67239
2016 FEMA Lidar: Michigan - Part 1
mi2016_part1_m9500_metadata
Data Set
Published / External
49401
Lidar - partner (no harvest)
Project
Completed
2016
2016
This metadata supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.
The State of Michigan (DTMB) contracted with Sanborn to provide LiDAR mapping services for 10 counties in the State of Michigan. These counties include Clare, Lake, Mecosta, Missaukee, Montcalm, Muskegon, Newaygo, Osceola, Roscommon, and Wexford. Utilizing multi-return systems, Light Detection and Ranging (LiDAR) data in the form of 3-dimensional positions of a dense set of mass points was collected for the 10 counties in April and May of 2016. LAS data products are suitable for 1 foot contour generation. USGS LiDAR Base Specification 1.2, QL2. 19.6 cm NVA.
Clare County: data covers approximately 575 square miles
Lake County: data covers approximately 573 square miles
Mecosta County: data covers approximately 571 square miles
Missaukee County: data covers approximately 574 square miles
Montcalm County: data covers approximately 721 square miles
Muskegon County: This county is available from a different data set, see the links in the URL section of this metadata record for the metadata and custom download.
Newaygo County: data covers approximately 826 square miles
Osceola County: data covers approximately 573 square miles
Roscommon County: data covers approximately 580 square miles
Wexford County: data covers approximately 575 square miles
The purpose of this data set is the acquisition and production of high resolution elevation data for the State of Michigan. This LiDAR operation was designed to create high resolution data sets that will establish an authoritative source for elevation information for the State of Michigan to create detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments, and hydrologic modeling.
Project Projection, Datums and Units. Projection - State Plane Michigan Central and South. Horizontal datum - North American Datum of 1983 (NAD83 (2011)). Vertical datum - North American Vertical Datum of 1988 (NAVD88) using the latest geoid (Geoid12a) for converting ellipsoidal heights to orthometric heights. Units - intl feet
The following are the USGS lidar fields in JSON:
{
"ldrinfo" : {
"ldrspec" : "USGS Base Specification 1.2, QL2 meeting 19.6cm NVA",
"ldrsens" : "Leica ALS70",
"ldrmaxnr" : "4",
"ldrnps" : "0.65",
"ldrdens" : "1.67",
"ldradens" : "2.2",
"ldranps" : "0.71",
"ldrfltht" : "2250",
"ldrfltsp" : "135",
"ldrscana" : "20",
"ldrscanr" : "64",
"ldrpulsr" : "167",
"ldrpulsd" : "10",
"ldrpulsw" : "3",
"ldrwavel" : "1064",
"ldrmpia" : "1",
"ldrbmdiv" : "0.3",
"ldrswatw" : "1222",
"ldrswato" : "30",
"ldrcrs" : "NAD_1983_2011_State_Plane_Michigan_Central_2112_Ft_Intl" and
"NAD_1983_2011_State_Plane_Michigan_South_2113_Ft_Intl",
"ldrgeoid" : "NGS Geoid12a"
},
"ldraccur" : {
"ldrchacc" : "0.196",
"rawnva" : "0.137",
"rawnvan" : "183",
"clsnva" : "0.156",
"clsnvan" : "183",
"clsvva" : "0.169",
"clsvvan" : "211"
},
"lasinfo" : {
"lasver" : "1.4",
"lasprf" : "6",
"laswheld" : "Withheld points were identified in these files with the withheld flag",
"lasolap" : "Overlap points were identified in these files with the overlap flag",
"lasintr" : "10",
"lasclass" : {
"clascode" : "1",
"clasitem" : "Unclassified"
},
"lasclass" : {
"clascode" : "2",
"clasitem" : "Bare earth"
},
"lasclass" : {
"clascode" : "7",
"clasitem" : "Noise"
},
"lasclass" : {
"clascode" : "9",
"clasitem" : "Water"
},
"lasclass" : {
"clascode" : "10",
"clasitem" : "Ignored Ground (Breakline Proximity)"
},
"lasclass" : {
"clascode" : "17",
"clasitem" : "Bridges"
},
"lasclass" : {
"clascode" : "18",
"clasitem" : "High Noise"
}
}}
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
Theme
ISO 19115 Topic Category
elevation
Spatial
Global Change Master Directory (GCMD) Location Keywords
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
Spatial
Global Change Master Directory (GCMD) Location Keywords
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MICHIGAN
Spatial
Global Change Master Directory (GCMD) Location Keywords
VERTICAL LOCATION > LAND SURFACE
Instrument
Global Change Master Directory (GCMD) Instrument Keywords
LIDAR > Light Detection and Ranging
Platform
Global Change Master Directory (GCMD) Platform Keywords
Airplane > Airplane
Spatial
Clare County
Spatial
Lake County
Spatial
Mecosta County
Spatial
Missaukee County
Spatial
Montcalm County
Spatial
Newaygo County
Spatial
Osceola County
Spatial
Roscommon County
Spatial
Wexford County
Office for Coastal Management
Charleston
SC
Data Set
Elevation
Unknown
Model (digital)
USGS Base Specification 1.2, QL2 meeting 19.6 cm NVA
The State of Michigan Geographic Information Systems digital data have been tested and their documentation carefully reviewed. However, the State of Michigan and its representatives make no warranty or representation, either expressed or implied, with respect to the digital data and their documentation, their quality, performance, merchantability, or fitness for a particular purpose. The digital data are distributed on "as is" basis, and the user assumes all risk to their quality, the results obtained from their use, and the performance of the data. In no event will the State of Michigan or its representatives be liable for any direct, indirect, special, incidental or consequential damages resulting from and defect in the State of Michigan or in their documentation. This disclaimer of warranty is exclusive and in lieu of all others, oral or written, express or implied. No agent or employee is authorized to make any modification, extension, or addition to this warranty.
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners.
State of Michigan (SOM)
Data Steward
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2020
Organization
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston
VA
20191
USA
https://usgs.gov
USGS Home
Home page for USGS
Online Resource
Metadata Contact
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Point of Contact
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Ground Condition
-86.053291
-84.357281
44.519836
43.111103
Range
2016-04-15
2016-05-03
Dates of collection for Montcalm county.
Range
2016-04-15
2016-04-16
Dates of collection for Newaygo county.
Range
2016-04-15
2016-04-23
Dates of collection for Mecosta county.
Range
2016-04-16
2016-04-17
Dates of collection for Clare county.
Range
2016-04-23
2016-05-02
Dates of collection for Lake and Osceola counties.
Range
2016-04-29
2016-05-02
Dates of collection for Wexford county.
Range
2016-04-30
2016-05-02
Dates of collection form Missaukee county.
Range
2016-05-02
2016-05-03
Dates of collection for Roscommon county.
No
Yes
No
No
No
Projected
EPSG:3857
WGS 84 / Pseudo-Mercator
World Geodetic System 1984
WGS 84
6378137
298.257223563
WGS 84
Popular Visualisation Pseudo-Mercator
Popular Visualisation Pseudo Mercator
Latitude of natural origin
0° 0' 0" N
Longitude of natural origin
0° 0' 0" E
False easting
0
metre
False northing
0
metre
1
Easting
X
metre
east
2
Northing
Y
metre
north
Vertical
EPSG:5703
NAVD88 height
North American Vertical Datum 1988
1
Gravity-related height
H
metre
up
Unclassified
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.
2022-05-13
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9500/details/9500
2022
Organization
NOAA Office for Coastal Management
Customized Download
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options.
Zip
Zip
2022-05-13
https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/
2020
Organization
U.S. Geological Survey
Bulk Download
Bulk download of data files in LAZ format, MI State Plane South and Central, NAD83 (2011), international feet coordinates and a vertical datum of NAVD88 (GEOID12A), units in international feet. This url links to the USGS copy of the files, from which the Entwine Point Tile files originated. These have not been reviewed by OCM and the link is provided here for convenience.
LAZ
LAS/LAZ - LASer
Zip
https://coast.noaa.gov/dataviewer/
NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV)
Online Resource
HTML
The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer.
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8731/details/8731
Custom Download of Muskegon County Points
Online Resource
Zip
Link to custom download the Muskegon County lidar points that are part of this larger data set.
https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/MI_16CountiesFEMA2015_C16/
USGS Additional Info
Online Resource
Link to the additional information available for this data set from the USGS. This information includes reports, tile index shapefiles, and hydro breaklines.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Clare_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Clare County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Mecosta_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Mecosta County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Newaygo_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Newaygo County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Osceola_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Osceola County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Roscommon_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Roscommon County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Lake_2016_LAS_2017/ept.json
Entwine Point Tiles (EPT) for Lake County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Missaukee_2016_LAS_2017/ept.json
Entwine Point Tiles (EPT) for Missaukee County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Montcalm_2015_LAS_2018/ept.json
Entwine Point Tiles (EPT) for Montcalm County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Wexford_2016_LAS_2017/ept.json
Entwine Point Tiles (EPT) for Wexford County
Online Resource
json
Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud.
https://usgs.entwine.io/data/view.html?r=[%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Clare_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Mecosta_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Newaygo_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Osceola_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_16Co_Roscommon_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Lake_2016_LAS_2017/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Missaukee_2016_LAS_2017/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Montcalm_2015_LAS_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/USGS_LPC_MI_Wexford_2016_LAS_2017/ept.json%22]
Potree 3D View
Online Resource
Link to view the point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer.
https://www.fisheries.noaa.gov/inport/item/56271
Muskegon County Metadata
Online Resource
Link to the Muskegon County metadata.
Microsoft Windows 7; ESRI ArcCatalog 9.3.1.1850
Horizontal positional accuracy for the 10 counties is dependent upon the quality of the GPS/INS solution, sensor calibration and ground conditions at the time of data capture. The standard system results for horizontal accuracy meet or exceed the project specified 1.0 meter RMSE. For the 10 counties, this value is computed by comparing ground control to a DEM derived from the classified LiDAR data and represents the RMSE of residuals on controls within the project area.
For the DEM data derived from the classified point cloud, the NVA and VVA were computed. The vertical accuracy was tested with independent survey check points located in various terrain types within the 10 counties. These check points were not used in the calibration or post processing of the lidar point cloud data. The survey check points were distributed throughout the block area. Specifications for this project require that the NVA be 19.6 cm or better @ 95 percent confidence level. The raw NVA was tested using 183 independent survey check points located in flat terrain types within the 10 counties. The survey checkpoints were distributed throughout the block area. The 183 independent check points were surveyed using static GPS base stations collecting point location for 20 minute intervals. Elevations were measured for the x,y,z location of each check point. Elevations interpolated from the DEM surface were then compared to the elevation values of the surveyed control.
The NVA was tested using 183 independent survey check points located in bare earth terrain types within the 10 counties. The 183 independent check points contained all NVA points and were surveyed using static GPS base stations collecting point location for 20 minute intervals. Elevations were measured for the x,y,z location of each check point. Elevations interpolated from the DEM surface were then compared to the elevation values of the surveyed control. The RMSE was computed to be 0.070m, or 0.137m @ 95th Confidence Interval defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
The VVA was tested using 211 independent survey check points located in various vegetation terrain types within the 10 counties. The 211 independent check points were surveyed using static GPS base stations collecting point location for 20 minute intervals. Elevations were measured for the x,y,z location of each check point. Elevations interpolated from the DEM surface were then compared to the elevation values of the surveyed control. The RMSE was computed to be 0.078m, or 0.169m @ 95th Percentile defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
LiDAR data is collected for the project area. Post processing of the simultaneously acquired GPS/INS is performed and applied to the laser returns to output a point cloud in the specified project coordinate system and datums. The point cloud data is then subjected to automated classification routines to assign all points in the point cloud to ground, water, overlap and unclassified point classes. Anomalous laser returns that occur infrequently are removed entirely from the data set. Once clean bare earth points are established, DEMs are created using bare earth points and hydro features. The DEM surface is then compared to the survey checkpoints. These accuracies must pass the Fundamental Vertical Accuracy, Supplemental Vertical Accuracy, and Consolidated Vertical Accuracy specifications.
LiDAR data is collected within the project area and processed. After the DEMs were created, the dataset was verified against control. Control was collected in 10 adjoining counties in Michigan. These counties include: Clare, Lake, Mecosta, Missaukee, Montcalm, Muskegon, Newaygo, Osceola, Roscommon, and Wexford. Accuracy is reported for all 10 counties combined.
Yes
Unknown
Yes
NCEI-CO
Data is backed up to tape and to cloud storage.
The 2016 FEMA Michigan Part 1 lidar was ingested into the Data Access Viewer for custom product generation by leveraging USGS hosted Entwine Point Tiles.
Entwine Point Tiles on AWS
Organization
USGS
Publisher
https://usgs.entwine.io/
USGS Entwine Point Cloud
1
At selected locations throughout the site, accurate GPS coordinates and elevations are surveyed and the points are marked with targets.
2016-01-01T00:00:00
2
New LiDAR data is captured for the project area using a Leica ALS70 LiDAR instrument an integrated IPAS20 GPS/INS system mounted within a Aero Commander twin engine airplane.
2016-01-01T00:00:00
3
The airborne GPS data is post-processed in Inertial Explorer software and LEICA CloudPro software to determine the LiDAR sensor's angle and orientation in the terrain (project) coordinate system and datums during the survey.
2016-01-01T00:00:00
4
The post processed GPS/INS solution is applied to the raw lidar data to orient and project the data points into the project area reference system as an unclassified point cloud.
2016-01-01T00:00:00
5
The georeferenced lidar data is then classified and edited in Terrasolid Terrascan software. Data is classified to produce: Class 1: unclassified, Class 2: ground, Class 7: low point, Class 9: water, Class 10: ignored ground, Class 11: withheld.
2016-01-01T00:00:00
6
The classified lidar data is exported as 2500 X 2500 foot tiles in the LAS format with any or all classes required to produce derivative products.
2016-01-01T00:00:00
7
Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 Web Mercator (EPSG 3857). Vertically, the data were converted to meters and no changes were made to the vertical datum (NAVD88 GEOID12A; EPSG 5703).
Organization
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston
VA
20191
USA
https://usgs.gov
USGS Home
Home page for USGS
Online Resource
8
References to the entwine point tiles and data reports were ingested into the Digital Coast Data Access Viewer. No changes to the data were made at this point. The Data Access Viewer will access the point cloud as it resides on AWS under the usgs-lidar-public container.
2022-05-12T00:00:00
Organization
Office for Coastal Management
OCM
2234 South Hobson Avenue
Charleston
SC
29405-2413
https://www.coast.noaa.gov/
56271
Data Set
2016 FEMA Michigan Lidar: Part 1 (Muskegon County)
Cross Reference
gov.noaa.nmfs.inport:67239
Rebecca Mataosky
2022-05-13T12:35:45
SysAdmin InPortAdmin
2023-10-17T16:12:36
2022-05-13
OCM Partners
OCMP
1002
Public
No
2022-05-13
1 Year
2023-05-13