First principles modeling for lidar sensing of complex ice surfaces

Kerekes, John P.; Goodenough, Adam A.; Brown, Scott; Zhang, J.; Csathó, Beáta; Schenk, A. F.; Nagarajan, Sudhagar; Wheelwright, Robert

doi:10.1109/igarss.2012.6350733

Cited by 7 publications

(6 citation statements)

References 8 publications

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“…The ICESat‐2 follow‐on mission will utilize a photon‐counting approach to potentially characterize individual crevasses in addition to crevasse fields [ Abdalati et al ., ]. Simulations and empirical data collected by the Multiple Altimeter Beam Experimental Lidar (MABEL) over the Greenland Ice Sheet have already demonstrated the ability of photon‐counting altimetry to map crevassed surface features at submeter resolutions [ Kerekes et al ., ].…”

Section: Remotely Sensed Observationsmentioning

confidence: 99%

Glacier crevasses: Observations, models, and mass balance implications

Colgan

Rajaram

Abdalati

et al. 2016

Reviews of Geophysics

174

199

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We review the findings of approximately 60 years of in situ and remote sensing studies of glacier crevasses, as well as the three broad classes of numerical models now employed to simulate crevasse fracture. The relatively new insight that mixed-mode fracture in local stress equilibrium, rather than downstream advection alone, can introduce nontrivial curvature to crevasse geometry may merit the reinterpretation of some key historical observation studies. In the past three decades, there have been tremendous advances in the spatial resolution of satellite imagery, as well as fully automated algorithms capable of tracking crevasse displacements between repeat images. Despite considerable advances in developing fully transient three-dimensional ice flow models over the past two decades, both the zero stress and linear elastic fracture mechanics crevasse models have remained fundamentally unchanged over this time. In the past decade, however, multidimensional and transient formulations of the continuum damage mechanics approach to simulating ice fracture have emerged. The combination of employing damage mechanics to represent slow upstream deterioration of ice strength and fracture mechanics to represent rapid failure at downstream termini holds promise for implementation in large-scale ice sheet models. Finally, given the broad interest in the sea level rise implications of recent and future cryospheric change, we provide a synthesis of 10 mechanisms by which crevasses can influence glacier mass balance. Field ObservationsBy virtue of providing relatively easy access to a glacier's interior, crevasses can be an asset to observational glaciologists, permitting, for example, the efficient examination of glacier stratigraphy. Annual accumulation

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Section: Remotely Sensed Observationsmentioning

confidence: 99%

Glacier crevasses: Observations, models, and mass balance implications

Colgan

Rajaram

Abdalati

et al. 2016

Reviews of Geophysics

174

199

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“…Given the expected number of noise and signal photons in the neighborhood, the parameter MinPts can be expressed as equation (10).…”

Section: 𝐹𝑊𝐻𝑀 = 2√𝑙𝑛2𝜎mentioning

confidence: 99%

“…The PCL is becoming increasingly popular because it can provide massive data and detect objects invisible to traditional remote sensing technologies. However, since this mechanism of PCL is sensitive to individual photon, it can not only receive signal echoes reflected from the ground surface but also record noise echoes returned by scattering and reflection, thus its data can severely be affected by the ambient condition (atmospheric scattering and solar radiation), target feature (land-cover types and reflectance), and instrument performance (transmit energy, detector efficiency, and deadtime and after-pulsing effect) [9] [10]. As a result, there are usually numerous noise photon events randomly and widely L 2 > REPLACE THIS LINE WITH YOUR MANUSCRIPT ID NUMBER (DOUBLE-CLICK HERE TO EDIT) < distributed along the laser propagation path, especially in the daytime data.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Signal Photon Detection Method Based on DBSCAN for Photon-Counting Laser Altimeter

Liu,

Wang,

Yang

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Photon-counting LiDAR is very sensitive to ambient interference, target features, and instrument performance, especially for long-distance detection of spaceborne laser altimeter and measurement of complex land-cover types with steep terrain. It is crucial to extract the signal photons on the ground surface from the collected photon point cloud (PPC). An adaptive signal photon detection method is presented in this paper, which combines histogram statistics and boxplot analysis with density-based spatial clustering of applications with noise (DBSCAN), to denoises the PPC data with strong and weak noise obtained by ICESat-2 laser altimeter. First, a coarse denoising with histogram of elevation is conducted on the raw PPC to reduce the calculation amount. Second, a fine denoising based on adaptive DBSCAN is used to extract the signal photons, where the key parameters of elliptic filter kernel are automatically determined according to the topographic data situation. We compared it with other methods, including local distance statistics (LDS), traditional and modified DBSCAN, traditional and modified ordering points to identify cluster structure (OPTICS), and ATL08 data. Some quantitative indicators, such as recall (R), precision (P), and F-score (F), are used to evaluate its performance. The results show that (1) the adaptive DBSCAN has the best performance on preserving the vertical structural characteristics of ground objects. (2) The adaptive DBSCAN in the mean R, P and F of three land covers (i.e., mountain forest, urban and water areas) can get up to the maximum are 0.9852, 0.9675 and 0.9761, respectively; followed by ATL08 data with 0.9773, 0.9412 and 0.9536, modified OPTICS with 0.9684, 0.9460 and 0.9586, and modified DBSCAN with 0.9613, 0.9474 and 0.9544; and then OPTICS with 0.9444, 0.9397 and 0.9378, and the DBSCAN with 0.9444, 0.9355 and 0.9554; the last one is LDS with 0.9382, 0.9261 and 0.9422. The proposed method provides an alternative approach for rapid and accurate processing of PPC on complex terrain.

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“…The second factor, namely the type of surface, is less obvious. The optical properties of ice and snow are affected by many variables, including density, salinity, dissolved components, particle size, and surface cover [9,10]. Differential penetration by the laser into diverse surfaces, such as ice, snow, melting or slushy snow, water, solid rock, require different threshold values.…”

Section: Determination Of Noise Reduction Parametersmentioning

confidence: 99%

An automated statistical analysis approach to noise reduction for photon-counting lidar systems

Horan

Kerekes

2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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Satellite-based and airborne lidar instrumentation has been demonstrated to be a strategic tool in increasing our understanding of Earth's polar cryosphere, specifically that of total mass balance, which is a significant factor in estimating sea level rise due to climate change. The Ice, Cloud and land Elevation Satellite 2 (ICESat-2) will provide accurate estimates of local glacial topographical changes with increased measurement precision and change detection capability. Measurements obtained from the airborne Multiple Altimeter Beam Experimental Lidar (MABEL) instrument, an experimental photon-counting lidar -which uses multiple transmit/receive beams to resolve cross-track slope and elevation changes -are critical to project scientists to develop algorithms that will be used for the upcoming ICESat-2 mission. To aid in this effort, a new noise reduction technique has been developed. The general approach is to 1) divide the received photons into bins, 2) calculate the mode for each bin, and 3) compare each photon elevation to the mode for that bin, retaining only those photons that fall within a set threshold. Because the proposed technique uses statistical analysis to separate the surface elevation photons from the solar background photons, finding the surface return is computationally very light, making it ideal for large data sets, such as those associated with photon-counting lidars.

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First principles modeling for lidar sensing of complex ice surfaces

Cited by 7 publications

References 8 publications

Glacier crevasses: Observations, models, and mass balance implications

Glacier crevasses: Observations, models, and mass balance implications

An Adaptive Signal Photon Detection Method Based on DBSCAN for Photon-Counting Laser Altimeter

An automated statistical analysis approach to noise reduction for photon-counting lidar systems

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