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Data Set ID:

IceBridge Merged Photon Counting Lidar/Profiler L4 Surface Slope and Elevations, Version 1

This data set contains geolocated surface elevation measurements captured over Antarctica using the Sigma Space Mapping Photon Counting Lidar and Riegl Laser Altimeter. 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.

Geographic Coverage

  • Glaciers/Ice Sheets > Glacier Elevation/Ice Sheet Elevation
  • Sea Ice > Sea Ice Elevation
Spatial Coverage:
  • N: -53, S: -90, E: 180, W: -180

Spatial Resolution:
  • 10 m x 10 m
Temporal Coverage:
  • 25 November 2010
Temporal Resolution: 12 month
Data Format(s):
  • HDF
  • XML
Platform(s) BT-67
Sensor(s): Sigma Space Lidar
Version: V1
Data Contributor(s): Donald Blankenship, Scott Kempf, Duncan Young, Laura Lindzey
Data Citation

As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Blankenship, D. D., S. D. Kempf, D. A. Young, and L. E. Lindzey. 2014. IceBridge Merged Photon Counting Lidar/Profiler L4 Surface Slope and Elevations, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: http://dx.doi.org/10.5067/STLZLZ7ZI7Z4. [Date Accessed].

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Detailed Data Description

This data set consists of airborne photon counting lidar and laser altimetry observations. The following are the goals of this product:

  • to provide an estimate of surface elevation along the aircraft ground track
  • to provide estimates of local surface slopes
  • to parameterize the quality of the Photon Counting Lidar data set.

Data files contain attributes for Elevation and Slope, and Photon Altimetry. Top level properties and attributes include file level metadata as well as campaign details.


The data files are Hierarchical Data Format (HDF5). Each data file is paired with an associated XML file. The XML files contain location, platform, and instrument metadata.

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File and Directory Structure

Data files are organized in folders by date in the https://n5eil01u.ecs.nsidc.org/ICEBRIDGE/ILSNP4.001/ directory, for example /2012.12.04/.

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File Naming Convention

The HDF5 files are named according to the following convention and as described in Table 1:

File name examples: 



Table 1. HDF5 File Naming Convention
Variable Description
ILSNP4 Short name for IceBridge Merged Photon Counting Lidar/Profiler L4 Surface Slope and Elevations
YYYY Four-digit year of survey
DOY Day of year of survey
PPP Geographic area (Project)
JKB2S Host platform for timing (System)
TTTT Transect name within Project
nnn Granule within line
.xxx Indicates HDF5 file (.h5), or XML file (.xml)
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File Size

The data files range from approximately 218 KB to 11 MB.

The XML files range from approximately 10 KB to 41 KB.

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The entire data set is approximately 540 MB.

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Spatial Coverage

The target region for this data is East Antarctica and the Antarctic Peninsula. Please see the metadata in the top level of each HDF5 data file for targets for each granule.

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

Spatial Resolution

10 meter spot on the ground at 800 meters.

Projection and Grid Description

Polar Stereographic true at −71 degrees latitude EPSG:3031

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Temporal Coverage

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

Temporal Resolution

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

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Parameter or Variable

Parameter Description

Parameters are organized in the HDF5 files as Elevation and Slope attributes, and Photon Altimetry attributes. File level HDF5 attributes store metadata describing targets, collection parameters and details of funding and logistical support.

Elevation and Slope attributes are described in Table 2.

Table 2. Elevation and Slope Attributes Description
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
YEAR Year of survey Year
latitude Latitude of laser altimeter spot (WGS-84/ITRF08) Degrees North
longitude Longitude of laser altimeter spot (WGS-84/ITRF08) Degrees East
mean_swath_surface_elevation Mean nadir surface elevation of plane through all beams of the photon counting lidar swath (WGS-84/ITRF08) Meters
point_surface_elevation Surface elevation of laser altimeter spot (WGS-84/ITRF08) Meters
point_swath_divergence_angle Angular difference between normals of the swath best fit plane and the along track laser altimeter Degrees
seconds_of_day Seconds of day of survey Seconds (UTC)
x_gradient Gradient in x direction with respect to polar stereographic −71 projection (EPSG:3031) dimensionless
y_gradient Gradient in y direction with respect to polar stereographic −71 projection (EPSG:3031) dimensionless

Photon Altimetry includes information for BEAM0 through BEAM5. The exact location of the beams varies with scan pattern, but beam 0 and 1 are located along track, beam 2 and 3 are located at the edge of the scan pattern, and beams 4 and 5 are halfway between the edge and the flight track. Beam 0 was not used on data collected with a linear scan pattern. Please see granule metadata for specific details of beam layout and scan pattern used.

Photon Altimetry beam attributes are described in Table 3.

Table 3. Photon Altimetry Beam Attributes Description
Parameter Description Units
DOY Day Of Year of survey Day
DScontinuous_time_of_day Time since midnight of the first day of acquisition. Seconds
DSdelta_time_start Time since the start of the transect Seconds
X_range_vector Cross track component of detected surface spot with respect to the lidar body; positive is along right wing Meters
YEAR 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
course_noise_rate Number of photons in current beam in a 5 meter window 20 meters above surface over 0.25 second interval Counts
latitude Latitude of detected surface spot (WGS-84/ITRF08) Degrees North
leading_quartile_range Range between detected surface and the 25th percentile photon above the surface, from a total population from a 15 meter window around the surface Meters
longitude Longitude of detected surface spot (WGS-84/ITRF08) Degrees East
peak_event_count_course Number of photons in current beam in a 5 meter window around the surface counted over 0.25 second period Counts
peak_event_count_fine Number of photons in current beam in a 1 centimeter window around the surface counted over 0.25 second period Counts
point_surface_elevation Surface elevation of detected surface spot (WGS-84/ITRF08) Meters
seconds_of_day Seconds of day of survey Seconds UTC

Sample Data Record

Below are mean_swath_surface_elevation, and point_surface_elevation values from a sample of the ILSNP4_2012339_SCT_JKB2h_Y46b_000.h5 data file as displayed in the HDFView tool.

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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.

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Data Acquisition and Processing

Data Acquisition Methods

Data were acquired from an aircraft flown between 500 and 1500 meters above the ice sheet surface. A laser altimeter and a scanning photon counting lidar system collected range data, while IMU and GPS instruments were used to collect trajectory information.

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Derivation Techniques and Algorithms

Input products are:

Please review descriptions of these data products for geolocation, initial filtering, and calibration methods.

In order to determine the surface location, the ranges are extracted from the beam's subset photon cloud. For each beam, a coarse histogram is built along the Z_range_vector of the lidar coordinate system with 5 meter bin resolution. The peak bin is selected as the coarse z distance.

In order to determine a more precise location, we return the median z distance of the photons in the maximum coarse bin and the two adjacent bins.

Using the known angles for this beam and the computed distance to the surface in the z direction, we calculate x distance and y distance in the lidar reference frame. We then rotate and translate the lidar range vector using the reported aircraft orientation using the estimated pointing biases and measured lever arm between the IPUTG1B coordinate system and the lidar.

This vector is then added to the aircraft trajectory to obtain the surface location in the WGS-84 reference frame. Statistics on the shape of the surface return peak and background noise character were also reported.

Trajectory and Attitude Data

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

Processing Steps

As absolute ranges for the lidar may have a bias due to uncertainties in the high resolution timing oscillator, the lidar data are integrated with simultaneously acquired laser profiler data.

The local surface slope was determined by fitting a plane to a 400 meter wide segment of the lidar surface elevation data, which was integrated with the laser altimetry ILSNP1B product, and provided the final surface elevation.

Version History

On 25 April, 2014, the the ILSNP4 HDF5 data replaced the ASCII data in the previous ILSNP2 data set. The data are newly processed as a Level-4 product. ILSNP4 includes a composite profiler-lidar product for altimetry and cross track slope. Vector rotations now occur in Earth Centered Earth Fixed space.

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 part of the ILSNP4 dataset.

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 2010-2011 data, GPS errors were higher (typically 10 cm) as the GPS data was not constrained by IMU data.

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

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Sensor or Instrument Description

Instrumentation is comprised of the following components

Sigma Space Mapping Photon Counting Lidar system

  • Lidar scan pattern: circular
  • Lidar scan rate: 18 hertz
  • Lidar shot rate: 20 kilohertz
  • Lidar wavelength: 532 nanometers

As described on the University of Texas Institute for Geophysics Web site, the scanning photon counting lidar images the surface below the aircraft with one hundred laser beamlets which are mechanically scanned in a swath either side of the flight path. A one hundred channel photon counting receiver captures return photons and records time of flight and time tag data allowing a three dimensional reconstruction of the surface flown over. The system can make 2.2 million measurements per second. At the typical survey elevation of 800 meters above the ice sheet, the swath width is about 400 meters.

Reigl LD90-3800HiP-LR Distance Meter


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Contacts and Acknowledgments

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


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

Document Information

Document Creation Date

24 April 2014

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No FAQs or How Tos available for this data set.

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