Data Management Plan
GUID: gov.noaa.nmfs.inport:49918 | Published / External
Data Management Plan
DMP Template v2.0.1 (2015-01-01)Please provide the following information, and submit to the NOAA DM Plan Repository.
Reference to Master DM Plan (if applicable)
As stated in Section IV, Requirement 1.3, DM Plans may be hierarchical. If this DM Plan inherits provisions from a higher-level DM Plan already submitted to the Repository, then this more-specific Plan only needs to provide information that differs from what was provided in the Master DM Plan.
1. General Description of Data to be Managed
Metadata for the LAS files was not provided to NOAA OCM. This metadata record contains information derived from the Watershed
Sciences, Inc. lidar report. This report may be accessed at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/1475/supplemental/GlassButtes.pdf
This LiDAR data set was collected between May 8 and May 14, 2010 and falls in portions of Deschutes, Harney, and Lake
counties in the Glass Buttes area of Oregon. The total pulse density is 9.26 pulses per square meter over terrestrial surfaces.
The requested lidar area of interest (AOI) totaled 84,849 acres, but was buffered to ensure data coverage, resulting in a total
area flown (TAF) of 86,631 acres.
This data set consists of ground (bare earth) and unclassified points.
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
Notes: Only a maximum of 4000 characters will be included.
Notes: Data collection is considered ongoing if a time frame of type "Continuous" exists.
Notes: All time frames from all extent groups are included.
Notes: All geographic areas from all extent groups are included.
(e.g., digital numeric data, imagery, photographs, video, audio, database, tabular data, etc.)
(e.g., satellite, airplane, unmanned aerial system, radar, weather station, moored buoy, research vessel, autonomous underwater vehicle, animal tagging, manual surveys, enforcement activities, numerical model, etc.)
2. Point of Contact for this Data Management Plan (author or maintainer)
Notes: The name of the Person of the most recent Support Role of type "Metadata Contact" is used. The support role must be in effect.
Notes: The name of the Organization of the most recent Support Role of type "Metadata Contact" is used. This field is required if applicable.
3. Responsible Party for Data Management
Program Managers, or their designee, shall be responsible for assuring the proper management of the data produced by their Program. Please indicate the responsible party below.
Notes: The name of the Person of the most recent Support Role of type "Data Steward" is used. The support role must be in effect.
Programs must identify resources within their own budget for managing the data they produce.
5. Data Lineage and Quality
NOAA has issued Information Quality Guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of information which it disseminates.
(describe or provide URL of description):
- 2010-01-01 00:00:00 - No metadata for the lidar point data was provided to NOAA OCM with this data set. The following process step contains information derived from the Ormat Technologies lidar report. This lidar report may be accessed at: https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/1475/supplemental/GlassButtes.pdf Acquisition Ground Survey - Instrumentation and Methods During the LiDAR survey, static (1 Hz recording frequency) ground surveys were conducted over monuments with known coordinates. After the airborne survey, the static GPS data were processed using triangulation with CORS stations and checked against the Online Positioning User Service (OPUS2) to quantify daily variance. Multiple sessions were processed over each monument to confirm antenna height measurements and reported position accuracy. Multiple differential GPS units were used in the ground based real-time kinematic (RTK) portion of the survey. To collect accurate ground surveyed points, a GPS base unit was set up over monuments to broadcast a kinematic correction to a roving GPS unit. The ground crew used a roving unit to receive radio-relayed kinematic corrected positions from the base unit. This RTK survey allowed precise location measurement (sigma less than or equal to 1.5 cm). Lidar Point Data The lidar data were collected between May 8 and May 14, 2010. The LiDAR survey utilized a Leica ALS60 sensor mounted in a Cessna Caravan 208B. The Leica ALS60 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 14 degrees from nadir. These settings are developed to yield points with an average native pulse density of greater than or equal to 8 points per square meter over terrestrial surfaces. 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 vary according to distributions of terrain, land cover, and water bodies. The area of interest was surveyed with opposing flight line side-lap of greater than or equal to 50 percent (greater than or equal to 100 percent 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. To solve for laser point position, an accurate description of aircraft position and attitude is vital. Aircraft position is described as x, y, and z and measured twice per second (2 Hz) by an onboard differential GPS unit. Aircraft attitude was measured 200 times per second (200 Hz) as pitch, roll, and yaw (heading) from an onboard inertial measurement unit (IMU). Processing Aircraft Kinematic GPS and IMU Data LiDAR survey datasets were referenced to 1 Hz static ground GPS data collected over a pre-surveyed monument with known coordinates. While surveying, the aircraft collected 2 Hz kinematic GPS data and the inertial measurement unit (IMU) collected 200 Hz attitude data. Waypoint GraphNav v.8.10 was used to process the kinematic corrections for the aircraft. The static and kinematic GPS data were then post-processed after the survey to obtain an accurate GPS solution and aircraft positions. IPAS Pro v.1.3 was used to develop a trajectory file including corrected aircraft position and attitude information. The trajectory data for the entire flight survey session were incorporated into a final smoothed best estimated trajectory (SBET) file containing accurate and continuous aircraft positions and attitudes.
- 2010-01-01 00:00:00 - Lidar Point Data Laser point coordinates were 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) were assigned an associated (x, y, and z) coordinate along with unique intensity values (0-255). The data were output into large LAS v. 1.2 files; each point maintaining the corresponding scan angle, return number (echo), intensity, and x, y, and z (easting, northing, and elevation) information. Flightlines and LiDAR data were then reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. Once the laser point data were imported into TerraScan, a manual calibration was 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 was resolved and corrected if necessary. The LiDAR points were then filtered for noise, pits and birds by screening for absolute elevation limits, isolated points and height above ground. The data were then inspected for pits and birds manually, and spurious points were removed. For a .las file containing approximately 7.5-9.0 million points, an average of 50-100 points were 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. Internal calibration was refined using TerraMatch. Points from overlapping lines were tested for internal consistency and final adjustments made for system misalignments (i.e., pitch, roll, heading offsets and mirror scale). Automated sensor attitude and scale corrections yielded 3-5 cm improvements in the relative accuracy. Once the system misalignments were corrected, vertical GPS drift was resolved and removed per flight line, yielding a slight improvement (<1 cm) in relative accuracy. In summary, the data must complete a robust calibration designed to reduce inconsistencies from multiple sources (i.e., sensor attitude offsets, mirror scale, GPS drift). 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 are developed from triangulated irregular networks (TINs) of ground points.
- 2013-02-01 00:00:00 - 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 UTM Zone 11 (NAD83) coordinates and NAVD88 (Geoid03) vertical datum. OCM performed the following processing for data storage and Digital Coast provisioning purposes: 1. The data were converted from UTM Zone 11 (NAD83) coordinates to geographic coordinates. 2. The data were converted from NAVD88 (orthometric) heights to GRS80 (ellipsoid) heights using Geoid03. 3. The data were sorted by time and zipped to laz format. 4. The metadata was updated in 2014 to reflect DOGAMI as an originator and the title of the project was also altered to reflect the association with existing DOGAMI projects. All acknowledgements for Ormat Technologies remain the same.
(describe or provide URL of description):
6. Data Documentation
The EDMC Data Documentation Procedural Directive requires that NOAA data be well documented, specifies the use of ISO 19115 and related standards for documentation of new data, and provides links to resources and tools for metadata creation and validation.
- 1.6. Type(s) of data
- 1.7. Data collection method(s)
- 3.1. Responsible Party for Data Management
- 4.1. Have resources for management of these data been identified?
- 4.2. Approximate percentage of the budget for these data devoted to data management
- 5.2. Quality control procedures employed
- 7.1. Do these data comply with the Data Access directive?
- 7.1.1. If data are not available or has limitations, has a Waiver been filed?
- 7.1.2. If there are limitations to data access, describe how data are protected
- 7.4. Approximate delay between data collection and dissemination
- 8.1. Actual or planned long-term data archive location
- 8.3. Approximate delay between data collection and submission to an archive facility
- 8.4. How will the data be protected from accidental or malicious modification or deletion prior to receipt by the archive?
(describe or provide URL of description):
7. Data Access
NAO 212-15 states that access to environmental data may only be restricted when distribution is explicitly limited by law, regulation, policy (such as those applicable to personally identifiable information or protected critical infrastructure information or proprietary trade information) or by security requirements. The EDMC Data Access Procedural Directive contains specific guidance, recommends the use of open-standard, interoperable, non-proprietary web services, provides information about resources and tools to enable data access, and includes a Waiver to be submitted to justify any approach other than full, unrestricted public access.
Notes: The name of the Organization of the most recent Support Role of type "Distributor" is used. The support role must be in effect. This information is not required if an approved access waiver exists for this data.
Notes: This field is required if a Distributor has not been specified.
Notes: All URLs listed in the Distribution Info section will be included. This field is required if applicable.
This data can be obtained on-line at the following URL:
This data set is dynamically generated based on user-specified parameters.;
Notes: This field is required if applicable.
8. Data Preservation and Protection
The NOAA Procedure for Scientific Records Appraisal and Archive Approval describes how to identify, appraise and decide what scientific records are to be preserved in a NOAA archive.
(Specify NCEI-MD, NCEI-CO, NCEI-NC, NCEI-MS, World Data Center (WDC) facility, Other, To Be Determined, Unable to Archive, or No Archiving Intended)
Notes: This field is required if archive location is World Data Center or Other.
Notes: This field is required if archive location is To Be Determined, Unable to Archive, or No Archiving Intended.
Notes: Physical Location Organization, City and State are required, or a Location Description is required.
Discuss data back-up, disaster recovery/contingency planning, and off-site data storage relevant to the data collection
9. Additional Line Office or Staff Office Questions
Line and Staff Offices may extend this template by inserting additional questions in this section.