Modifications were made to an existing Lake St. Clair topobathy data set to interpolate areas of missing near shore elevation data. Areas with missing elevation data were not interpolated where there was low confidence in the underlying depth. This included rivers, canals, harbors, lakes, reservoirs, etc. Areas important for targeting Phragmites australis management often lie within these aquatic/terrestrial transition zones. A shaded relief map was generated for the modified digital elevation model. The original topobathy data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The base elevation data were the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. The base elevation includes data for Alcona, Alpena, Arenac, Bay, Cheboygan, Chippewa, Huron, Iosco, Mackinac, Presque Isle, Sanilac, St. Clair, and Tuscola counties in Michigan.

Modifications were made to an existing Lake Ontario topobathy data set to interpolate areas of missing near shore elevation data. Areas with missing elevation data were not interpolated where there was low confidence in the underlying depth. This included rivers, canals, harbors, lakes, reservoirs, etc. Areas important for targeting Phragmites australis management often lie within these aquatic/terrestrial transition zones. A shaded relief map was generated for the modified digital elevation model. The original topobathy data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The base elevation data were the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. The base elevation includes data for Alcona, Alpena, Arenac, Bay, Cheboygan, Chippewa, Huron, Iosco, Mackinac, Presque Isle, Sanilac, St. Clair, and Tuscola counties in Michigan.

Modifications were made to an existing Lake Ontario topobathy data set to interpolate areas of missing near shore elevation data. Areas with missing elevation data were not interpolated where there was low confidence in the underlying depth. This included rivers, canals, harbors, lakes, reservoirs, etc. Areas important for targeting Phragmites australis management often lie within these aquatic/terrestrial transition zones. The original topobathy data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The base elevation data were the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. The base elevation includes data for Alcona, Alpena, Arenac, Bay, Cheboygan, Chippewa, Huron, Iosco, Mackinac, Presque Isle, Sanilac, St. Clair, and Tuscola counties in Michigan.

Modifications were made to an existing Lake Superior topobathy data set to interpolate areas of missing near shore elevation data. Areas with missing elevation data were not interpolated where there was low confidence in the underlying depth. This included rivers, canals, harbors, lakes, reservoirs, etc. Areas important for targeting Phragmites australis management often lie within these aquatic/terrestrial transition zones. The original topobathy data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The base elevation data were the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. The base elevation includes data for Alcona, Alpena, Arenac, Bay, Cheboygan, Chippewa, Huron, Iosco, Mackinac, Presque Isle, Sanilac, St. Clair, and Tuscola counties in Michigan.

This dataset is a LAS (industry-standard binary format for storing large point clouds) dataset containing light detection and ranging (LiDAR) data and sonar data representing the beach and near-shore topography of Lake Superior at Minnesota Point, Duluth, Minnesota. Average point spacing of the LAS files in the dataset are as follows: LiDAR, 0.137 meters (m); multi-beam sonar, 1.029 m; single-beam sonar, 0.999 m. The LAS dataset was used to create a 10-m (32.8084 feet) digital elevation model (DEM) of the approximately 5.9 square kilometer (2.3 square mile) surveyed area using the "LAS dataset to raster" tool in Esri ArcGIS, version 10.7. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). Multi-beam sonar data were collected August 7-11, 2019 using an R2Sonic 2024 sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 27-28, 2019 using a CEESCOPE single-beam echosounder and methodology similar to that described by Wilson and Richards (2006).

These data are digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point near the Duluth Entry, Duluth, Minnesota. A LAS dataset was used to create DEMs of 10 meter (m; 32.8084 feet) and 1 m (3.28084 feet) resolution, covering the approximately 1.75 square kilometer surveyed area. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.094 meters (m); multibeam sonar, 0.501 m; single-beam sonar, 1.876 m. Lidar data were collected August 22, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected August 22-23, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 23, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

These data are digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point, near the Superior entry, Duluth, Minnesota. The DEMs have 1 meter (m; 3.28084 ft) and/or 10 m (32.8084 ft) cell size and was created from a LAS dataset of terrestrial light detection and ranging (LiDAR) data representing the beach topography and sonar data representing the bathymetry for an approximate 1.78 square kilometer survey area. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.055 meters (m); multibeam sonar, 0.511 m; single-beam sonar, 1.687 m. Lidar data were collected November 01, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected October 31-November 01, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected November 01, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

These data are digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point near the Duluth Entry, Duluth, Minnesota. A LAS dataset was used to create DEMs of 10 meter (m; 32.8084 feet) and 1 m (3.28084 feet) resolution, covering the approximately 1.75 square kilometer surveyed area. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.094 meters (m); multibeam sonar, 0.501 m; single-beam sonar, 1.876 m. Lidar data were collected August 22, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected August 22-23, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 23, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

Modifications were made to Great Lakes topobathy data to interpolate areas of missing near shore elevation data. Areas with missing elevation data were not interpolated where there was low confidence in the underlying depth. This included rivers, canals, harbors, lakes, reservoirs, etc. Areas important for targeting Phragmites australis management often lie within these aquatic/terrestrial transition zones. The original topobathy data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the NOAA Lake Level Viewer. It depicts potential lake level rise and fall and its associated impacts on the nation's coastal areas. The base elevation data were the best available lidar and US Army Corps of Engineer dredge survey data known to exist at the time of DEM creation that met project specifications. Water depths were modeled using the updated topobathy data set and a low water datum (https://tidesandcurrents.noaa.gov/gldatums.html) used to denote a static water surface elevation. Low water datums (LWD) are a stable water surface elevation that doesn't change over time based on fluctuating water levels. Water depths were modeled at levels 3 feet below to 10 feet above the LWD in 1/2 foot increments. Units are in centimeters, the larger the negative value, the deeper the water. These water depths do not consider natural processes such as erosion, subsidence, or future construction. Water extent is as it would appear on a calm day with no wind-driven waves or seiche effect. The mapping may not accurately capture detailed hydrologic/hydraulic features such as canals, ditches, and stormwater infrastructure, resulting in inundated areas that are not connected to a lake. A more detailed analysis may be required to determine an area's actual susceptibility to flooding. The data should be used only as a screening-level tool (https://coast.noaa.gov/llv).

These data are digital elevation models (DEMs) of the beach topography and near-shore bathymetry of Lake Superior at Minnesota Point, near the Superior entry, Duluth, Minnesota. The DEMs have 1 meter (m; 3.28084 ft) and/or 10 m (32.8084 ft) cell size and was created from a LAS dataset of terrestrial light detection and ranging (LiDAR) data representing the beach topography and sonar data representing the bathymetry for an approximate 1.78 square kilometer survey area. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.055 meters (m); multibeam sonar, 0.511 m; single-beam sonar, 1.687 m. Lidar data were collected November 01, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected October 31-November 01, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected November 01, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.