2023 NOAA Topobathy Lidar: Northern Lake Michigan & Northern Lake Huron, MI

Product: This topobathy lidar dataset consists of processed classified LAS 1.4 files used to create intensity images and topobathymetric DEMs as necessary.

Three project areas for this dataset are:

1. Lansing Shoals - 4273 individual 500 m x 500 m tiles

2. Green Bay - 1837 individual 500 m x 500 m tiles

3. Lake Huron - 2871 individual 500 m x 500 m tiles

Geographic Extent: The Michigan coastline along parts of northern Lake Michigan and northern Lake Huron, covering approximately 627 square miles.

1. Lansing Shoals portion (Lake Michigan) of the AOI covers approximately 311 square miles

2. Green Bay portion (Lake Michigan) of the AOI covers approximately 116 square miles

3, Lake Huron portion of the AOI covers approximately 200 square miles

Dataset Description: The Great Lakes Topobathymetric Lidar project called for the planning, acquisition, processing and derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 1 meter for bathymetric areas. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.3. The data was developed based on a horizontal projection/datum of NAD83 (2011), UTM zones 16N and 17N, meters and vertical datum of NAVD88 (Geoid 18), meters.

Ground Conditions:

1. Lansing Shoals - Lidar was collected for the Lansing Shoals region from September 14, 2023 to September 25, 2023, while no snow was on the ground and rivers were at or below normal levels

2. Green Bay - Lidar was collected for the Green Bay region from September 28, 2023 to October 5, 2023, while no snow was on the ground and rivers were at or below normal levels.

3, Lake Huron - Lidar was collected for the Northern Lake Huron region from September 16, 2023 to October 4, 2023, while no snow was on the ground and rivers were at or below normal levels.

This project has two primary goals to fill critical gaps in our understanding of benthic habitat within Lakes Michigan and Huron. The first goal is the collection of new bathymetric lidar to support multiple agencies including NOAA; US Fish and Wildlife Service; state agencies with Michigan and Wisconsin; and other regional partners' mapping and modeling needs by expanding existing high resolution bathymetry coverage in and around the Entry to Lansing Shoals and Lansing Shoals, Lake Michigan, and Northern Huron in Lake Huron. The second goal is to use this bathymetry in the creation of new benthic mapping products using the Coastal and Marine Ecological Classification Standard (CMECS). Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create Intensity Images and Raster DEMs. The purpose of these lidar data was to produce high accuracy Digital Elevation Model (DEM) with a 1 meter cell size. These lidar point cloud data were used to create intensity images and topobathymetric DEMs as necessary.

Contract No. 1305M221DNCNP0017 CONTRACTOR: Dewberry Engineers. Lidar data were acquired and calibrated by Dewberry. All follow-on processing was completed by Dewberry. A complete description of this dataset is available in the Final Project Report that will be submitted to NOAA.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification v 1.3",

"ldrsens" : "CZMIL (Topo Channels)",

"ldrmaxnr" : "15",

"ldrnps" : "0.38",

"ldrdens" : "7",

"ldranps" : "0.38",

"ldradens" : "7",

"ldrfltht" : "400",

"ldrfltsp" : "130",

"ldrscana" : "40",

"ldrscanr" : "27",

"ldrpulsr" : "140",

"ldrpulsd" : "1.2-2.1",

"ldrpulsw" : "na",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "5",

"ldrswatw" : "291",

"ldrswato" : "30",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid 18"

},

"ldrinfo" : {

"ldrspec" : "U.S. Geological Survey (USGS) - National Geospatial Program (NGP) Lidar Base Specification v 1.3",

"ldrsens" : "CZMIL (Shallow/Deep Bathy Channels)",

"ldrmaxnr" : "15",

"ldrnps" : "0.38",

"ldrdens" : "7",

"ldranps" : "0.38",

"ldradens" : "7",

"ldrfltht" : "400",

"ldrfltsp" : "130",

"ldrscana" : "40",

"ldrscanr" : "27",

"ldrpulsr" : "140",

"ldrpulsd" : "1.2-2.1",

"ldrpulsw" : "proprietary",

"ldrwavel" : "532",

"ldrmpia" : "1",

"ldrbmdiv" : "5",

"ldrswatw" : "291",

"ldrswato" : "30",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid 18"

},

"ldraccur" : {

"ldrchacc" : "0",

"rawnva" : "0",

"rawnvan" : "0"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Withheld (ignore) points were identified in these files using the standard LAS Withheld bit. Noise classes, class 7 and class 18, were assigned LAS withheld bit.",

"lasolap" : "The LAS overlap bit was not utilized for this dataset.",

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare Earth, Ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low Noise"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High Noise"

},

"lasclass" : {

"clascode" : "40",

"clasitem" : "Bathymetric Bottom"

},

"lasclass" : {

"clascode" : "41",

"clasitem" : "Water Surface"

},

"lasclass" : {

"clascode" : "42",

"clasitem" : "Synthetic Water Surface"

},

"lasclass" : {

"clascode" : "45",

"clasitem" : "Water Column"

}

}}

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners.

Data is available online for bulk and custom downloads.

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.

CZMIL SuperNOVA; CARIS; LAStools; Microstation; Terrascan; ArcGIS 10.6; Microsoft Windows 10 Enterprise Service Pack 1

Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested.

Lidar vendors calibrate their lidar systems during installation of the system and then again for every project acquired. Typical calibrations include cross flights that capture features from multiple directions that allow adjustments to be performed so that the captured features are consistent between all swaths and cross flights from all directions. This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 41 cm RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1 meter at a 95% confidence level.

The topographic portion of this lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz = 6.9 cm, equating to plus or minus 13.6 cm at 95% confidence level. The bathymetric portion of this lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 15.0 cm RMSEz Vertical Accuracy Class. Actual bathymetric vertical accuracy was found to be RMSEz = 13.5 cm, equating to plus or minus 26.4 cm at 95% confidence level.

Topobathymetric data covers the project boundary to the fullest extent possible depending on water clarity, environmental conditions, and sensor signal returns. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.

Data covers the entire area specified for this project.

Data is backed up to cloud storage.

Dewberry acquired, processed, and calibrated the lidar data for this project. The data deliverables were provided to the NOAA Office for Coastal Management (OCM) to make the data publicly available on the NOAA Digital Coast.