Enabling Value Added Scientific Applications of ICESat‐2 Data With Effective Removal of Afterpulses

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Vaughan, Mark; Palm, Stephen P.; Trepte, Charles; Omar, Ali; Lucker, Patricia L.; Baize, Rosemary R.

doi:10.1029/2021ea001729

Cited by 27 publications

(21 citation statements)

References 18 publications

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“…In some low-signal cases, not every transmitted laser pulse has associated signal photons. Conversely, in highly reflective geophysical conditions, all available ATLAS detector elements may detect photons within a short period of time (∼3 nanoseconds) and cannot immediately record additional photon events in a pulse (Lu et al, 2021;Martino et al, 2019;Neumann et al, 2019). Any laser pulse that has 16 photons in a strong beam or 4 photons in a weak beam within 0.5 m of height is considered saturated and is not considered further.…”

Section: Signal Photons Per Pulsementioning

confidence: 99%

On‐Orbit Radiometric Performance on ICESat‐2

Gibbons¹,

Neumann

Hancock³

et al. 2021

Earth and Space Science

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The Ice, Cloud, and land Elevation Satellite -2 (ICESat-2) observatory launched on September 15, 2018 with objectives to measure changes in ice sheet elevation, monitor sea ice freeboard, and enable a global assessment of vegetation and canopy height (Markus et al., 2017). ICESat-2 uses green laser light emitted by the Advanced Topographic Laser Altimeter System (ATLAS) as the basis for elevation measurements between 88° north and south latitudes (Martino et al., 2019). ATLAS provides the data necessary for ground processing to calculate the round-trip photon time-of-flight from the observatory to Earth and back again. These components are combined with the laser beam pointing vectors (Bae & Webb, 2017) and the position of the observatory in space (Luthcke et al., 2019) to generate the Global Geolocated Photon data product (ATL03) (Neumann et al., 2020a(Neumann et al., , 2020b) which provides a unique latitude, longitude, and elevation for each photon event telemetered for ground processing and an initial discrimination between a band of signal photons (emitted by ATLAS and reflected by Earth) and background photons (emitted by the sun in the same part of the electromagnetic spectrum). Schematics of the ATLAS transmitter and receiver are found in Neumann et al., 2019, Figures 2 and 3 respectively.The ATLAS telescope collects incoming light and is fiber-coupled to filters which only transmit light of the same wavelength as emitted by ATLAS (532 nm ± 0.15) (Neumann et al., 2019). After passing through these filters, light for a given spot is distributed across the elements of a multi-element photomultiplier tube to convert optical energy to electrical energy to be time tagged (a photon event) for further analysis. The ATL03 product is organized by ground tracks, which refer to the relative location of the 6 beams on the ground. Since the spacecraft orientation changes every ∼9 months in order to optimize the position of the solar array relative to the sun, ATLAS strong and weak spots change their relative orientation (from left to right). We organize our analyses by ATLAS spots which do not change with spacecraft orientation. ATLAS spots are numbered 1-6 indicating laser illumination from the instrument field of view, where 1, 3, and 5 are "strong" spots and have four times the energy of spots 2, 4, and 6, referred to as "weak" spots. Each of the three ATLAS strong spots have 16 detection elements (pixels) which supply 16 individual timing channels. Similarly, each of the three ATLAS weak spots have four independent pixels and timing channels (Martino Abstract 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 higherlevel products, along with the Atmospheric Layer Characteristics product (ATL09). ATL03 provides time-tagged, geolocated photon heights referenced to the ellipsoid and a paramete...

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Section: Signal Photons Per Pulsementioning

confidence: 99%

On‐Orbit Radiometric Performance on ICESat‐2

Gibbons¹,

Neumann

Hancock³

et al. 2021

Earth and Space Science

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“…In addition, the ICESat-2-detected photon events over ocean regions provide great opportunity for ocean subsurface studies (Lu et al, 2019;Lu, Hu, Yang, et al, 2020). Details on ocean subsurface properties retrieval methods, including a dedicated deconvolution method to remove ICESat-2 after pulsing effects (e.g., Figure S6), are given in the work of Lu, Hu, Vaughan, et al (2020), Lu, Hu, Yang, et al (2020), Lu, Hu, Yang, et al (2021 and Text S2. Figure S7 gives the concept and schematic flow chart of applying ICESat-2 ATL03 data for ocean subsurface optical properties' retrieval.…”

Section: Atlas Data and Methodsmentioning

confidence: 99%

“…Here, we focus on retrieving ocean subsurface optical properties using both CALIOP and ATLAS measurements. For both systems, measurement artifacts such as CALIOP's polarization crosstalk (Lu, Hu, Omar, et al, 2021) (Text S1) and the ATLAS's after-pulsing effects (Lu, Hu, Yang, et al, 2021) (Text S2) are removed in order to obtain reliable ocean subsurface results. The cross-polarization component of the ocean subsurface backscatter (  w , sr −1 ), subsurface depolarization ratio (  sub ), and particulate backscattering coefficient (b bp , m −1 ) are retrieved globally from the CALIOP version 4.1 level 1b (L1) data product (Getzewich et al, 2018;Kar et al, 2018).…”

mentioning

confidence: 99%

New Ocean Subsurface Optical Properties From Space Lidars: CALIOP/CALIPSO and ATLAS/ICESat‐2

Yang

et al. 2021

Earth and Space Science

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Ocean color remote sensing entered a new era with the launch of the National Aeronautics and Space Administration (NASA) Coastal Zone Color Scanner in 1978 (C. W. Sullivan et al., 1993). For the first time, maps of phytoplankton biomass (chlorophyll)-a key measurement of marine ecosystems-could be produced from space-based observations, with the potential for daily to interannual observations at ocean basin scales. Regional to global maps of phytoplankton chlorophyll and other products derived from satellite measurements of water-leaving radiance are now accessible to users all over the world and have become an essential tool for the study and analysis of ocean biogeochemistry and ocean ecosystems. For decades, ocean color remote sensing has led to unprecedented scientific understanding in global ocean biology and biogeochemistry (Blondeau-Patissier et al., 2014;Brown et al., 1985;Dickey et al., 2006). However, because previous ocean color measurements have relied solely on passive remote sensing techniques, the data coverage is limited to the uppermost portion of the water column and is unable to resolve the underlying vertical structure (Hostetler et al., 2018;Jamet et al., 2019). Moreover, passive sensors (e.g., the MODerate-resolution Imaging Spectroradiometer, MODIS) only provide ocean color records during daytime. As a result, vast ocean areas in high latitudes during polar nights remain unsampled and places for which data are available typically provide information for only a few months in each calendar year.Estimates of global phytoplankton distributions from a space-based lidar were first demonstrated using measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) (Behrenfeld et al., 2013). CALIOP is a dual-wavelength (532 and 1,064 nm), polarization sensitive (at 532 nm) elastic backscatter lidar that has been making measurements from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite since June 2006(Hunt et al., 2009Winker et al., 2009). Using the CALIOP depolarization ratio measurements at 532 nm together with colocated A-Train measurements, such as Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) wind speeds and MODIS diffuse attenuation coefficients (k d , m −1 ), innovative retrieval methods have been developed to translate the CALIOP ocean backscattered signals into ocean optical properties, such as the particulate backscatter coefficient (b bp , m −1 ) (

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“…Data used in deriving bbp from CALIPSO comes from NASA/ CNES's LiDAR Level 1B profile data, Version 4-10 product (Winker et al, 2009). For the majority of this assessment, we followed Behrenfeld et al (2013), implementing changes that have come about over the last decade to improve the reliability of the results (Lu et al, 2013;2021b;Bisson et al, 2021). A schematic of how b bp is derived from CALIPSO is shown in Figure 1.…”

Section: Calispo B Bpmentioning

confidence: 99%

“…At every point along the satellite track, the co-polarized and cross-polarized channel returns are extracted. A cross-talk correction between the two channels is implemented and the transient response from the surface is removed (Lu et al, 2014;2021b). The corrected signal is then used to calculate a depolarization ratio (δ t ) between the two channels for the first three bins below the surface of the water.…”

Section: Calispo B Bpmentioning

confidence: 99%

Assessment of using spaceborne LiDAR to monitor the particulate backscatter coefficient on large, freshwater lakes: A test using CALIPSO on Lake Michigan

Watkins

Sayers²,

Shuchman³

et al. 2023

Front. Remote Sens.

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The Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite was launched in 2006 with the primary goal of measuring the properties of clouds and aerosols in Earth’s atmosphere using LiDAR. Since then, numerous studies have shown the viability of using CALIPSO to observe day/night differences in subsurface optical properties of oceans and large seas from space. To date no studies have been done on using CALIPSO to monitor the subsurface optical properties of large, freshwater-lakes. This is likely due to the limited spatial resolution of CALIPSO, which makes the mapping of subsurface properties of regions smaller than large seas impractical. Still, CALIPSO does pass over some of the world’s largest, freshwater-lakes, yielding important information about the water. Here we use the entire CALIPSO data record (approximately 15 years) to measure the particulate backscatter coefficient (bbp, m−1) across Lake Michigan. We then compare the LiDAR derived values of bbp to optical imagery values obtained from MODIS and to in situ measurements. Critically, we find that the LiDAR derived bbp aligns better in non-summer months with in situ values when compared to the optically imagery. However, due to both high cloud coverage and high wind speeds on Lake Michigan, this comes with the caveat that the CALIPSO product is limited in its usability. We close by speculating on the roll that spaceborne LiDAR, including CALIPSO and other satitlites, have on the future of monitoring the Great Lakes and other large bodies of fresh water.

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Enabling Value Added Scientific Applications of ICESat‐2 Data With Effective Removal of Afterpulses

Cited by 27 publications

References 18 publications

On‐Orbit Radiometric Performance on ICESat‐2

On‐Orbit Radiometric Performance on ICESat‐2

New Ocean Subsurface Optical Properties From Space Lidars: CALIOP/CALIPSO and ATLAS/ICESat‐2

Assessment of using spaceborne LiDAR to monitor the particulate backscatter coefficient on large, freshwater lakes: A test using CALIPSO on Lake Michigan

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