Radiometric Assessment of ICESat-2 over Vegetated Surfaces

Abstract

The ice, cloud, and land elevation satellite-2 (ICESat-2) is providing global elevation measurements to the science community. ICESat-2 measures the height of the Earth’s surface using a photon counting laser altimeter, ATLAS (advanced topographic laser altimetry system). As a photon counting system, the number of reflected photons per shot, or radiometry, is a function primarily of the transmitted laser energy, solar elevation, surface reflectance, and atmospheric scattering and attenuation. In this paper, we explore the relationship between detected scattering and attenuation in the atmosphere against the observed radiometry for three general forest types, as well as the radiometry as a function of day versus night. Through this analysis, we found that ATLAS strong beam radiometry exceeds the pre-launch design cases for boreal and tropical forests but underestimates the predicted radiometry over temperate forests by approximately half a photon. The weak beams, in contrast, exceed all pre-launch conditions by a factor of two to six over all forest types. We also observe that the signal radiometry from day acquisitions is lower than night acquisitions by 10% and 40% for the strong and weak beams, respectively. This research also found that the detection ratio between each beam-pair was lower than the predicted 4:1 values. This research also presents the concept of ICESat-2 radiometric profiles; these profiles provide a path for calculating vegetation structure. The results from this study are intended to be informative and perhaps serve as a benchmark for filtering or analysis of the ATL08 data products over vegetated surfaces.

ICESat-2 for Canopy Cover Estimation at Large-Scale on a Cloud-Based Platform

“…Although prior research reveals that beams with high energy levels have been more effective in estimating tree height than weak beams, our study yielded contrasting results despite employing a different set of stand parameters. This highlights the need to conduct similar evaluations in diverse study areas to understand better the role of energy levels and other factors in improving the accuracy of canopy cover estimations [ 84 , 85 ]. Because of this, accuracies of canopy cover estimations by segments from different energy levels were also calculated for smaller-scaled sample fields that were previously used to examine the impact of different vegetation indices, and it was confirmed that eliminating any energy level segments from the analysis had no positive effect on estimations.…”

PhoREAL: increasing spatial and temporal data accessibly of ICESat-2 through open-source Python repository

“…Landcover derived from Copernicus), whereas others are calculated within PhoREAL based upon the photon labels. All calculations executed within PhoREAL are made in the same manner as the official ATL08 data product and described in the ATL08 Algorithm Theoretical Basis Document (ATBD) [3].…”

“…The algorithm estimates the ground surface and top of canopy surface elevations based on the distribution of signal photons. The algorithm then labels the individual photons as either noise, ground, canopy, or top of canopy photons [3]. Statistics for both terrain and canopy detections are reported at the 100-meter step size based on the photon label.…”

Improved Mapping of Regional Forest Heights by Combining Denoise and LightGBM Method

“…The ATL08 product (V005) between April 2019 and September 2021 was downloaded by visiting the National Snow and Ice Data Center (NSIDC; https://nsidc.org/data/icesat-2, accessed on 20 March 2023). Here, we used h_canopy as the height estimation metric, which can represent 98% of the relative height during the energy return, and RH98 can characterize the top height of the canopy instead of the RH100 due to the high signal-to-noise ratio at the top of canopy [67]. In addition, a number of metrics were extracted to ensure the accuracy of the data, including longitude (longitude), latitude (latitude), best-fit terrain (h_te_best_fit), terrain uncer- The HLS project [53] provides consistent surface reflectance (SR) data by coordinating the Landsat8-OLI and the Multi-Spectral Instrument (Sentinel2-MSI) to enable short-period, full-coverage, and high-resolution global terrestrial observations.…”