Dickinson County, MI LIDAR_LAS_1.2
Data Set (DS) | OCM Partners (OCMP)GUID: gov.noaa.nmfs.inport:49803 | Updated: August 9, 2022 | Published / External
Summary
Short Citation
OCM Partners, 2024: Dickinson County, MI LIDAR_LAS_1.2, https://www.fisheries.noaa.gov/inport/item/49803.
Full Citation Examples
TASK NAME:(NRCS) Dickinson County, MI LIDAR
LiDAR Data Acquisition and Processing Production Task
USGS Contract No. G10PC00057
Task Order No. G12PD00721
Woolpert Order No. 072637
CONTRACTOR: Woolpert, Inc.
LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The LiDAR systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 1 meter. The final products include first, last, and at least one intermediate return LAS, full classified LAS and one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format.
Distribution Information
-
Create custom data files by choosing data area, product type, map projection, file format, datum, etc.
-
Simple download of data files.
None
None. However, 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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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 it's limitations.
Controlled Theme Keywords
elevation
Child Items
No Child Items for this record.
Contact Information
Point of Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Metadata Contact
NOAA Office for Coastal Management (NOAA/OCM)
coastal.info@noaa.gov
(843) 740-1202
https://coast.noaa.gov
Extents
-88.15461° W,
-87.603883° E,
46.25445° N,
45.710332° S
2012-11-15
2012-11-16
Item Identification
Title: | Dickinson County, MI LIDAR_LAS_1.2 |
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Short Name: | mi2012_usgs_dickinson_m4808_metadata |
Status: | Completed |
Publication Date: | 2015-02-09 |
Abstract: |
TASK NAME:(NRCS) Dickinson County, MI LIDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G12PD00721 Woolpert Order No. 072637 CONTRACTOR: Woolpert, Inc. LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The LiDAR systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 1 meter. The final products include first, last, and at least one intermediate return LAS, full classified LAS and one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. |
Purpose: |
This task order consisted of LiDAR data acquisition and processing for the USGS. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 1 meter. The LiDAR data was provided in 1,500 meters x 1,500 meters tiles in the UTM projection. The LiDAR tile file name was derived from the southwest corner of each tile. The tiles are named based on the US National Grid. |
Notes: |
10448 |
Supplemental Information: |
A report for this project is available at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/4808/supplemental/mi2012_usgs_dickinson_m4808_surveyreport.pdf A footprint of this data set may be viewed in Google Earth at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/4808/supplemental/mi2012_usgs_dickinson_m4808.kmz |
Keywords
Theme Keywords
Thesaurus | Keyword |
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ISO 19115 Topic Category |
elevation
|
UNCONTROLLED | |
None | Ground |
None | Terrain |
Physical Location
Organization: | Office for Coastal Management |
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City: | Charleston |
State/Province: | SC |
Data Set Information
Data Set Scope Code: | Data Set |
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Maintenance Frequency: | As Needed |
Data Presentation Form: | las |
Entity Attribute Overview: |
LAS 1.2 format (classes 1,2,7,8,9,10,17,18) |
Entity Attribute Detail Citation: |
none |
Distribution Liability: |
Any conclusions drawn from the analysis of this information are not the responsibility of Woolpert, USGS, NOAA, the Office for Coastal Management or its partners. |
Support Roles
Data Steward
Date Effective From: | 2015-02-09 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Distributor
Date Effective From: | 2015-02-09 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Metadata Contact
Date Effective From: | 2015-02-09 |
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Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Point of Contact
Date Effective From: | 2015-02-09 |
---|---|
Date Effective To: | |
Contact (Organization): | NOAA Office for Coastal Management (NOAA/OCM) |
Address: |
2234 South Hobson Ave Charleston, SC 29405-2413 |
Email Address: | coastal.info@noaa.gov |
Phone: | (843) 740-1202 |
URL: | https://coast.noaa.gov |
Extents
Currentness Reference: | Ground Condition |
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Extent Group 1
Extent Group 1 / Geographic Area 1
W° Bound: | -88.15461 | |
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E° Bound: | -87.603883 | |
N° Bound: | 46.25445 | |
S° Bound: | 45.710332 |
Extent Group 1 / Time Frame 1
Time Frame Type: | Discrete |
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Start: | 2012-11-15 |
Extent Group 1 / Time Frame 2
Time Frame Type: | Discrete |
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Start: | 2012-11-16 |
Spatial Information
Spatial Representation
Representations Used
Vector: | Yes |
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Access Information
Security Class: | Unclassified |
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Data Access Procedure: |
This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=4808 The data set is dynamically generated based on user-specified parameters.; |
Data Access Constraints: |
None |
Data Use Constraints: |
None. However, 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 it's limitations. |
Distribution Information
Distribution 1
Download URL: | https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=4808 |
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Distributor: | |
File Name: | Customized Download |
Description: |
Create custom data files by choosing data area, product type, map projection, file format, datum, etc. |
Distribution 2
Download URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/4808/index.html |
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Distributor: | |
File Name: | Bulk Download |
Description: |
Simple download of data files. |
URLs
URL 1
URL: | https://coast.noaa.gov/dataviewer |
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URL Type: |
Online Resource
|
URL 2
URL: | https://coast.noaa.gov |
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URL Type: |
Online Resource
|
URL 3
URL: | https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/4808/supplemental/mi2012_usgs_dickinson_m4808.kmz |
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Name: | Browse Graphic |
URL Type: |
Browse Graphic
|
File Resource Format: | kmz |
Description: |
This graphic shows the lidar coverage for the 2012 lidar project covering Dickinson County, MI. |
Activity Log
Activity Log 1
Activity Date/Time: | 2016-05-23 |
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Description: |
Date that the source FGDC record was last modified. |
Activity Log 2
Activity Date/Time: | 2017-11-14 |
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Description: |
Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using 'fgdc_to_inport_xml.pl' script. Contact Tyler Christensen (NOS) for details. |
Activity Log 3
Activity Date/Time: | 2018-02-08 |
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Description: |
Partial upload of Positional Accuracy fields only. |
Activity Log 4
Activity Date/Time: | 2018-03-13 |
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Description: |
Partial upload to move data access links to Distribution Info. |
Data Quality
Horizontal Positional Accuracy: |
Compiled to meet 0.432 meters horizontal accuracy at 95 percent confidence level. |
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Vertical Positional Accuracy: |
LAS data covering the Dickinson County 1.0 meter NPS Lidar Task Order was compared to survey control points to determine the FVA of the LAS Swath and of the Bare-Earth DEM. In addition, this LAS data was compared to supplemental points from categories: Bare Earth Open Terrain, Urban, Tall Weeds/Crops, Brush Lands and Trees, and Forested Fully Grown. Fundamental Vertical Accuracy (FVA) LAS Swath Fundamental Vertical Accuracy (FVA) Tested 0.098 meters fundamental vertical accuracy at a 95 percent confidence level, derived according to NSSDA, in open terrain using 0.0500 meters (RMSEz) x 1.96000. Tested against the TIN using independent check points. Bare-Earth DEM Fundamental Vertical Accuracy (FVA) Tested 0.097 meters fundamental vertical accuracy at a 95 percent confidence level, derived according to NSSDA, in open terrain using 0.0496 meters (RMSEz) x 1.96000. Tested against the DEM using independent check points. Supplemental Vertical Accuracy (SVA) Bare Earth/Open Terrain Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.099 meters supplemental vertical accuracy at the 95th percentile in Bare Earth/Open Terrain. Tested against the DEM. Urban Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.103 meters supplemental vertical accuracy at the 95th percentile in Urban. Tested against the DEM. Tall Weeds/Crops Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.187 meters supplemental vertical accuracy at the 95th percentile in Tall Weeds/Crops. Tested against the DEM. Brush Lands and Trees Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.176 meters supplemental vertical accuracy at the 95th percentile in Brush Lands and Trees. Tested against the DEM. Forested and Fully Grown Land Cover Classification Supplemental Vertical Accuracy (SVA) Tested 0.223 meters supplemental vertical accuracy at the 95th percentile in Forested and Fully Grown. Tested against the DEM. Consolidated Vertical Accuracy (CVA) Tested 0.144 meters consolidated vertical accuracy at the 95th percentile level, derived according to ASPRS Guidelines for Vertical Accuracy Reporting for LiDAR Data. Tested against the DEM. Based on the 95th percentile error in all land cover categories combined. |
Completeness Report: |
The LiDAR data is visually inspected for completeness to ensure that are no gaps between flight lines. |
Conceptual Consistency: |
All formatted data are validated using commercial GIS software to ensure proper formatting and loading prior to delivery. |
Lineage
Process Steps
Process Step 1
Description: |
Using Leica ALS70 (LiDAR) system 36 flight lines of high density data, at a nominal pulse spacing (NPS) of 1 meter, were collected for the Dickinson county, Michigan (approximately 776 square miles). Data Acquisition Height = 7,800 feet AGL - Aircraft Speed = 150 Knots. Multiple returns were recorded for each laser pulse along with an intensity value for each return. A total of two (2) missions were flown on November 15, 2012 and November 16, 2012. A single airborne Global Navigation Satellite System (GNSS) Base Station was used in support of the LiDAR data acquisition. 26 ground control points were surveyed through static methods. The geoid used to reduce satellite derived elevations to orthometric heights was GEOID12a. Data for the task order is referenced to the UTM Zone 16N, North American Datum of 1983 (NAD83), and NAVD88, in Meters. Airborne GPS data was differentially processed and integrated with the post processed IMU data to derive a smoothed best estimate of trajectory (SBET). The SBET was used to reduce the LiDAR slant range measurements to a raw reflective surface for each flight line. The coverage was classified to extract a bare earth digital elevation model (DEM) and separate last returns. In addition to the LAS deliverables, one layer of coverage was delivered in the IMG Format: bare-earth. |
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Process Date/Time: | 2012-11-15 00:00:00 |
Process Step 2
Description: |
The ALS70 calibration and system performance is verified on a periodic basis using Woolpert's calibration range. The calibration range consists of a large building and runway. The edges of the building and control points along the runway have been located using conventional survey methods. Inertial measurement unit (IMU) misalignment angles and horizontal accuracy are calculated by comparing the position of the building edges between opposing flight lines. The scanner scale factor and vertical accuracy is calculated through comparison of LiDAR data against control points along the runway. Field calibration is performed on all flight lines to refine the IMU misalignment angles. IMU misalignment angles are calculated from the relative displacement of features within the overlap region of adjacent (and opposing) flight lines. The raw LiDAR data is reduced using the refined misalignment angles. |
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Process Date/Time: | 2012-01-01 00:00:00 |
Process Step 3
Description: |
Once the data acquisition and GPS processing phases are complete, the LiDAR data was processed immediately to verify the coverage had no voids. The GPS and IMU data was post processed using differential and Kalman filter algorithms to derive a best estimate of trajectory. The quality of the solution was verified to be consistent with the accuracy requirements of the project. |
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Process Date/Time: | 2012-11-20 00:00:00 |
Process Step 4
Description: |
The individual flight lines were inspected to ensure the systematic and residual errors have been identified and removed. Then, the flight lines were compared to adjacent flight lines for any mismatches to obtain a homogenous coverage throughout the project area. The point cloud underwent a classification process to determine bare-earth points and non-ground points utilizing "first and only" as well as "last of many" LiDAR returns. This process determined Default (Class 1), Ground (Class 2), Noise (Class 7), Model Key Point (Class 8), Water (Class 9) Ignored Ground (Class 10), Overlap Default (Class 17) and Overlap Ground (Class 18). The bare-earth (Class 2 - Ground) LiDAR points underwent a manual QA/QC step to verify that artifacts have been removed from the bare-earth surface. The surveyed ground control points are used to perform the accuracy checks and statistical analysis of the LiDAR dataset. |
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Process Date/Time: | 2012-11-20 00:00:00 |
Process Step 5
Description: |
The NOAA Office for Coastal Management (OCM) received the files in laz format from USGS via an FTP online repository. The files contained lidar elevation and intensity measurements. The data were in UTM Zone 16, NAVD88 (orthometric) heights in meters. OCM performed the following processing for data storage and Digital Coast provisioning purposes: 1. The data were converted from UTM coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights in meters to GRS80 (ellipsoid) heights in meters using Geoid 12a. 3. The LAS data were sorted by latitude and the headers were updated. 4. Erroneous elevations were removed. |
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Process Date/Time: | 2015-01-18 00:00:00 |
Catalog Details
Catalog Item ID: | 49803 |
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GUID: | gov.noaa.nmfs.inport:49803 |
Metadata Record Created By: | Anne Ball |
Metadata Record Created: | 2017-11-15 15:22+0000 |
Metadata Record Last Modified By: | SysAdmin InPortAdmin |
Metadata Record Last Modified: | 2022-08-09 17:11+0000 |
Metadata Record Published: | 2022-03-16 |
Owner Org: | OCMP |
Metadata Publication Status: | Published Externally |
Do Not Publish?: | N |
Metadata Last Review Date: | 2022-03-16 |
Metadata Review Frequency: | 1 Year |
Metadata Next Review Date: | 2023-03-16 |