Urquhart, M. Coffer, W. Salls, R. Stumpf, K. Loftin, and P.J. Werdell. Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 140: 108990, (2022).

CONUS extent

공공데이터포털

MERIS and OLCI satellite data with CI_cyano algorithm quantify the spatial extent of cyanobacteria. This dataset is associated with the following publication: Schaeffer, B., E. Urquhart, M. Coffer, W. Salls, R. Stumpf, K. Loftin, and P.J. Werdell. Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 140: 108990, (2022).

Lake cyanoHAB occurrence

공공데이터포털

ESA Envisat MERIS 300mx300m raster ocean color data using cyanobacteria index (CI) algorithm. This dataset is associated with the following publication: Coffer, M., B. Schaeffer, J. Darling, E. Urquhart, and W. Salls. Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 111: 105976, (2020).

Lake cyanoHAB occurrence

공공데이터포털

ESA Envisat MERIS 300mx300m raster ocean color data using cyanobacteria index (CI) algorithm. This dataset is associated with the following publication: Coffer, M., B. Schaeffer, J. Darling, E. Urquhart, and W. Salls. Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 111: 105976, (2020).

Sentinel-3B OLCI Global Binned Cyanobacteria Index (CI) - 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 Binned Cyanobacteria Index (CI) - 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.

Data for satellites predict lakes at risk from cyanobacteria and microcystin toxins

공공데이터포털

Data for analysis for modeling probability of measuring microcystin toxin, cyanobacteria cell abundance, and chlorophyll a concentration in ~2,200 lakes based on cyanobacteria summer bloom magnitude measured by satellite imagery. This dataset is associated with the following publication: Handler, A., J. Compton, R. Hill, S. Leibowitz, and B. Schaeffer. Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 869: 161784, (2023).

Data for satellites predict lakes at risk from cyanobacteria and microcystin toxins

공공데이터포털

Data for analysis for modeling probability of measuring microcystin toxin, cyanobacteria cell abundance, and chlorophyll a concentration in ~2,200 lakes based on cyanobacteria summer bloom magnitude measured by satellite imagery. This dataset is associated with the following publication: Handler, A., J. Compton, R. Hill, S. Leibowitz, and B. Schaeffer. Identifying lakes at risk of toxic cyanobacterial blooms using satellite imagery and field surveys across the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 869: 161784, (2023).

Sentinel-3B OLCI Global Binned Cyanobacteria Index (CI) 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.