Using Airborne Lidar Data from IcePod to Measure Annual and Seasonal Ice Changes Over Greenland

Abstract:

The IcePod is a multi-sensor airborne science platform that supports a wide suite of instruments, including a Riegl VQ-580 infrared scanning laser, GPS-inertial positioning system, shallow and deep-ice radars, visible-wave and infrared cameras, and upward-looking pyrometer. These instruments allow us to image the ice from top to bottom, including the surface of melt-water plumes that originate at the ice-ocean boundary. In collaboration with the New York Air National Guard 109^th Airlift Wing, the IcePod is flown on LC-130 aircraft, which presents the unique opportunity to routinely image the Greenland ice sheet several times within a season. This is particularly important for mass balance studies, as we can measure elevation changes during the melt season. During the 2014 summer, laser data was collected via IcePod over the Greenland ice sheet, including Russell Glacier, Jakobshavn Glacier, Eqip Glacier, and Summit Camp. The Icepod will also be routinely operated in Antarctica.

We present the initial testing, calibration, and error estimates from the first set of laser data that were collected on IcePod. At a survey altitude of 1000 m, the laser swath covers ~ 1000 m. A Northrop-Grumman LN-200 tactical grade IMU is rigidly attached to the laser scanner to provide attitude data at a rate of 200 Hz. Several methods were used to determine the lever arm between the IMU center of navigation and GPS antenna phase center, terrestrial scanning laser, total station survey, and optimal estimation. Additionally, initial bore sight calibration flights yielded misalignment angles within an accuracy of ±4 cm. We also performed routine passes over the airport ramp in Kangerlussuaq, Greenland, comparing the airborne GPS and Lidar data to a reference GPS-based ground survey across the ramp, spot GPS points on the ramp and a nearby GPS base station. Positioning errors can severely impact the accuracy of a laser altimeter when flying over remote regions such as across the ice sheets. Setting up GPS base stations along the flight track can prove to be logistically challenging. We have processed the GPS-inertial data using both DGPS and PPP and present the comparison of those results here. Finally, we discuss our processing, calibration and error estimation methods and compare our results to previously flown IceBridge lines.