Search

NASA's ICESat‐2 mission measures Earth's elevation with the Advanced Topographic Laser Altimeter System (ATLAS), a 6‐beam photon‐counting laser altimeter. The Global Geolocated Photon data product (ATL03) is the primary source of photon information used by surface‐type‐specific higher‐level products, along with the Atmospheric Layer Characteristics product (ATL09). ATL03 provides time‐tagged, geolocated photon heights referenced to the ellipsoid and a parameter providing an initial classification of photon events as signal or background. We use this classification to evaluate ATLAS radiometry (number of signal photons per transmitted laser pulse) over short time scales and over the mission to date. The radiometric performance of ATLAS will in part determine what differences in the signal and background photon rates are significant and indicate geophysical, rather than instrumental, changes. We find the ATLAS radiometry is very stable over short time scales and exhibits a long‐term decrease of ∼1 signal photon per laser pulse (∼−12%) in the strong spots over the first 1.5 years of the mission.

The Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) launched on September 15th, 2018 and this mission offers an extraordinary opportunity to contribute to an assessment of forest resources at multiple spatial scales. This study served to develop a methodology for utilizing ICESat-2 data over vegetated areas. The specific objectives were to: (1) derive a simulated ICESat-2 photon-counting lidar (PCL) vegetation product using airborne lidar data, (2) examine the use of simulated PCL metrics for modelling aboveground biomass (AGB) along ICESat-2 profiles using a simulated ICESat-2 PCL vegetation product and reference AGB estimated from airborne lidar data, and (3) estimate forest canopy cover using simulated PCL canopy product data and airborne lidar-derived canopy cover. Using existing airborne lidar data for Sam Houston National Forest (SHNF) in Texas and known ICESat-2 track locations, PCL simulations were carried out. Three scenarios were analyzed in this study; 1) simulated data without the addition of noise, 2) processed simulated data for daytime, and 3) nighttime scenarios. Segments measuring 100 m along the proposed ICESat-2 tracks were used to extract simulated PCL metrics from each of the three data scenarios and spatially coincident, reference airborne lidar-estimated AGB and airborne lidar canopy cover estimates. Linear regression models were then developed with a subset of the simulated PCL segments to estimate AGB and canopy cover and their performance assessed using separate testing sets. AGB model testing with the simulated dataset without noise, nighttime and daytime scenarios resulted in R2 values of 0.79, 0.79 and 0.63 respectively, with root mean square error (RMSE) values of 19.16 Mg/ha, 19.23 Mg/ha, and 25.35 Mg/ha. Predictive models for canopy cover (4.6 m) achieved R2 values of 0.93, 0.75 and 0.63 and RMSE values of 6.36%, 12.33% and 15.01% for the simulated dataset without noise, nighttime and daytime scenarios respectively. Findings from this study suggest the potential of ICESat-2 for estimating AGB, given the photon detection rate and background noise anticipated by ICESat-2 under temperate forest settings, and especially in the data format provided by standard ICESat-2 data vegetation products.

A first look at data from NASA’s laser altimeter mission ICESat-2 reveals very high resolution 3-D profiles of ice on land and sea, forests, and shallow bodies of water.

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) and its sole scientific instrument, the Advanced Topographic Laser Altimeter System (ATLAS), was launched on 15 September 2018 with a primary goal of measuring changes in the surface of the Earth's land ice (glaciers and ice sheets). ATLAS is a photon-counting laser altimeter, which records the transit time of individual photons in order to reconstruct surface height along track. The ground-track pattern repeats every 91 days such that changes in ice sheet surface height can be estimated through time. In this paper, we describe the set of algorithms that have been developed for ICESat-2 to retrieve ice sheet surface height from the geolocated photons for the Land Ice Along-Track Height Product (ATL06), and demonstrate their output and performance using a synthetic dataset over various land-ice surfaces and under different cloud conditions. We show that the ATL06 algorithm is expected to perform at the level required to meet the ICESat-2 science objectives for land ice.

The Ice, Cloud, and land Elevation Satellite – 2 (ICESat-2) observatory was launched on 15 September 2018 to measure ice sheet and glacier elevation change, sea ice freeboard, and enable the determination of the heights of Earth’s forests. ICESat-2’s laser altimeter, the Advanced Topographic Laser Altimeter System (ATLAS) uses green (532 nm) laser light and single-photon sensitive detection to measure time of flight and subsequently surface height along each of its six beams. In this paper, we describe the major components of ATLAS, including the transmitter, the receiver and the components of the timing system. We present the major components of the ICESat-2 observatory, including the Global Positioning System, star trackers and inertial measurement unit. The ICESat-2 Level 1B data product (ATL02) provides the precise photon round-trip time of flight, among other data. The ICESat-2 Level 2A data product (ATL03) combines the photon times of flight with the observatory position and attitude to determine the geodetic location (i.e. the latitude, longitude and height) of the ground bounce point of photons detected by ATLAS. The ATL03 data product is used by higher-level (Level 3A) surface-specific data products to determine glacier and ice sheet height, sea ice freeboard, vegetation canopy height, ocean surface topography, and inland water body height.