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Short Citation:
OCM Partners, 2023: 2014 Baltimore County Lidar, https://www.fisheries.noaa.gov/inport/item/51983.

Item Identification

Title: 2014 Baltimore County Lidar
Status: Completed
Publication Date: 2015-04
Abstract:

Aerial Cartographics of America (ACA) collected 750 square miles covering Baltimore County. The nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground, 7-Low Noise, 9-Water, 10-Ignored Ground due to breakline proximity. Dewberry produced 3D breaklines and combined these with the final LiDAR data to produce seamless hydro-conditioned DEMs for the project area. The data was formatted according to the Baltimore County tile naming convention.

Purpose:

The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.2 format, 3D breaklines, and 1 meter cell size hydroconditioned Digital Elevation Models (DEMs). All products follow and comply with Baltimore County Lidar specifications

Supplemental Information:

A complete description of this dataset is available in the Final Project Report that was submitted to Baltimore County

Keywords

Theme Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION
ISO 19115 Topic Category
elevation
UNCONTROLLED
None beach
None Contours
None erosion

Spatial Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Location Keywords
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > MARYLAND
Global Change Master Directory (GCMD) Location Keywords
VERTICAL LOCATION > LAND SURFACE

Instrument Keywords

Thesaurus Keyword
UNCONTROLLED
Global Change Master Directory (GCMD) Instrument Keywords Earth Remote Sensing Instruments > Active Remote Sensing > Profilers/Sounders > Lidar/Laser Sounders > LIDAR > Light Detection and Ranging

Platform Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Platform Keywords
Airplane > Airplane

Physical Location

Organization: Office for Coastal Management
City: Charleston
State/Province: SC

Data Set Information

Data Set Scope Code: Data Set
Data Set Type: Elevation
Maintenance Frequency: As Needed
Data Presentation Form: Elevation Data
Entity Attribute Detail Citation:

none

Distribution Liability:

This data was produced for Baltimore County according to specific project requirements. This information is provided "as is".

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

Data Set Credit: Baltimore County Office of Information Technology

Support Roles

Data Steward

CC ID: 739452
Date Effective From: 2018
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

CC ID: 739453
Date Effective From: 2018
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

CC ID: 739454
Date Effective From: 2018
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

CC ID: 739455
Date Effective From: 2018
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

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 1140906
W° Bound: -76.914808
E° Bound: -76.33876
N° Bound: 39.722331
S° Bound: 39.193934

Extent Group 1 / Time Frame 1

CC ID: 1140905
Time Frame Type: Range
Start: 2014-05-06
End: 2014-05-07

Spatial Information

Spatial Resolution

Horizontal Distance: 0.7 Meter

Spatial Representation

Representations Used

Vector: Yes

Access Information

Security Class: Unclassified
Data Access Procedure:

Data is available online for custom downloads

Data Access Constraints:

None

Data Use Constraints:

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.

Distribution Information

Distribution 1

CC ID: 739458
Start Date: 2018
End Date: Present
Download URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8492
Distributor: NOAA Office for Coastal Management (NOAA/OCM) (2018 - Present)
File Name: Customized Download
Description:

Create custom data files by choosing data area, product type, map projection, file format, datum, etc.

File Type: Zip
Compression: Zip

Distribution 2

CC ID: 739459
Start Date: 2018
End Date: Present
Download URL: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8492/index.html
Distributor: NOAA Office for Coastal Management (NOAA/OCM) (2018 - Present)
File Name: Bulk Download
Description:

Bulk download of data files in LAZ format, geographic coordinates, orthometric heights.

File Type: LAZ

URLs

URL 1

CC ID: 739447
URL: https://coast.noaa.gov/
Name: NOAA's Office for Coastal Management (OCM) website
URL Type:
Online Resource
File Resource Format: HTML
Description:

Information on the NOAA Office for Coastal Management (OCM)

URL 2

CC ID: 739448
URL: https://coast.noaa.gov/dataviewer/#/
Name: NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV)
URL Type:
Online Resource
File Resource Format: HTML
Description:

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.

URL 3

CC ID: 739449
URL: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8492/supplemental/2015_Baltimore_county_area.kmz
Name: Browse graphic
URL Type:
Browse Graphic
File Resource Format: KML
Description:

This graphic displays the footprint for this lidar data set.

URL 4

CC ID: 739792
URL: https://imap.Maryland.gov
Name: Maryland iMAP
URL Type:
Online Resource
Description:

Original source for the point clouds.

Technical Environment

Description:

Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog 10.1

Data Quality

Horizontal Positional Accuracy:

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. Qualitative value: 66 cm, Test that produced the valued: 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.

Dewberry tested the horizontal accuracy of the LiDAR by comparing photo-identifiable survey checkpoints to the LiDAR Intensity Imagery. As only thirteen (13) checkpoints were photo-identifiable, the results are not statistically significant enough to report as a final tested value but the results of this testing are shown below.

Using NSSDA methodology (endorsed by the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014)), horizontal accuracy at the 95% confidence level (called ACCURACYr) is computed by the formula RMSEr * 1.7308 or RMSExy * 2.448. Actual positional accuracy of this dataset was found to be RMSEx = 27 cm and RMSEy = 27 cm which equates to +/- 66 cm at 95% confidence level.

Vertical Positional Accuracy:

The vertical accuracy of the source LiDAR and final bare earth DEMs was tested by Dewberry with 104 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain, and urban terrain (41), and vegetated terrain, including forest, brush, tall weeds, crops, and high grass (63). The vertical accuracy of the LiDAR is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the LiDAR ground points. Checkpoints are always compared to interpolated surfaces created from the LiDAR point cloud because it is unlikely that a survey checkpoint will be located at the location of a discrete LiDAR point. The vertical accuracy of the final bare earth DEMs is tested by extracting the elevation of the pixel that contains the x/y coordinates of the checkpoint and comparing these DEM elevations to the surveyed elevations. Accuracy results may vary between the source LiDAR and final DEM deliverable. DEMs are created by averaging several LiDAR points within each pixel which may result in slightly different elevation values at each survey checkpoint when compared to the source LAS, which is tested by comparing survey checkpoints to TINs. TINs do not average several LiDAR points together but interpolate (linearly) between two or three points to derive an elevation value. The accuracy results reported for the overall project are the accuracy results of the source LiDAR. Bare earth DEM accuracy results are reported in the DEM metadata file.

All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications required a NVA of 19.6 cm at the 95% confidence level based on RMSEz (10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications required a VVA of 30 cm based on the 95th percentile.Qualitative value:13.3 cm 19.0 cm, Test that produced the value: The following result is from testing the source LiDAR data. DEM accuracy results are in the DEM metadata file.

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 =6.79 cm, equating to +/- 13.3 cm at 95% confidence level. The following result is from testing the source LiDAR data. DEM accuracy results are in the DEM metadata file.

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 VVA accuracy was found to be +/- 19.0 cm at the 95th percentile.

The 5% outliers consisted of 6 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 19.2 cm and 23.7 cm.

Completeness Report:

A visual qualitative assessment was performed to ensure data completeness and bare earth data cleanliness. No void or missing data and data passes vertical accuracy specifications.

Conceptual Consistency:

Data covers the tile scheme provided for the project area.

Lineage

Sources

Maryland iMAP data

CC ID: 1158071
Contact Role Type: Publisher
Contact Type: Organization
Contact Name: Maryland iMAP
Citation URL: https://imap.maryland.gov
Citation URL Name: maryland imap

Process Steps

Process Step 1

CC ID: 1140901
Description:

Data for the Baltimore County Lidar project was acquired by Aerial Cartogrpahics of America (ACA).

The project area included approximately 750 contiguous square miles covering baltimore county. LiDAR sensor data were collected with the Reigle 680i. The data was delivered in Maryland State Plane Corrdinate System, US Feet, horizontal datum NAD83, vertical datum NAVD88, Geoid 09. Deliverables for the project included a raw (unclassified) calibrated LiDAR point cloud, hydroconditioned DEMs, DSMs, intensity imagery, and breakline data.

The calibration process considered all errors inherent with the equipment including errors in GPS, IMU, and sensor specific parameters. Adjustments were made to achieve a flight line to flight line data match (relative calibration) and subsequently adjusted to control for absolute accuracy. Process steps to achieve this are as follows:

Rigorous LiDAR calibration: all sources of error such as the sensor's ranging and torsion parameters, atmospheric variables, GPS conditions, and IMU offsets were analyzed and removed to the highest level possible. This method addresses all errors, both vertical and horizontal in nature. Ranging, atmospheric variables, and GPS conditions affect the vertical position of the surface, whereas IMU offsets and torsion parameters affect the data horizontally. The horizontal accuracy is proven through repeatability: when the position of features remains constant no matter what direction the plane was flying and no matter where the feature is positioned within the swath, relative horizontal accuracy is achieved.

Absolute horizontal accuracy is achieved through the use of differential GPS with base lines shorter than 25 miles. The base station is set at a temporary monument that is 'tied-in' to the CORS network. The same position is used for every lift, ensuring that any errors in its position will affect all data equally and can therefore be removed equally.

Vertical accuracy is achieved through the adjustment to ground control survey points within the finished product. Although the base station has absolute vertical accuracy, adjustments to sensor parameters introduces vertical error that must be normalized in the final (mean) adjustment.

Process Step 2

CC ID: 1140902
Description:

Dewberry utilizes a variety of software suites for inventory management, classification, and data processing. All LiDAR related processes begin by importing the data into the GeoCue task management software. The swath data is tiled according to project specifications. The tiled data is then opened in Terrascan where Dewberry classifies edge of flight line points that may be geometrically unusable to a separate class. These points are separated from the main point cloud so that they are not used in the ground algorithms. Dewberry then uses proprietary ground classification routines to remove any non-ground points and generate an accurate ground surface. The ground routine consists of three main parameters (building size, iteration angle, and iteration distance); by adjusting these parameters and running several iterations of this routine an initial ground surface is developed. The building size parameter sets a roaming window size. Each tile is loaded with neighboring points from adjacent tiles and the routine classifies the data section by section based on this roaming window size. The second most important parameter is the maximum terrain angle, which sets the highest allowed terrain angle within the model. As part of the ground routine, low noise points are classified to class 7. Once the ground routine has been completed, bridge decks are classified to class 17 using bridge breaklines compiled by Dewberry. A manual quality control routine is then performed using hillshades, cross-sections, and profiles within the Terrasolid software suite. After this QC step, a peer review is performed on all tiles and a supervisor manual inspection is completed on a percentage of the classified tiles based on the project size and variability of the terrain. After the ground classification and bridge deck corrections are completed, the dataset is processed through a water classification routine that utilizes breaklines compiled by Dewberry to automatically classify hydrographic features. The water classification routine selects ground points within the breakline polygons and automatically classifies them as class 9, water. During this water classification routine, points that are within 1x NPS or less of the hydrographic features are moved to class 10, an ignored ground due to breakline proximity. Overage points are then identified in Terrascan and GeoCue is used to set the overlap bit for the overage points and the withheld bit is set on the withheld points previously identified in Terrascan before the ground classification routine was performed. A final QC is performed on the data. T

The data was classified as follows:

Class 1 = Unclassified. This class includes vegetation, buildings, noise etc.

Class 2 = Ground

Class 7= Low Noise

Class 9 = Water

Class 10 = Ignored Ground due to breakline proximity

The LAS header information was verified to contain the following:

Class (Integer)

Adjusted GPS Time (0.0001 seconds)

Easting (0.003 m)

Northing (0.003 m)

Elevation (0.003 m)

Echo Number (Integer)

Echo (Integer)

Intensity (16 bit integer)

Flight Line (Integer)

Scan Angle (degree)

Process Date/Time: 2014-08-01 00:00:00

Process Step 3

CC ID: 1140903
Description:

NOAA OCM downloaded the point cloud data from the Maryland iMAP (imap.maryland.gov) in October, 2017.

Data were reprojected to geographic coordinates and vertically transformed to ellipsoid heights in meters using the Geoid12a model for ingest into the Digital Coast Data Access Viewer.

Classifications were found to not completely agree with the descriptions in steps 1 and 2 above. Only classes 1,2,7,9, and 17 are in the data set.

The data set is listed on the iMAP site as 2015, but the collection was in 2014 according to the original metadata and the time stamps in the point cloud.

Process Date/Time: 2018-03-09 00:00:00
Process Contact: Office for Coastal Management (OCM)
Source: Maryland iMAP data

FAQs

FAQ 1

CC ID: 739773
Date: 2018-03-09 00:00:00
Author: Kirk Waters
Question:

What are the USGS lidar fields for this dataset?

Answer:

"lidar" : {

"ldrinfo" : {

"ldrspec" : "Baltimore County Lidar Specifications",

"ldrsens" : "Riegl 680i",

"ldrmaxnr" : "7",

"ldrnps" : "0.67",

"ldrdens" : "2.2",

"ldranps" : "0.67",

"ldradens" : "2.2",

"ldrfltht" : "1000",

"ldrfltsp" : "100",

"ldrscana" : "60",

"ldrscanr" : "76",

"ldrpulsr" : "200",

"ldrpulsd" : "10",

"ldrpulsw" : "3",

"ldrwavel" : "1064",

"ldrmpia" : "0",

"ldrbmdiv" : "0.5",

"ldrswatw" : "1155",

"ldrswato" : "50",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12A"

},

"ldraccur" : {

"ldrchacc" : "0.1813",

"rawnva" : "0.175",

"rawnvan" : "20",

"clsnva" : "0.133",

"clsnvan" : "20",

"clsvva" : "0.190",

"clsvvan" : "60"

},

"lasinfo" : {

"lasver" : "1.2",

"lasprf" : "1",

"laswheld" : "Withheld points were identified in these files using the standard LAS Withheld bit",

"lasintr" : "16",

"lasclass" : {

"clascode" : "0",

"clasitem" : "Calibrated, never classified"

},

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed, but unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth, ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

"clasitem" : "Ignored ground due to breakline proximity"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High noise"

}

}

}}

Catalog Details

Catalog Item ID: 51983
GUID: gov.noaa.nmfs.inport:51983
Metadata Record Created By: Kirk Waters
Metadata Record Created: 2018-03-08 15:32+0000
Metadata Record Last Modified By: SysAdmin InPortAdmin
Metadata Record Last Modified: 2023-02-21 18:41+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