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IceBridge Photon Counting Lidar L1B Subset Geolocated Photon Elevations

This data set contains nadir photon counting data captured over Antarctica using the Sigma Space photon counting lidar. Position and orientation data are included. The data were collected by scientists working on the International Collaborative Exploration of the Cryosphere through Airborne Profiling (ICECAP) project, which was funded by the National Science Foundation (NSF), the Antarctic Climate and Ecosystems Collaborative Research Center, and the Natural Environment Research Council (NERC) with additional support from NASA Operation IceBridge.

Operation IceBridge products may include test flight data that are not useful for research and scientific analysis. Test flights usually occur at the beginning of campaigns. Users should read flight reports for the flights that collected any of the data they intend to use. Check IceBridge campaign Flight Reports for dates and information about test flights.

Table of Contents

  1. Contacts and Acknowledgments
  2. Detailed Data Description
  3. Data Access and Tools
  4. Data Acquisition and Processing
  5. References and Related Publications
  6. Document Information

Citing These Data

We kindly request that you cite the use of this data set in a publication using the following citation example. For more information, see our Use and Copyright Web page.

Blankenship, Donald D., Duncan A. Young, Laura E. Lindzey, Scott D. Kempf. 2012, updated 2014. IceBridge Photon Counting Lidar L1B Subset Geolocated Photon Elevations, [indicate subset used]. Boulder, Colorado USA: NASA DAAC at the National Snow and Ice Data Center. http://nsidc.org/data/ilsnp1b.html.

Overview

Platform

Kenn Borek Air DC-3T

Sensor

Sigma Space Photon Counting Lidar

Spatial Coverage

East Antarctica, Antarctic Peninsula, Greenland

Spatial Resolution

10 cm spot on the ground at 800 m

Temporal Coverage

25 November 2010 to the present

Temporal Resolution

Seasonal

Parameters

Photon Counting Data
paired with Position/Orientation Data

Data Format

Hierarchical Data Format (HDF5)

XML

Metadata Access

View Metadata Record

Get Data

FTP

1. Contacts and Acknowledgments

Investigator(s) Name and Title

Donald D. Blankenship, Duncan A. Young, Laura E. Lindzey, Scott D. Kempf
University of Texas at Austin
Institute for Geophysics
Austin, TX, 78759-8500

Technical Contact

NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449  USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
e-mail: nsidc@nsidc.org

Acknowledgements

ICECAP/Operation Ice Bridge. See each granule HDF5 metadata for specific grants and logistical support.

2. Detailed Data Description

Format

The data files are in HDF5 format. Each data file is paired with an associated XML file. The XML files contain location, platform, and instrument metadata.

File Naming Convention

The files are named according to the following convention and as described in Table 1:

ILSNP1B_2012327_ICP5_JKB2h_F07T02a_005.h5

ILSNP1B_2012327_ICP5_JKB2h_F07T02a_005.h5.xml

ILSNP1B_YYYYDOY_PPP_JKB2h_TTTT_xxx.h5

Where:

Table 1. Naming Convention
Variable Description
ILSNP1B Short name for IceBridge Sigma Space Photon Counting Lidar L1B Time-Tagged Nadir Photon Ranges
YYYY Four-digit year of survey
DOY Day of year of survey
PPP Geographic area (Project)
JKB2h Host platform for timing (System)
TTTT Transect name within Project
xxx Granule within line
.h5 indicates HDF5 file
.h5.xml indicates XML metadata file

File Size

The HDF5 data files range from approximately 1.5 MB to 260 MB.

Volume

The entire data set is approximately 465 GB.

Spatial Coverage

The target region for this data is East Antarctica, Greenland, and the Antarctic Peninsula. Please see HDF5 metadata for targets for each granule.

Greenland:
Southernmost Latitude 59° N
Northernmost Latitude: 83° N
Westernmost Longitude: 74° W
Easternmost Longitude: 12° W

Antarctica:
Southernmost Latitude: 90° S
Northernmost Latitude: 53° S
Westernmost Longitude: 180° W
Easternmost Longitude: 180° E

Spatial Resolution

10 centimeter spot on the ground at 800 meters (per photon).

Projection and Grid Description

Polar Stereographic at -71 degrees latitude EPSG:3031

Temporal Coverage

These data were collected as part of ICECAP, NSF, NERC, and Operation IceBridge funded campaigns from 25 November 2010 to the present.

Temporal Resolution

ICECAP campaigns were conducted on an annual basis. East Antarctic campaigns for this data set typically extend from November to early January.

Parameter or Variable

Parameter Description

Parameters in the HDF5 files are organized as photon data, granule georeferencing data, and transect georeferencing data attributes. In addition, top level attributes store metadata describing platform, beam location on scan, and additional campaign information.

Photon data attributes for BEAM0 through BEAM5 are described in Table 2.

Table 2. Photon Data Attributes
Parameter Description Units
DOY Day Of Year of survey Day
DScontinuous_time_of_day Seconds since 2012-12-04 0:0:0 Seconds
DSdelta_time_start Seconds since 2012-12-04T00:12:03 Seconds
Easting Apparent projected Easting of photon (WGS-84/ITRF08/EPSG:3031) Meters
Elevation Apparent elevation of photon (WGS-84/ITRF08) Meters
Northing Apparent projected northing of photon (WGS-84/ITRF08/EPSG:3031) Meters
X_range_vector Cross track component of detected surface spot with respect to the lidar body; positive is along right wing Meters
YEAR Current year (UTC) (Year of survey) Year
Y-range_vector Along track component of detected surface spot with respect to the lidar body; positive is toward nose Meters
Z-range_vector Along track component of detected surface spot with respect to the lidar body; positive is down Meters
cell Numbered counting channel on detector array Count
seconds_of_day Seconds of current day (UTC) (on day of survey) Seconds

Granule and transect georeferencing data attributes are described in Table 3.

Table 3. Granule and Transect Georeferencing Data Attributes
Parameter Description Units
DOY Day Of Year of survey Day
DScontinuous_time_of_day Seconds since 2012-12-04 0:0:0 Seconds
DSdelta_time_start Seconds since 2012-12-04T00:12:03 Seconds
EW_acceleration East-West acceleration of the aircraft Milligal
NS_acceleration North-South acceleration of the aircraft Milligal
YEAR Current year (UTC) (Year of survey) Year
aircraft_elevation Elevation of center of gravity GNSS antenna, as determined by real time kalman filter (WGS-84/ITRF08) Meters
heading_angle Rotation around aircraft Z axis (with respect to true north, clockwise is positive) Degrees
latitude Latitude of laser altimeter spot (WGS-84/ITRF08) Degrees North
longitude Longitude of laser altimeter spot (WGS-84/ITRF08) Degrees East
pitch_angle Rotation around aircraft Y axis (with respect to local geodetic vertical, nose up is positive, zero is aircraft level) Degrees
position_error The geometric sum of the expected horizontal and vertical position errors derived by taking the square root of the corresponding Kalman filter variances Degrees
roll_angle Rotation around aircraft X axis (with respect to local geodetic vertical, right wing up is positive, zero is wings level) Meters
seconds_of_day Seconds of current day Seconds (UTC)
vertical_acceleration vertical acceleration of the aircraft Milligal

Sample Data Record

Below are Elevation values for BEAM1, BEAM2, and BEAM3 from a sample of the ILSNP1B_2012327_ICP5_JKB2h_F07T02a_005.h5 data file as displayed in the HDFView tool.

3. Data Access and Tools

Get Data

Data are available via FTP.

Software and Tools

The following external links provide access to software for reading and viewing HDF5 data files. Please be sure to review instructions on installing and running the programs. Version 1.8.5 of the HDF5 libraries was used.

HDFView: Visual tool for browsing and editing HDF4 and HDF5 files.

h5dump: Free standard UNIX command line tool to extract HDF5 content.

h5py: Free python module for interacting with HDF5 data. Depends on the SciPy/NumPy suite of Python Modules.

Matlab: The h5read command in recent versions of Mathworks Matlab can also access HDF5 variables.

For additional tools, see the HDF-EOS Tools and Information Center.

4. Data Acquisition and Processing

Theory of Measurements

The concept of a Photon Counting Lidar (PCL) is described in Degnan, 2002. While the fundamental principles are similar to that of a traditional laser ranging system, a PCL relies on very fast pulse rates and statistical integration to allow detection of lower energy returns, which results in substantial reduction in power, mass, and optical structure requirements. The scanning PCL system (Degnan et al., 2007) from which the PCL was derived was originally developed as an outer-planets exploration test bed, then adapted for deployment on unmanned airborne vehicles.

The ability to field a light weight instrument with multiple lidar beams was a fundamental driver of the decision to use a photon counting system (the Advanced Topographic Laser Altimeter System, ATLAS) on ICESat-2 (Yu, 2010). The PCL system differs from NASA's Multiple Altimeter Beam Experimental Lidar or MABEL (Brunt et al., 2010), in that the PCL is typically flown at much lower heights (800 meters versus 20,000 m), has more cells (up to 100 versus 16), and actively scans versus having fixed discrete beams.

Our approach to addressing the large data volume involves subsampling the photons into beams chosen to mimic the planned ATLAS configuration, detecting a surface while still in the aircraft-relative frame, and finally georeferencing that surface point.

The objective of beam averaging is to generate a simple data product of manageable volume that can be used both to iteratively determine pointing biases and to accomplish first-order altimetry science goals. To do this we emulate the discrete beams found on the ATLAS system by filtering for photons within limited cones.

For circular scan patterns, we selected six cones within the lidar reference frame sampling the edges, fore and aft, and at 45 degrees. For linear scan patterns, we selected the edges of the scan pattern, the nadir point, and two points in between. Each beam consists of the photons within a single cone. At typical aircraft survey heights, this corresponds to a 10 m wide footprint for each beam. Refer to Figure 1 for locations of geolocated PCL surface recoveries in the Indo-Pacific sector of East Antarctica. Background is bed elevations showing major subglacial basins (Fretwell et al, 2013).

Figure 1: Locations of geolocated PCL surface recoveries in the Indo-Pacific sector of East Antarctica.

Data Acquisition Methods

The ICECAP geophysical system was installed on the aircraft at the McMurdo seasonal sea ice runway at the start of each field season. Installation is followed by a calibration flight involving multiple crossovers over flat ice. On typical data-collection flights, the aircraft is flown 600 m to 1000 m above the ground, at a ground speed of 90 m sec-1.

A range gate is applied to limit incoming photons on the PCL. This is adjusted to match the aircraft's height above ice, and was typically 1000 m tall, centered at a distance of 1000 m. Approximately 100 GB of range data are acquired per six hour flight.

Derivation Techniques and Algorithms

After the trajectory is obtained, for each time step the position and orientation in Earth Centered Earth Fixed space is found, and matrix translations are performed for the sensor lever arm and range vector, following Vaughn et al. (1996) and Koks (2006). The data are then transformed back to the WGS-84 ellipsoidal reference frame.

Pointing biases are determined using an iterative minimization of crossover errors. See Table 4.

Table 4. Pointing Biases
Season Date Roll Bias Pitch Bias Crossings Error (cm) Target
ICP3 December 18, 2010 0.325° (−0.2 25°) −4.525° (−0.525°) 107 (1976) 10.7 (37) Law Dome
ICP4 December 23, 2011 0.370° (0.150°) −4.200° (0.075°) 62 (443) 6.0 (16.9) McMurdo Ice Shelf
ICP5 November 13, 2012 0.475° (0.175°) −3.450° (0.025°) 96 (968) 12.5 (23.4) Ross Ice Shelf

Trajectory and Attitude Data

Please see each granule's HDF5 attributes, and the IPUTG1B dataset for details of trajectory collection.

Error Sources

The lidar coarse clock used to calculate ranges has a temperature and acquisition card dependent uncertainty of 0.1 percent, which translates to a scaling error in range of ~80 cm. For this reason, we use the ILUTP2 data to calibrate results in the Elevation and Slope section of the ILSNP4 data set.

GPS relative errors are estimated by Waypoint to be typically 6 cm where a convergent combined GPS-IMU solution is produced, with orientation errors of 50 μrad.

For 2010-11 data, GPS errors were higher (typically 10 cm) as the GPS data was not constrained by IMU data.

We used a simple, static 1-D atmospheric model to estimate delays due to propagation through air.

Sensor or Instrument Description

In the PCL system a 532 nm laser beam, pulsed at ~19 kHz, is split into a 10 x 10 grid of beamlets and projected through a Risley prism beam steering unit, with time of the outgoing pulse recorded as the pulse start. The angular spread of the beamlets is 0.12° along each side of the grid yielding an illuminated grid on the ground of about 1-2 meters for every shot.

For the 2010-11 season, two prisms were used to generate a 45 degrees linear scan pattern, with a maximum deflection from nadir of 14.9 degrees. During the 2011 and 2012 seasons only one prism was used, which resulted in a reduced circular scan pattern with 7.3 degrees deflection from nadir. The beam steering unit is synchronized to the laser, such that one cycle of the beam steering unit corresponds to 1024 shots after the system has spun up after starting; thus the system scans underlying terrain at 18.5 Hz. Return photons are received through the same optics and directed to a 10 x 10 cell anode microchannel plate photomultiplier. Timing of the returns is split 50/50 between two independent Field-Programmable Gate Arrays (FPGAs).

Each cell has a coarse, 16 bit approximately 295 Hz clock (range resolution ~0.5 meters) and a fine 8 bit ~12.5 GHz clock (range resolution ~1.2 cm), calibrated per shot that allows ~0.1 nsec precision for detection times (stops). The differences between the starts and stops is the time of flight, which multiplied by an appropriate velocity of light provides the apparent range to the photon source. The coarse clock rate can drift due to temperature and hardware issues by up to 0.01 percent, limiting absolute accuracy to 80 cm without registration to the LAS.

The 0.7 nsec pulse width limits the precision of start times, yielding a minimum range precision per-photon of ~10.5 cm. Systematic biases between individual cells are estimated to be symmetrically distributed with a root mean squared (RMS) deviation of 15 cm. Higher precision requires stacking numerous individual shots.

Time stamps are generated with every shot, every prism rotation, and on reception of a 1 Hz GPS generated pulse from timing calibration. The timing data from each FPGA is recorded directly to independent hard drives, typically at 4-5 MB sec-1. In post-processing, these time stamps allow each photon's time-of-flight to be converted into an X, Y, and Z location relative to the sensor.

5. References and Related Publications

Brunt, K. M., H. A. Fricker, L. Padman, T. A. Scambos, and S. O'Neel. 2010. Mapping the Grounding Zone of the Ross Ice Shelf, Antarctica, Using ICESat Laser Altimetry, Annals Of Glaciology, 51(55):71-79, doi:10.3189/172756410791392790.

Degnan, J., D. Wells, R. Machan, and E. Leventhal. 2007. Second Generation Airborne 3D Imaging Lidars Based on Photon Counting, SPIE Proceedings: Lidar, 6771/67710N. 10.1117/12.732086.

Degnan, J. J. 2002. Photon-counting Multikilohertz Microlaser Altimeters for Airborne and Spaceborne Topographic Measurments, Journal Of Geodynamics, 34(3-4): 503-549.

Fretwell, P., et al. 2013. Bedmap2: Improved Ice Bed, Surface and Thickness Datasets for Antarctica, The Cryosphere, 7: 375--393, 10.5194/tc-7-375-2013.

Koks, D. 2006. Using Rotations to Build Aerospace Coordinate Systems, Australian Government, Defence Science and Technology Organization, DSTO-TN-0640.

Vaughn, C. R., J. L. Button, W. B. Krabill, and D. Rabine. 1996. Georeferencing of Airborne Laser Altimeter Measurements, International Journal Of Remote Sensing, 17, 11, 2185-2200, 10.1080/01431169608948765.

Young, D. A., et al. In review. Extending Surface Elevation Time Series in East Antarctica Using ICECAP Photon Counting Swath Altimetry, Journal Of Glaciology.

Yu, A. W., et al. 2010. Space Laser Transmitter Development for ICESat-2 Mission, Proceedings Of SPIE, 7578, 757809-2.

Related Data Collections

Related Web Sites

6. Document Information

Acronyms and Abbreviations

The acronyms used in this document are listed in Table 4.

Table 4. Acronyms and Abbreviations
Acronym Description
ASCII American Standard Code for Information Interchange
ATLAS Advanced Topographic Laser Altimeter System
CIRES Cooperative Institute for Research in Environmental Science
FPGA Field-Programmable Gate Array
FTP File Transfer Protocol
GPS Global Positioning System
ICECAP Investigating the Cryospheric Evolution of the Central Antarctic Plate
IceSat-2 Ice, Cloud, and land Elevation Satellite-2
IMU Inertial Measurement Unit
JPEG Joint Photographic Experts Group
HDF5 Hierarchical Data Format 5
ITRF International Terrestrial Reference Frame
L1B Processing Level-1B
MABEL Multiple Altimeter Beam Experimental Lidar
NASA National Aeronautics and Space Administration
NERC Natural Environment Research Council
NSF National Science Foundation
NSIDC National Snow and Ice Data Center
PCL Photon Counting Lidar
URL Uniform Resource Locator
UTC Coordinated Universal Time
UTIG University of Texas Institute for Geophysics
WGS-84 World Geodetic System 1984

Document Creation Date

25 June 2014

Document Revision Date

.....

Document URL

http://nsidc.org/data/docs/daac/icebridge/ilsnp1b/index.html