Bruce Wallin

Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation for the ICESat-2 Mission

NASAs Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission is a decadal survey mission (2016 launch). The mission objectives are to measure land ice elevation, sea ice freeboard, and changes in these variables, as well as to collect measurements over vegetation to facilitate canopy height determination. Two innovative components will characterize the ICESat-2 lidar: 1) collection of elevation data by a multibeam system and 2) application of micropulse lidar (photon-counting) technology. A photon-counting altimeter yields clouds of discrete points, resulting from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of the returned points to reflectors of interest. The objective of this paper is to derive an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2 data, based on airborne observations with a Sigma Space micropulse lidar. The mathematical algorithm uses spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors, and geostatistical classification parameters and hyperparameters. Validation shows that ground and canopy elevation, and hence canopy height, can be expected to be observable with high accuracy by ICESat-2 for all expected beam energies considered for instrument design (93.01%-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp), and 72.85%-98.68% for 0.48 msp). The algorithm derived here is generally applicable for elevation determination from photon-counting lidar altimeter data collected over forested areas, land ice, sea ice, and land surfaces, as well as for cloud detection.

Using the MicroASAR on the NASA SIERRA UAS in the Characterization of Arctic Sea Ice Experiment

The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU µSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role flying on the SIERRA UAS platform as part of CASIE-09.

On the influence of Greenland outlet glacier bed topography on results from dynamic ice-sheet models

Abstract Prediction of future changes in dynamics of the Earth’s ice sheets, mass loss and resultant contribution to sea-level rise are the main objectives of ice-sheet modeling. Mass transfer from ice sheet to ocean is, in large part, through outlet glaciers. Subglacial topography plays an important role in ice dynamics; however, trough systems have not been included in bed digital elevation models (DEMS) used in modeling, because their size is close to the model resolution. Using recently collected CReSIS MCoRDs data of subglacial topography and an algorithm that allows topographically and morphologically correct integration of troughs and trough systems at any modeling scale (5 km resolution for SeaRISE), an improved Greenland bed DEM was developed that includes Jakobshavn Isbræ, Helheim, Kangerdlussuaq and Petermann glaciers (JakHelKanPet DEM). Contrasting the different responses of two Greenland ice-sheet models (UMISM and SICOPOLIS) to the more accurately represented bed shows significant differences in modeled surface velocity, basal water production and ice thickness. Consequently, modeled ice volumes for the Greenland ice sheet are significantly smaller using the JakHelKanPet DEM, and volume losses larger. More generally, the study demonstrates the role of spatial modeling of data specifically as input for dynamic ice-sheet models in assessments of future sea-level rise.

An algorithm for generalizing topography to grids while preserving subscale morphologic characteristics-creating a glacier bed DEM for Jakobshavn trough as low-resolution input for dynamic ice-sheet models

The objective of this paper is to derive an algorithm for preserving important subscale morphologic characteristics at grids of lower-resolution, in particular for linear features such as canyons and ridge lines. The development of such an algorithm is necessitated by applications that require reduced spatial resolution, as is common in cartographic generalization, GIS applications, and geophysical modeling. Since any algorithm that results in weighted averages, including optimum interpolation and ordinary kriging, cannot reproduce correct depths, a new algorithm is designed based on principles of mathematical morphology. The algorithm described here is applied to derive a subglacial bed of the Greenland Ice Sheet that includes the trough of Jakobshavn Isbrae as a continuous canyon at correct depth in a low-resolution (5-km) digital elevation model (DEM). Data from recent airborne radar measurements of the elevation of the subglacial bed as part of the CReSIS project are utilized. The morphologic algorithm is designed with geophysical ice-sheet modeling in mind, in the following context. Currently occurring changes in the Earths climate and the cryosphere cause changes in sea level, and the societal relevance of these natural processes motivates estimation of maximal sea-level rise in the medium-term future. The fast-moving outlet glaciers are more sensitive to climatic change than other parts of the Greenland ice sheet. Jakobshavn Isbrae, the fastest-moving ice stream in Greenland, follows a subglacial geologic trough. Since the existence of the trough causes the acceleration of the slow-moving inland ice in the Jakobshavn region and the formation of the ice stream, correct representation of the trough in a DEM is essential to model changes in the dynamics of the ice sheet and resultant sea-level predictions, even if current ice-sheet models can typically be run only at 5-km resolution. The DEM resultant from this study helps to bridge the conceptual gap between data analysis and geophysical modeling approaches. It is available as SeaRISE Greenland bed data set dev1.2 at http://websrv.cs.umt.edu/isis/index.php/SeaRISE_Assessment.

Applications of Geostatistics in Optimal Design of Satellite Altimetry Orbits and Measurement Configurations

The Geoscience Laser Altimeter System (GLAS) aboard NASA’s Ice, Cloud and land Elevation Satellite (ICESat) is a pulse-limited laser that records measurements in a geophysical track-line ground pattern of single discrete points along a sub-satellite track. Spacing between tracks depends on latitude and repeat cycle. Derivation of digital elevation models (DEMs) of the ice surface from GLAS data requires interpolation, which due to the spatial data distribution is mathematically an extrapolation problem, best solved using a form of geostatistical estimation. In this article, we investigate the relationships between observing ice surface elevations with single-beam and multi-beam altimetry, regional coverage and spatial resolution, orbit ground track design and repeat-track spacing, analysis with ordinary and advanced universal Kriging algorithms and resultant DEM accuracy. The study is a contribution to the ICESat-2 ad-hoc Science Definition Team tasks and analyzes GLAS data and several potential multi-beam configurations proposed for the ICESat-2 instrumentation. Measurement of elevation change at the accuracy required by the U.S. National Research Council (2007) “Decadal Survey” recommendations requires understanding the effects of spatial variability of the elevation measurement, in particular for complex, rough or steep natural surfaces. This problem, which is important to correctly assess the cryosphere’s contribution to sea-level rise, is treated using scale-dependent simulation. Results indicate that multi-beam laser measurements are needed and provide a solution to the trade-off problem between repeat-mission and geodetical coverage. More generally, the article demonstrates links between space mission planning, orbit design, spatial distribution of measurements from future instrumentation and improved mathematical data processing algorithms.

The trough-system algorithm and its application to spatial modeling of Greenland subglacial topography

Abstract Dynamic ice-sheet models are used to assess the contribution of mass loss from the Greenland ice sheet to sea-level rise. Mass transfer from ice sheet to ocean is in a large part through outlet glaciers. Bed topography plays an important role in ice dynamics, since the acceleration from the slow-moving inland ice to an ice stream is in many cases caused by the existence of a subglacial trough or trough system. Problems are that most subglacial troughs are features of a scale not resolved in most ice-sheet models and that radar measurements of subglacial topography do not always reach the bottoms of narrow troughs. The trough-system algorithm introduced here employs mathematical morphology and algebraic topology to correctly represent subscale features in a topographic generalization, so the effects of troughs on ice flow are retained in ice-dynamic models. The algorithm is applied to derive a spatial elevation model of Greenland subglacial topography, integrating recently collected radar measurements (CReSIS data) of the Jakobshavn Isbræ, Helheim, Kangerdlussuaq and Petermann glacier regions. The resultant JakHelKanPet digital elevation model has been applied in dynamic ice-sheet modeling and sea-level-rise assessment.

Spatio-temporal analysis of surface elevation changes in Pine Island Glacier, Antarctica, from ICESat GLAS data and ERS-1 radar altimeter data

Abstract Characterized by fast movement, low surface slope and grounding below sea level, Pine Island Glacier (PIG) plays an important role in the stability of the West Antarctic ice sheet. In previous work, we reported that the spatial distribution of 1995–2003 surface lowering in PIG suggests an attribution of changes to an internally forced process in the glacier. Other work associates changes in PIG entirely with processes in its ice shelf. Here time series of maps of surface elevation change in PIG and its ice shelf are derived from geostatistical analysis of ICESat GLAS and ERS-1 radar altimeter data. Based on spatio-temporal analysis of 1995–2007 elevation change, we discuss indications of processes that initiate from changes in the ice shelf versus processes that start internally in the glacier. Thinning rates continued to increase after 2003, regionally to >15 m a–1. The initiation of acceleration occurred in the interior of the ice stream, while in later years largest elevation loss was driven by changes in the ice shelf and upward propagation. By 2006, the region of thinning had expanded up-glacier beyond the initial areas of surface lowering to 100 km above the hinge line. More than one process causes dynamically complex changes in PIG.

Utilizing the microASAR on the SIERRA UAS for NASA's characterization of Arctic Sea Ice Experiment

The MicroASAR is a flexible, robust SAR system built on the successful legacy of the BYU ìSAR. It is a compact LFM-CW SAR system designed for low-power operation on small, manned aircraft or UAS. The NASA SIERRA UAS was designed to test new instruments and support flight experiments. NASA used the MicroASAR on the SIERRA during a science field campaign in 2009 to study sea ice roughness and break-up in the Arctic and high northern latitudes. This mission is known as CASIE-09 (Characterization of Arctic Sea Ice Experiment 2009). This paper describes the MicroASAR and its role on the SIERRA UAS platform as part of CASIE-09.