AndreaBozzo/ceres-open-data-index huggingface dataset:
Aquatic Ecological Units Vector Dataset

A vectorized version of the original Aquatic Ecological Units (AEUs) dataset. Please see the link [here ] for the original raster dataset. Owing to the enormity and complexity of the Laurentian Great Lakes, an ecosystem classification is needed to better understand, protect, and manage this largest freshwater ecosystem in the world. Using a combination of statistical analyses, published knowledge, and expert opinion, key driving variables and their ecologically relevant thresholds were delineated and mapped for the entire Great Lakes. A total of 77 aquatic ecological units (AEUs) were identified and mapped, depicting unique combinations of depth, thermal regime, hydraulic, and landscape classifiers. Those 77 AEU types were distributed across 1,997 polygons (patches) ranging from 1 to >48,000 km2 in area and were most diverse in the nearshore (35 types), followed by the coastal margin (26), and then the offshore (16). Classification and mapping of ecological units captures gradients that characterize types of aquatic systems in the Great Lakes and provides a geospatial accounting framework for resource inventory, status and trend assessment; research for ecosystem questions; and management and policy-making. This classification is described in: Riseng, Catherine, M., Kevin E. Wehrly, Li Wang, Edward S. Rutherford, James E. McKenna Jr., Lucinda B. Johnson, Lacey A. Mason, Christian Castiglione, Thomas P. Hollenhorst, Beth L. Sparks-Jackson, Scott P. Sowa (2018) Ecosystem classification and mapping of the Laurentian Great Lakes. Canadian Journal of Fisheries and Aquatic Sciences, 2018, 75:1693-1712, https://doi.org/10.1139/cjfas-2017-0242.
Aquatic Ecological Units Raster Dataset (original)

Owing to the enormity and complexity of the Laurentian Great Lakes, an ecosystem classification is needed to better understand, protect, and manage this largest freshwater ecosystem in the world. Using a combination of statistical analyses, published knowledge, and expert opinion, key driving variables and their ecologically relevant thresholds were delineated and mapped for the entire Great Lakes. A total of 77 aquatic ecological units (AEUs) were identified and mapped, depicting unique combinations of depth, thermal regime, hydraulic, and landscape classifiers. Those 77 AEU types were distributed across 1,997 polygons (patches) ranging from 1 to >48,000 km2 in area and were most diverse in the nearshore (35 types), followed by the coastal margin (26), and then the offshore (16). Classification and mapping of ecological units captures gradients that characterize types of aquatic systems in the Great Lakes and provides a geospatial accounting framework for resource inventory, status and trend assessment; research for ecosystem questions; and management and policy-making. This classification is described in: Riseng, Catherine, M., Kevin E. Wehrly, Li Wang, Edward S. Rutherford, James E. McKenna Jr., Lucinda B. Johnson, Lacey A. Mason, Christian Castiglione, Thomas P. Hollenhorst, Beth L. Sparks-Jackson, Scott P. Sowa (2018) Ecosystem classification and mapping of the Laurentian Great Lakes. Canadian Journal of Fisheries and Aquatic Sciences, 2018, 75:1693-1712, [https://doi.org/10.1139/cjfas-2017-0242]. The dataset consists of a geodatabase containing five raster files (Aquatic Ecological Units, cumulative degree day classification, depth classification, mechanical energy classification, and tributary influence classification) and five layer files containing sympology for the corresponding raster files.
Great Lakes USACE Stations Annual Wave Stats 1979-2012

WIS uses proven numerical wave hindcast models with the best available input wind fields to produce output wave parameters and wave spectra for stations near the U.S. coast, the Great Lakes and territories for periods of 20 years or more. Hindcast results are verified through comparison to all available measured data. New techniques of spectral comparisons have been developed to determine the accuracy of hindcasted directional wave spectra. Data is calculated at an hourly time step for the years 1979-2012. The Great Lakes Aquatic Habitat Framework (GLAHF) project computed summary statistics for annual, monthly, and seasonal time peroids for mean windspeed (meters / second); mean, maximum and coefficient of variation of wave height (meters); and mean wave period (seconds). More information can be found at https://wis.erdc.dren.mil/.
Reef predictions for Good Harbor Reef and Sleeping Bear Dunes National Lakeshore

This geodatabase contains a variety of datasets resulting from down-scaled Lake Michigan reef modeling for Good Harbor Reef and surrounding nearshore areas of the Sleeping Bear Dunes National Lakeshore (see Case Study 1 from citation in Credits). Datasets include predictor rasters (depth, bathymetric position index, and distance to hard substrate) and a raster of reef model results at a 2 m resolution. See metadata for individual datasets along with the supporting publication for more details.