The ICESat-2 Density Dimension Algorithm (DDA): Applications to Ice Surface Characterization and Cloud Layer Detection.
Abstract
NASA's ICESat-2 (Ice, Cloud, and land Elevation Satellite 2) missionscheduled for launch in August 2017 will carry a micropulse photon-counting multi-beam LiDAR instrument called the Advanced Topographic Laser Altimeter System (ATLAS). Unlike the pulse-limited data of ICESat's Geoscience Laser Altimeter System (GLAS) instrument,ATLAS data will include returns for every photon, including actively sensed photons and ambient photons.In preparation for the mission, we have developed the density dimension algorithm (DDA) for cloud and ground elevation determination from ICESat-2 data. The DDA solves the problem of signal identification and specific versions of the algorithm allow analysis of cloud layers, aerosols and the main Earth surface types.Here we present examples of applications to glaciology and atmospheric sciences. The glaciology example is based on data from the ICESat-2 simulator instrument —Slope Imaging Multi-Polarization Photon Counting LiDAR (SIMPL) over outlet glaciers in Greenland in August 2015.SIMPL uses four beams at 532nm and 1064nm frequencies and in parallel and polarized modes. The DDA facilitates accurate height determination over heavily crevassed glaciers as demonstrated for the Giesecke Brær. The atmosphere version of the DDA is selected as the official algorithm for ICESat-2. Examples of the capability of the algorithm to detect even tenuous cloud layers and aerosols will be given.A parameter sensitivity study is conducted and optimal parameters for different conditions are presented. In particular, day time data potentially suffers from many ambient photon returns and therefore the thresholding procedure requires parameter adjustments to effectively retain surface without creating false high density patches in thefinal output. Finally, one of the principle difficulties in surface detection is the attenuation of photons in dense clouds above. In the interest of maximizing the utility of the data, methods are developed to detect faint ground signals present under clouds. The precision of ground detection under these clouds is limited and is not suitable for detailed surface characterization studies but may be useful in the examination of large scale glacial elevation change over time — an important aspect of glacial monitoring and ice mass balance studies.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.C11A0749M
- Keywords:
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- 0758 Remote sensing;
- CRYOSPHEREDE: 0799 General or miscellaneous;
- CRYOSPHEREDE: 1240 Satellite geodesy: results;
- GEODESY AND GRAVITYDE: 1241 Satellite geodesy: technical issues;
- GEODESY AND GRAVITY