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Short Citation:
OCM Partners, 2023: 2008 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Camp Creek,

Item Identification

Title: 2008 Oregon Department of Geology and Mineral Industries (DOGAMI) Lidar: Camp Creek
Short Name: or2008_dogami_camp_creek_m1159_metadata
Status: Completed
Publication Date: 2012-02

The Oregon Department of Geology & Mineral Industries (DOGAMI) contracted with Watershed Sciences, Inc. to collect high

resolution topographic lidar data for multiple areas within the State of Oregon. The areas for lidar collection have been designed

as part of a collaborative effort of state, federal, and local agencies in order to meet a wide range of project goals.

The Camp Creek study area was collected August 19 - 27, 2008 and covers a portion of eastern Grant County. The total

flown area covers 320 square miles, or 205,250 acres. This data set consists of bare earth and unclassified points. There

are approximately 8 points per square meter over terrestrial surfaces. In some areas of heavy vegetation or forest cover,

there may be relatively few ground points in the lidar data. Elevation values for open water surfaces are not valid elevation

values because few lidar points are returned from water surfaces. Lidar intensity values were also collected.

Original contact information:

Contact Name: Ian Madin

Contact Org: DOGAMI

Phone: 971-673-1542



Provide high resolution terrain elevation and land cover elevation data.



Supplemental Information:

The Watershed Sciences Lidar Remote Sensing Data Collection Report for Camp Creek may be accessed at:

A footprint of this data set may be viewed in Google Earth at:


Theme Keywords

Thesaurus Keyword
ISO 19115 Topic Category
None Bare earth
None Bare ground
None High-resolution
None Light Detection and Ranging

Physical Location

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

Data Set Information

Data Set Scope Code: Data Set
Maintenance Frequency: None Planned
Distribution Liability:

Any conclusions drawn from the analysis of this information are not the responsibility of the Oregon

Department of Geology and Mineral Industries (DOGAMI), the Office for Coastal Management or its partners.

Data Set Credit: DOGAMI

Support Roles

Data Steward

CC ID: 682552
Date Effective From: 2012-02
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address:
Phone: (843) 740-1202


CC ID: 682554
Date Effective From: 2012-02
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address:
Phone: (843) 740-1202

Metadata Contact

CC ID: 682555
Date Effective From: 2012-02
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address:
Phone: (843) 740-1202

Point of Contact

CC ID: 682553
Date Effective From: 2012-02
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address:
Phone: (843) 740-1202


Currentness Reference: Ground Condition

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 1132773
W° Bound: -118.913404
E° Bound: -118.305533
N° Bound: 44.75846
S° Bound: 44.44149

Extent Group 1 / Time Frame 1

CC ID: 1132772
Time Frame Type: Range
Start: 2008-08-19
End: 2008-08-27

Spatial Information

Spatial Representation

Representations Used

Vector: Yes

Access Information

Security Class: Unclassified
Data Access Procedure:

This data can be obtained on-line at the following URL:

This data set is dynamically generated based on user-specified parameters.


Data Access Constraints:


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


Distribution Information

Distribution 1

CC ID: 741980
Download URL:
File Name: Customized Download

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

Distribution 2

CC ID: 741981
Download URL:
File Name: Bulk Download

Simple download of data files.



CC ID: 741983
URL Type:
Online Resource


CC ID: 741984
URL Type:
Online Resource


CC ID: 741985
Name: Browse Graphic
URL Type:
Browse Graphic
File Resource Format: kmz

This graphic shows the lidar coverage for the Camp Creek data set.

Activity Log

Activity Log 1

CC ID: 682576
Activity Date/Time: 2016-05-23

Date that the source FGDC record was last modified.

Activity Log 2

CC ID: 682575
Activity Date/Time: 2017-11-14

Converted from FGDC Content Standards for Digital Geospatial Metadata (version FGDC-STD-001-1998) using '' script. Contact Tyler Christensen (NOS) for details.

Activity Log 3

CC ID: 718482
Activity Date/Time: 2018-02-08

Partial upload of Positional Accuracy fields only.

Activity Log 4

CC ID: 741982
Activity Date/Time: 2018-03-13

Partial upload to move data access links to Distribution Info.

Technical Environment


Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog

Data Quality

Horizontal Positional Accuracy:

Horizontal accuracies were not specified in the agreement since true horizontal accuracy is regarded as a product of the LiDAR ground

foot print. LiDAR is referenced to co-acquired GPS base station data that has accuracies far greater than the value of the LiDAR

foot print. The ground footprint is equal to 1/3333rd of above ground flying height. Survey altitude for this acquisition was targeted

at 900 meters yielding a ground foot print of 0.27 meters. This value exceeds the typical accuracy value of ground control used to

reference the LiDAR data (less than 0.01 m). Project specifications required the LiDAR foot print to fall within 0.15 and 0.40 meters.

Vertical Positional Accuracy:

Based on 1452 RTK points, the absolute vertical accuracy for this data set is 4.57 cm (0.15 ft) RMSE (Root Mean Square Error).

Completeness Report:

LiDAR data has been collected and processed for all areas within the project study area.

Conceptual Consistency:

Upon receipt from vendor (Watershed Sciences), all LiDAR data was independently reviewed by staff from the Oregon Department of

Geology and Mineral Industries (DOGAMI) to ensure project specifications were met. All data were inventoried for completeness

and data were checked for quality, which included examining LiDAR data for errors associated with internal data consistency,

model quality, and accuracy.


Process Steps

Process Step 1

CC ID: 1132768

The LiDAR data was collected between August 19, 2008 and August 27, 2008. The survey used a Leica ALS50 Phase II laser system

mounted in a Cessna Caravan 208B. The system was set to acquire greater than or equal to 105,000 laser pulses per

second (i.e. 105 kHz pulse rate) and flown at 900 meters above ground level (AGL), capturing a scan angle of plus or minus

14 degrees from nadir. These settings were developed to yield points with an average native density of greater than or

equal to 8 points per square meter over terrestrial surfaces. The native pulse density is the number of pulses emitted

by the LiDAR system. Some types of surfaces (i.e. dense vegetation or water) may return fewer pulses than the laser

originally emitted. Therefore, the delivered density can be less than the native density and lightly variable according

to distributions of terrain, land cover, and water bodies. The completed areas were surveyed with opposing flight

line side-lap of greater than or equal to 50% (greater than or equal to 100% overlap) to reduce laser shadowing and increase

surface laser painting. The system allows up to four range measurements per pulse, and all discernible laser returns were

processed for the output dataset.

During the LiDAR survey of the study area, a static (1 Hz recording frequency) ground survey was conducted over monuments

with known coordinates. After the airborne survey, the static GPS data were processed using triangulation with CORS

stations checked against the Online Positioning User Service (OPUS) to quantify daily variance. Multiple sessions

are processed over the same monument to confirm the antenna height measurements and reported position accuracy.

Multiple DGPS units are used for the ground real-time kinematic (RTK) portion of the survey. To collect accurate ground

surveyed points, a GPS base unit is set up over monuments to broadcast a kinematic correction to a roving GPS unit. The

ground crew uses a roving unit to receive radio-relayed kinematic corrected positions from the base unit. This method is

referred to as real-time kinematic (RTK) surveying and allows precise location measurement (sigma less than or equal to 1.5 cm (0.6 in)).

For the Camp Creek study area, 1452 RTK points were collected across 41 of the 243 flightlines, resulting in 17 percent of

all flight lines being intersected by RTK survey points.

Process Date/Time: 2008-01-01 00:00:00

Process Step 2

CC ID: 1132769

1. Laser point coordinates are computed using the IPAS and ALS Post Processor software suites based on independent data from the

LiDAR system (pulse time, scan angle), and aircraft trajectory data (SBET). Laser point returns (first through fourth) are assigned

an associated (x, y, z) coordinate along with unique intensity values (0-255). The data are output into large LAS v. 1.1 files;

each point maintains the corresponding scan angle, return number (echo), intensity, and x, y, z (easting, northing, and elevation)


2. These initial laser point files are too large to process. To facilitate laser point processing, bins (polygons) are created to divide

the dataset into manageable sizes (less than 500 MB). Flightlines and LiDAR data are then reviewed to ensure complete coverage of the study area

and positional accuracy of the laser points.

3. Once the laser point data are imported into bins in TerraScan, a manual calibration is performed to assess the system offsets for pitch,

roll, heading, and mirror scale. Using a geometric relationship developed by Watershed Sciences, each of these offsets is resolved and

corrected if necessary.

4. The LiDAR points are then filtered for noise, pits, and birds by screening for absolute elevation limits, isolated points, and height

above ground. Each bin is then inspected for pits and birds manually; spurious points are removed. For a bin containing approximately

7.5-9.0 million points, an average of 50-100 points are typically found to be artificially low or high. These spurious non-terrestrial

laser points must be removed from the dataset. Common sources of non-terrestrial returns are clouds, birds, vapor, and haze.

5. The internal calibration is refined using TerraMatch. Points from overlapping lines are tested for internal consistency and final

adjustments are made for system misalignments (i.e., pitch, roll, heading offsets and mirror scale). Automated sensor attitude and

scale corrections yield 3-5 cm improvements in the relative accuracy. Once the system misalignments are corrected, vertical GPS drift

is then resolved and removed per flight line, yielding a slight improvement (less than 1 cm) in relative accuracy. At this point in the workflow,

data have passed a robust calibration designed to reduce inconsistencies from multiple sources (i.e. sensor attitude offsets,

mirror scale, GPS drift) using a procedure that is comprehensive (i.e. uses all of the overlapping survey data). Relative accuracy

screening was complete.

6. The TerraScan software suite is designed specifically for classifying near-ground points (Soininen, 2004). The processing sequence

begins by removing all points that are not near the earth based on geometric constraints used to evaluate multi-return points.

The resulting bare earth (ground) model is visually inspected and additional ground point modeling is performed in site-specific areas

(over a 50-meter radius) to improve ground detail. This is only done in areas with known ground modeling deficiencies,

such as: bedrock outcrops, cliffs, deeply incised stream banks, and dense vegetation. In some cases, ground point classification

includes known vegetation (i.e., understory, low/dense shrubs, etc.) and these points are manually reclassified as non-grounds.

Ground surface rasters were developed from triangulated irregular networks (TINs) of ground points.

Process Date/Time: 2008-01-01 00:00:00

Process Step 3

CC ID: 1132770

The NOAA Office for Coastal Management (OCM) received the files in las format. The files contained LiDAR

elevation and intensity measurements. The data were in Oregon Lambert (NAD83), International Feet projection

and NAVD88 (Geoid 03) vertical datum. OCM performed the following processing for data storage and Digital Coast

provisioning purposes:

1. The data were converted from Oregon Lambert (NAD83), International Feet to geographic coordinates.

2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid 03.

3. The vertical units of the data were converted from International feet to meters.

4. The data were sorted by latitude and the headers were updated.

Process Date/Time: 2012-02-01 00:00:00

Catalog Details

Catalog Item ID: 49901
GUID: gov.noaa.nmfs.inport:49901
Metadata Record Created By: Anne Ball
Metadata Record Created: 2017-11-15 15:23+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