The Algorithm Theoretical Basis Document for the Derivation of Range and Range Distributions from Laser Pulse Waveform Analysis for Surface Elevations, Roughness, Slope, and Vegetation Heights

The primary purpose of the GLAS instrument is to detect ice elevation changes over time which are used to derive changes in ice volume. Other objectives include measuring sea ice freeboard, ocean and land surface elevation, surface roughness, and canopy heights over land. This Algorithm Theoretical Basis Document (ATBD) describes the theory and implementation behind the algorithms used to produce the level 1B products for waveform parameters and global elevation and the level 2 products that are specific to ice sheet, sea ice, land, and ocean elevations respectively. These output products, are defined in detail along with the associated quality, and the constraints, and assumptions used to derive them

The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products

The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming

Assessment of Cloud Screening with Apparent Surface Reflectance in Support of the ICESat-2 Mission

The separation of cloud and clear scenes is usually one of the first steps in satellite data analysis. Before deriving a geophysical product, almost every satellite mission requires a cloud mask to label a scene as either clear or cloudy through a cloud detection procedure. For clear scenes, products such as surface properties may be retrieved; for cloudy scenes, scientist can focus on studying the cloud properties. Hence the quality of cloud detection directly affects the quality of most satellite operational and research products. This is certainly true for the Ice, Cloud, and land Elevation Satellite-2 (lCESat-2), which is the successor to the ICESat-l. As a top priority mission, ICESat-2 will continue to provide measurements of ice sheets and sea ice elevation on a global scale. Studies have shown that clouds can significantly affect the accuracy of the retrieved results. For example, some of the photons (a photon is a basic unit of light) in the laser beam will be scattered by cloud particles on its way. So instead of traveling in a straight line, these photons are scattered sideways and have traveled a longer path. This will result in biases in ice sheet elevation measurements. Hence cloud screening must be done and be done accurately before the retrievals

Satellite laser altimetry over sea ice.

The Arctic region plays an important role in the global climate system through various feedbacks, involving surface albedo, oceanic deep-water formation, and sea surface salinity, which can amplify climate variability and change. We investigate the exploitation of data collected by the first Earth-orbiting laser altimeter carried onboard ICESat over the sea-ice covered regions of the Arctic Ocean. We extract parameters associated with the study of the polar climate system including the time-varying component of sea surface topography and sea ice freeboard. We assess an existing method for the retrieval of Arctic sea surface height from ICESat data. We present an alternative method for sea surface height retrieval, based on surface reflectivity and analysis of parameters associated with the shape of the received echo. This method aims to discriminate echoes originating over leads or thin ice. We provide the first maps of Arctic sea surface height as derived from ICESat. We examine the accuracy of our results through comparisons with independent sea surface height estimates derived from ENVISAT radar altimetry. We demonstrate the use of sea surface height data for oceanographic and geodetic applications in the Arctic Ocean. We derive an ICESat mean sea surface which, when combined with the recently developed Arctic hybrid geoid model, can be used to analyse mean dynamic ocean topography. In addition we investigate the use of ICESat sea surface height measurements to map marine gravity anomalies up to the limit of coverage at 86 N. By combining ICESat surface elevation measurements with sea surface height estimates, we derive sea ice freeboard throughout the Arctic up to 86 N. We compare our results to coincident estimates of sea ice freeboard from ENVISAT. Finally, we explore the feasibility of combining satellite laser and radar altimetric measurements of sea ice freeboard to measure the depth of snow loading on sea ice

Biophysical parameter retrieval from satellite laser altimetry.

Quantifying and monitoring vegetation distribution and change are fundamental to carbon accounting and requirements of national forest inventories. This research explores the potential of the Geoscience Laser Altimeter System (GLAS), launched in 2003 by NASA as the first global Earth surface satellite LiDAR mission. The project study site is the Forest of Dean, Gloucestershire, UK, a highly mixed, temperate forest with varied topography. Methods are developed to distinguish the regions within waveforms returned from vegetation and ground. When compared with field measurements, estimation of canopy height gives a correlation of R2=0.92; RMSE=2.81m. Waveform indices are determined and evaluated with respect to their potential to estimate biophysical parameters. Heights of cumulative energy percentiles within the waveform prove to be significant estimators. When compared to calculations from independent yield models, results show correlations with stand- level top height (R2=0.76; RMSE 3.9m) and stemwood volume (mixed composition stands dominated by broadleaves: R2=0.47, RMSE=75.6m3/ha; conifers: R2=0.66, RMSE=82.5m3/ha). Uncertainty analysis is undertaken of both waveform and yield model estimates. Canopy cover is estimated for the area beneath GLAS waveforms, corrected for differences in reflectance for ground and canopy surfaces. These are assessed against airborne LiDAR estimates, validated using hemispherical photography. The method produces results with R2=0.63; RMSE=11% for stands with greatest coverage by broadleaves and R2=0.41; RMSE 16% for conifer-dominated stands. Small footprint airborne LiDAR (AL) is widely accepted to offer valuable data regarding forest parameters. An evaluation of AL and GLAS results demonstrate that the broad GLAS footprint dimensions allow similar estimation of stand-level parameters (e.g. AL/yield model Top Height: R2=0.73, RMSE=4.5m). Direct comparison of GLAS with AL shows ground surface identification with mean difference of 0.32m and that elevation profiles correspond well (98th percentiles R2=0.76, RMSE=3.4m). Finally, prospects for use of LiDAR in carbon accounting, assimilation within models and for forestry applications are discussed

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2): Science Requirements, Concept, and Implementation

The Ice, Cloud, and land Elevation Satellite (ICESat) mission used laser altimetry measurements to determine changes in elevations of glaciers and ice sheets, as well as sea ice thickness distribution. These measurements have provided important information on the response of the cryosphere (Earths frozen surfaces) to changes in atmosphere and ocean condition. ICESat operated from 2003-2009 and provided repeat altimetry measurements not only to the cryosphere scientific community but also to the ocean, terrestrial and atmospheric scientific communities. The conclusive assessment of significant ongoing rapid changes in the Earths ice cover, in part supported by ICESat observations, has strengthened the need for sustained, high accuracy, repeat observations similar to what was provided by the ICESat mission. Following recommendations from the National Research Council for an ICESat follow-on mission, the ICESat-2 mission is now under development for planned launch in 2018. The primary scientific aims of the ICESat-2 mission are to continue measurements of sea ice freeboard and ice sheet elevation to determine their changes at scales from outlet glaciers to the entire ice sheet, and from 10s of meters to the entire polar oceans for sea ice freeboard. ICESat carried a single beam profiling laser altimeter that produced approximately 70 m diameter footprints on the surface of the Earth at approximately 150 m along-track intervals. In contrast, ICESat-2 will operate with three pairs of beams, each pair separated by about 3 km across-track with a pair spacing of 90 m. Each of the beams will have a nominal 17 m diameter footprint with an along-track sampling interval of 0.7 m. The differences in the ICESat-2 measurement concept are a result of overcoming some limitations associated with the approach used in the ICESat mission. The beam pair configuration of ICESat-2 allows for the determination of local cross-track slope, a significant factor in measuring elevation change for the outlet glaciers surrounding the Greenland and Antarctica coasts. The multiple beam pairs also provide improved spatial coverage. The dense spatial sampling eliminates along-track measurement gaps, and the small footprint diameter is especially useful for sea surface height measurements in the often narrow leads needed for sea ice freeboard and ice thickness retrievals. The ICESat-2 instrumentation concept uses a low energy 532 nm (green) laser in conjunction with single-photon sensitive detectors to measure range. Combining ICESat-2 data with altimetry data collected since the start of the ICESat mission in 2003, such as Operation IceBridge and ESAs CryoSat-2, will yield a 15+ year record of changes in ice sheet elevation and sea ice thickness. ICESat-2 will also provide information of mountain glacier and ice cap elevations changes, land and vegetation heights, inland water elevations, sea surface heights, and cloud layering and optical thickness

Improved estimates of vegetation and terrain parameters from waveform LiDAR.

Light Detection And Ranging (LiDAR) technologies have evolved rapidly over the last decade, contributing to our knowledge of the Earth's surface evolution from local to global scales. A relatively young form of LiDAR is continuous waveform, which has not yet been fully exploited. The current research investigates and develops new methods, highlighting the potential and possible pitfalls of working with continuous waveform LiDAR. The first piece of research investigates the effects of shadowing in LiDAR waveforms in physically observed, large footprint LiDAR waveforms, based on previous works noting shadowing effects in radiative transfer models, and in a controlled environment experiment. For this investigation airborne LiDAR derived digital elevation models were employed in conjunction with spatially corresponding waveform returns to identify possible shadowing effects. It was found that shadows occur more frequently over more severely sloped terrain, affecting the accuracy of waveform derived vegetation parameters. The implications of shadows in waveform data are also discussed. The second piece of research develops and tests two methods, the Slope Screening Model and Independent Slope Model, such to determine ground slope information from LiDAR waveforms. Both methods were validated against discrete return airborne LiDAR data, and British Ordnance Survey data, such to identify winch method is most suited to retrieving slope. The third piece of research utilises the favoured method for slope prediction from the second r(\searc4i topic to correct vegetation height estimates for slope. Two methods (Lox' and modified) are investigated and tested, and validated against airborne LiDAR equivalent results at the regional scale, and against normalised difference vegetation index at the near global scale. Both correction methods produced statistically significant differences in mean global vegetation heights with regards to a control dataset

Profiling Sea Ice with a Multiple Altimeter Beam Experimental Lidar (MABEL)

The sole instrument on the upcoming ICESat-2 altimetry mission is a micropulse lidar that measures the time-of-flight of individual photons from laser pulses transmitted at 532 nm. Prior to launch, MABEL serves as an airborne implementation for testing and development. In this paper, we provide a first examination of MABEL data acquired on two flights over sea ice in April 2012: one north of the Arctic coast of Greenland, and the other in the East Greenland Sea.We investigate the phenomenology of photon distributions in the sea ice returns. An approach to locate the surface and estimate its elevation in the distributions is described, and its achievable precision assessed. Retrieved surface elevations over relatively flat leads in the ice cover suggest that precisions of several centimeters are attainable. Restricting the width of the elevation window used in the surface analysis can mitigate potential biases in the elevation estimates due to subsurface returns at 532 nm. Comparisons of nearly coincident elevation profiles from MABEL with those acquired by an analog lidar show good agreement.Discrimination of ice and open water, a crucial step in the determination of sea ice free board and the estimation of ice thickness, is facilitated by contrasts in the observed signal background photon statistics. Future flight lines will sample a broader range of seasonal ice conditions for further evaluation of the year-round profiling capabilities and limitations of the MABEL instrument