ICESat-2 Precision Orbit Determination Performance

NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) Kd(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and Kd(490) in the range of 0.05–0.12 m−1. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.

Spaceborne sensors are now providing invaluable datasets for the Earth’s surface studies. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) with the Advanced Topographic Laser Altimeter System (ATLAS) was launched by NASA on 15 September 2018, to measure the elevation of the Earth’s surface using a laser wavelength of 532 nm and pulse repetition frequency of 10 kHz giving a footprint of approximately 70 cm on the ground. The ICESat-2 datasets are used in this study for the visualization and investigation of the complex Himalayan terrain in the parts of the Kinnaur district and surroundings, which are prone to frequent landslides due to the geology of the region as observed during the recent landslide events. The ICESat-2 elevation datasets were compared with the openly accessible DEM datasets namely, ALOS PALSAR RTC HR (12.5 m) and TanDEM-X (90 m) at ICESat-2 footprint locations. The preprocessing of datasets was completed for selecting ICESat-2 footprints (Track ID: 325, 1270, 828, 386) at locations of high-quality datasets for analysis. The analysis of pre-processed 19,755 ICESat-2 footprints (out of 20,948 footprints) was performed with ALOS PALSAR RTC HR (12.5 m) and TanDEM-X (90 m) datasets. The visualization of the region in the Google earth and OpenAltimetry 3D viewer depicts that the mountain slopes are very steep indicating rugged terrain difficult to access and challenging for construction of transport facilities. The results of Track ID: 325, show that the range of elevations in ICESat-2 elevation values in the study area is from 3409.75 m to 5976.31 m. The standard deviation representing terrain ruggedness using ICESat-2 elevation values is found as 432.06 m. Considering higher accuracy ICESat-2 values for the difficult terrain as a reference, the mean error (ME), mean absolute error (MAE), and RMSE for TanDEM-X were found as 0.26 m, 12.92 m, and 17.4 m, respectively. Whereas the ME, MAE, and RMSE for ALOS PALSAR RTC HR DEM were found as 0.20 m, 9.50 m, and 13.88 m, respectively. Thus, for the study site, using ICESat-2 ATL06 products, ALOS PALSAR RTC HR DEM is found more suitable than TanDEM-X 90 m openly accessible datasets for any kind of application in such a terrain.

<p>Bathymetric measurement using remotely sensed data acquired in shallow-water marine contexts generally incurs challenges regardless of acquisition method. Multibeam sonar can be challenged with respect to survey vessel access and diminishing swath width, Airborne Laser Bathymetry is often affected by nearshore wave action and turbidity, and Satellite Derived Bathymetry can be complicated by local variations in water-column backscatter and bottom reflectance.</p><p>The NASA ICESat-2 (Ice, Cloud and Land Elevation Satellite-2) acquires elevation data for the global monitoring of temporal elevation change in ice caps, glaciers, sea ice and forests. The ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) issues three along-track parallel pairs of laser beams set 3.3km apart at a Pulse Repetition Frequency of 10,000 points per second (equivalent to 0.7m ground resolution). Returning photons (approximately 10 only are required from the trillions of photons within each laser pulse) are captured as returns from 1387 orbit tracks, which repeat every 31 days. While the ATLAS instrument is not intended for bathymetric measurement, ATLAS Global Geolocated Photon data (ATL-03) acquired over water may include laser returns from the seabed. Evaluation by the ICESat-2 research team indicates the potential for bathymetric measurement to depths of 30m in sub-tropical waters. ICESat-2 bathymetric measurement errors of approximately 0.5m RMSE were highlighted using ALB reference data, with a sub-decimetre error component attributable to laser refraction beyond 30m.</p><p>The EO-Intertide project, based at Dublin City University in Ireland and funded by the Irish Geological Survey research programme, is evaluating the potential for bathymetric inference using ICESat-2 data acquired across a wide range of seabed conditions around the entire Irish coast. Initial results demonstrate the potential for bathymetric measurement from ICESAT-2 to depths of between 5 and 20 metres, depending upon seabed sediment type and exposure to ocean swell conditions. A repeatable method is applied within the EO-Intertide project to extract bathymetric ATL-03 photon returns, using ATL-03 photon confidence scores in conjunction with a 3D spatial-data selection approach and a custom local elevation filter.</p><p>The elevation accuracy of the extracted ICESat-2 bathymetric profiles are validated using  combination of published Multibeam Echosounder (MBES) and airborne Laser Bathymetry (ALB) data acquired under the Integrated Mapping For the Sustainable Development of Ireland's Marine Resource (INFOMAR) project. INFOMAR is the seabed mapping programme jointly operated by Geological Survey Ireland and the Marine Institute. It is anticipated that extracted ICESAT-2 bathymetric profiles will provide a valuable input to EO-Intertide nearshore / intertidal bathymetric model generation from Sentinel-2 tidal-shoreline extractions and Satellite Derived Bathymetry (SDB). Validated bathymetric models issuing from this process will subsequently be applied as an input to the analysis of nearshore sediment dynamics within the Dublin City University PREDICT research project, to which the EO-Intertide project is allied.</p>

With a planned launch no later than September 2018, the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) will provide a global distribution of geodetic elevation measurements for both the terrain surface and relative canopy heights. The Advanced Topographic Laser Altimeter System (ATLAS) instrument on-board ICESat-2 is a LiDAR system sensitive to the photon level. The photon-counting technology has many advantages for space-based altimetry, but also has challenges, particularly with delineating the signal from background noise. As such, a current unknown facing the ecosystem community is the performance of ICESat-2 for terrain and canopy height retrievals. This paper aims to provide the science user community of ICESat-2 land/vegetation data products with a realistic understanding of the performance characteristics and potential uncertainties related to the vertical sampling error, which includes the error in the perceived height value and the measurement precision. Terrain and canopy heights from simulated ICESat-2 data are evaluated against the airborne LiDAR ground truth values to provide a baseline performance uncertainty for multiple ecosystems. Simulation results for wooded savanna and boreal forest result in a mean bias error and error uncertainty (precision) for terrain height retrievals at 0.06 m (0.24 m RMSE) and −0.13 m (0.77 m RMSE). In contrast, results over ecosystems with dense vegetation show terrain errors of 1.93 m (1.66 m RMSE) and 2.52 m (3.18 m RMSE), indicating problems extracting terrain height due to diminished ground returns. Simulated top of canopy heights from ICESat-2 underestimated true top of canopy returns for all types analyzed with errors ranging from 0.28 m (1.39 m RMSE) to 1.25 m (2.63 m RMSE). These results comprise a first step in a comprehensive evaluation of ICESat-2 anticipated performance. Future steps will include solar noise impact analysis and investigation into performance discrepancy between visible and near-infrared wavelengths.

The Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) has been making very high resolution measurements of the Earth’s surface elevation since October 2018. ATLAS uses photomultiplier tubes (PMTs) as detectors in photon counting mode, so that a single photon reflected back to the receiver triggers a detection within the ICESat‐2 data acquisition system. However, one characteristic of ICESat‐2 detected photons is the possible presence of afterpulses, defined as small amplitude pulses occurring after the primary signal pulse due to photon arrival. The disadvantage of these afterpulses is that they often confound the accurate measurements of low level signals following a large amplitude of signal and can degrade energy resolution and cause errors in pulse counting applications. This paper discusses and summarizes the after‐pulsing effects exhibited by the ATLAS PMTs based on on‐orbit measurements over different seasons and geographic regions. The potential impacts of these after‐pulsing effects on altimetry and ocean subsurface retrievals are discussed.

The present study aims to estimate the height of smoke aerosols and clouds from the Advanced Topographic Laser Altimeter System (ATLAS) instrument sensor onboard the Ice, Cloud and land Elevation Satellite-2 (ICESat-2). The study was conducted during the dry season on September 14th of 2020, when there was a large number spot of biomass burning fires and smoke aerosol layers over the Amazon and the South American region. Most often, the smoke plumes move with southward winds, along the east of the Andes. During this period occasionally polar cold fronts move from the south, meeting the smoke aerosol layers. Initially, daily images from the polar orbit satellites such as Terra, Aqua, NOAA and Suomi were used to identify the spatial location of smoke plumes and clouds over the region. Then, ICESat-2 tracks were analyzed to evaluate their presence in the study area. The results show that ICESat-2 data retrieval is able to estimate the height of the aerosol layer and the top of the cloud. Some tracks show clearly higher clouds, with tops reaching about 12-13 km, when there is the presence of a cold front or deep convective cumulonimbus. Over clear sky regions where smoke is observed, estimated heights from the lidar are on the order of 3-4 km. Local profiles of temperature obtained from radiosondes show inversion layers at similar heights as detected by the lidar sensor. These inversion layers seem to be associated with the warming effect of the absorbing biomass burning aerosols.

Due to the lack of in-situ gauge data, remote sensing is crucial for water level monitoring. This study presents a thorough examination of water level variations in nine main Sri Lankan reservoirs over the past five years, using data from the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) Advanced Topographic Laser Altimeter System (ATLAS). An initial data filtering was done focusing on key quality flags in ICESat-2 ATL13 products to ensure data reliability by eliminating outliers and significant elevation errors. An approach to assessing uncertainty in satellite-derived elevation readings is introduced, using photon counts to quantify uncertainty and enhance data interpretation. The evaluation of ICESat-2 data, in comparison to gauge measurements of nine reservoirs, confirms ICESat-2's higher accuracy in water level estimation, yielding a correlative coefficient as high as 0.99 for all reservoirs, though it has a low temporal resolution of 91 days.This study highlights the potential of ICESat-2 for comprehensive water level measuring in small reservoirs, offering valuable insights for effective water resource management and hydrological modelling efforts. Furthermore, the developed methodology can be used for reservoir water level measuring, highlighting the advantage of satellite products, especially in data-scarce regions.

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), featuring the advanced topographic laser altimeter system (ATLAS), pioneered spaceborne photon-counting LiDAR technology. The first spaceborne laser system in Earth’s orbit with water detection capabilities, offers a more direct approach for charting the bathymetry and underwater topography in coastal waters. However, the refraction effect of water column on light is not taken into account by ATLAS products, which will cause the position change of signal photons on the seafloor, consequently reducing the precision of nearshore bathymetry and underwater topography mapping. In the previous studies, the fluctuation water surface has been assumed as the plane to achieve the water refraction correction. In this process, the water incident angle, refraction angle and water refraction direction are same for all seafloor photons, which decreases the accuracy of the photon position and the nearshore bathymetry. Therefore, we present an innovative method for addressing refraction correction by tracking the trajectory of individual photons on the seafloor and reconstructing sea-wave profiles to achieve high-accuracy refraction correction for ATLAS data. In this method, the instantaneous sea wave has been modeled using the extracted signal photon of water surface and the proposed weight cubic polynomial model. Further, the corresponding various incident and refraction angles of each seafloor photon were accurately obtained to calculate various the displacement quantity and direction. Moreover, a coordinate correction model was introduced to aim at enhancing the accuracy of photon coordinates on the seafloor and mapping of underwater topography. Validation results demonstrate that the proposed method for refraction correction effectively enhances the bathymetric precision. The maximum depth displacement corrected in the study area reached 5.46 m, occurring at a water depth of 16.01 m. In the along-track direction, there was a range of maximum displacements from -0.54 to 0.47 m, while the maximum relative displacement reached 1.01 m, significantly exceeding the displacement observed in the cross-track direction.

Since its launch in 2018, the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission has provided atmospheric products, including calibrated backscatter profiles and cloud and aerosol layer detection. While not the primary focus of the mission, these products garnered more interest after the end of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) data collection in 2023. In comparing the cloud and aerosol detection frequencies from CALIOP and ICESat-2, we find general agreement in the global patterns. The global cloud detection frequencies were similar in June, July, and August of 2019 (64.7% for ICESat-2 and 59.8% for CALIOP), as were the location and altitude of the tropical maximum; however, low daytime signal-to-noise ratios (SNRs) reduced ICESat-2’s detection frequencies compared to those of CALIOP. The ICESat-2 global aerosol detection frequencies were likewise lower. ICESat-2 generally retrieved a higher average global aerosol optical depth compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) over the ocean, but the two were in closer agreement over regions with higher aerosol concentrations such as the Eastern Atlantic Ocean and the Northern Indian Ocean. The ICESat-2 and CALIOP orbital coincidences reveal highly correlated backscatter profiles as well as similar cloud and aerosol layer top altitudes. Future work with machine learning denoising techniques may allow for improved feature detection, especially during daytime.

The water surface slope (WSS) of rivers is essential for estimating flow velocity and discharge. It is also helpful as a correction applied to range measurements of satellite altimetry missions to derive water level time series at a virtual station. Using radar altimetry, WSS can only be roughly estimated and is limited to wide rivers because of its coarse spatiotemporal resolution. In contrast, the lidar sensor onboard Ice, Cloud, and Land Elevation Satellite 2 (ICESat‐2) can also observe small rivers. Using ICESat‐2's unique measurement geometry with six parallel laser beams, we derive instantaneous WSS along and across the satellite's ground track, time‐variable WSS (with an average of 5 days of records in the studied epoch between October 2018 and October 2021), and average WSS on reach‐scale. Although the method can be applied globally, this study is limited to 815 reaches in Europe and North America where sufficient validation data is available. We compare the ICESat‐2 WSS with time‐variable WSS derived from multiple gauges and constant data from the “SWOT River Database.” For 89% of the studied reaches, ICESat‐2 can be used to estimate the average WSS with a median absolute error of 23 mm/km. We also show the possible performance gain at multiple virtual stations (VS) in the “Database for Hydrological Time Series of Inland Waters” (https://dahiti.dgfi.tum.de), applying the WSS as a correction for altimetry satellites' ground track variability. We correct 137 VS for the derived ICESat‐2 WSS and yield improvements in the root mean square error by up to 30 cm or 66%.

Surface elevation and roughness measurements from NASA's Ice, Cloud, and land Elevation Satellite (ICESat) are compared with high-resolution airborne laser altimeter measurements over the Arctic sea ice north of Alaska, which were taken during the March 2006 EOS Aqua Advanced Microwave Scanning Radiometer sea ice validation campaign. The comparison of the elevation measurements shows that they agree quite well with correlations of around 0.9 for individual shots and a bias of less than 2 cm. The differences are found to decrease quite rapidly when applying running means. The comparison of the roughness measurements show that there are significant differences between the two data sets, with ICESat generally having higher values. The roughness values are only moderately correlated on an individual-shot basis, but applying running means to the data significantly improves the correlations to as high as 0.9. For the conversion of the elevation measurements into snow-ice freeboard, ocean surface elevation estimates are made with the high-resolution laser altimeter data, as well as several methods using lower resolution ICESat data. Under optimum conditions, i.e., when leads that are larger than the ICESat footprint are present, the ICESat- and Airborne Topographic Mapper-derived freeboards are found to agree to within 2 cm. For other areas, ICESat tends to underestimate the freeboard by up to 9 cm.

Abstract. We present new coarse resolution (0.5° × 0.5°) vegetation height and vegetation-cover fraction data sets between 60° S and 60° N for use in climate models and ecological models. The data sets are derived from 2003–2009 measurements collected by the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat), the only LiDAR instrument that provides close to global coverage. Initial vegetation height is calculated from GLAS data using a development of the model of Rosette et al. (2008) with with further calibration on desert sites. Filters are developed to identify and eliminate spurious observations in the GLAS data, e.g. data that are affected by clouds, atmosphere and terrain and as such result in erroneous estimates of vegetation height or vegetation cover. Filtered GLAS vegetation height estimates are aggregated in histograms from 0 to 70 m in 0.5 m intervals for each 0.5° × 0.5°. The GLAS vegetation height product is evaluated in four ways. Firstly, the Vegetation height data and data filters are evaluated using aircraft LiDAR measurements of the same for ten sites in the Americas, Europe, and Australia. Application of filters to the GLAS vegetation height estimates increases the correlation with aircraft data from r = 0.33 to r = 0.78, decreases the root-mean-square error by a factor 3 to about 6 m (RMSE) or 4.5 m (68% error distribution) and decreases the bias from 5.7 m to −1.3 m. Secondly, the global aggregated GLAS vegetation height product is tested for sensitivity towards the choice of data quality filters; areas with frequent cloud cover and areas with steep terrain are the most sensitive to the choice of thresholds for the filters. The changes in height estimates by applying different filters are, for the main part, smaller than the overall uncertainty of 4.5–6 m established from the site measurements. Thirdly, the GLAS global vegetation height product is compared with a global vegetation height product typically used in a climate model, a recent global tree height product, and a vegetation greenness product and is shown to produce realistic estimates of vegetation height. Finally, the GLAS bare soil cover fraction is compared globally with the MODIS bare soil fraction (r = 0.65) and with bare soil cover fraction estimates derived from AVHRR NDVI data (r = 0.67); the GLAS tree-cover fraction is compared with the MODIS tree-cover fraction (r = 0.79). The evaluation indicates that filters applied to the GLAS data are conservative and eliminate a large proportion of spurious data, while only in a minority of cases at the cost of removing reliable data as well. The new GLAS vegetation height product appears more realistic than previous data sets used in climate models and ecological models and hence should significantly improve simulations that involve the land surface.

Refraction and coordinate correction with the JONSWAP model for ICESat-2 bathymetry

Assessing the societal impact of satellite remote sensing datasets is essential to understanding how these data influence decision-making and to identifying opportunities for further engagement. However, measuring such impacts remains challenging for missions serving diverse stakeholder communities. In this study, we evaluate the broader impact of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) and its successor mission, ICESat-2 by adapting the scientific impact framework (SIF), originally developed to assess public health research, into an Earth science-specific version (e-SIF). This framework captures data dissemination, community awareness, data-driven actions, measurable changes, and future influence, moving beyond traditional academic metrics to assess the missions' reach and effectiveness. Our findings reveal extensive global usage of ICESat and ICESat-2 data, with applications including, but not limited to, shallow water bathymetry, climate mitigation strategies, and forest management. By comparing the prevalence of topical areas in academic literature to real-world applications, we found that althoughthe cryosphere is the most frequently studied domain, differences between research focus and practical use highlight potential areas where further research could better support stakeholders. We found that ICESat and ICESat-2 data are widely employed by national and international governmental and non-governmental organizations but found only limited use by private sector and local governments. We recommend that the ICESat-2 Applications Team expand outreach efforts to these sectors to enhance dissemination of mission data. Furthermore, numerous ICESat-2 applications benefit from long-term data continuity, reinforcing the need for a successor mission. This study demonstrates the feasibility to use e-SIF to evaluate the impact of Earth science missions. • This study involves an innovative application of the CDC Scientific Impact Framework. • ICESat and ICESat-2 provide global altimetry data that empowers diverse applications. • Application topics vary between the academic and broader stakeholder communities. • The study models methods of how to examine real-world outcomes in the Earth sciences. Open scientific data empowers diverse communities to generate knowledge and insights that support decision-making across public policy, economic planning, and environmental management. Through Earth-observing missions, NASA aims to improve scientific understanding of our planet's current state and possible future changes. The NASA missions Ice, Cloud, and land Elevation Satellite (ICESat) and ICESat-2 have contributed to this effort by providing highly accurate elevation data using laser altimetry. In this study, we examined the impact of these missions beyond the academic community to identify key stakeholders and assess how these missions influence decision-making. To do so, we modified the Centers for Disease Control and Prevention's (CDC) Scientific Impact Framework (SIF), originally designed to evaluate public health research, to create an Earth science relevant SIF (e-SIF) in order to discover and analyze the applications of Earth science missions beyond the academic sector. Our findings show that these data products have had a strong policy impact at the intergovernmental level but have been used less frequently by local governments and corporations. Moreover, we observed notable differences between the scientific topics emphasized in academic literature and those found in reports and real-world applications. This study highlights the importance of evaluating how scientific research translates into real-world impacts, including for technological advancements, policy changes, economic effects, and more. As ICESat-2 approaches the end of its mission, ensuring data continuity is critical to supporting current and future applications that rely on these observations.

The new generation of satellite-borne laser radar Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data has been successfully used for ground information acquisition. However, when dealing with complex terrain and dense vegetation cover, the accuracy of the extracted understory Digital Terrain Model (DTM) is limited. Therefore, this paper proposes a photon correction data processing method based on ICESat-2 to improve the DTM inversion accuracy in complex terrain and high forest coverage areas. The correction value is first extracted based on the ALOS PALSAR DEM reference data to correct the cross-track photon data of ICESat-2. The slope filter threshold is then selected from the reference data, and the extracted possible ground photons are slope filtered to obtain accurate ground photons. Finally, the impacts of cross-track photon and slope filtering on fine ground extraction from the ICESat-2 data are discussed. The results show that the proposed photon correction and slope filtering algorithms help to improve the extraction accuracy of forest DTM in complex terrain areas. Compared with the forest DTM extracted without the photon correction and slope filtering methods, the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) are reduced by 51.90~57.82% and 49.37~53.55%, respectively. To the best of our knowledge, this is the first study demonstrating that photon correction can improve the terrain inversion ability of ICESat-2, while providing a novel method for ground extraction based on ICESat-2 data. It provides a theoretical basis for the accurate inversion of canopy parameters for ICESat-2.