14 citations as recorded by crossref.

1. Enhanced sea ice classification for ICESat-2 using combined unsupervised and supervised machine learning W. Liu et al. https://doi.org/10.1016/j.rse.2025.114607
2. Automated Detection and Mapping of Supraglacial Lakes Using Machine Learning From ICESat-2 and Sentinel-2 Data G. Zhang et al. https://doi.org/10.1109/TGRS.2025.3602429
3. AWI-ICENet1: a convolutional neural network retracker for ice altimetry V. Helm et al. https://doi.org/10.5194/tc-18-3933-2024
4. Optical determination of snow density via sub-surface scattering L. Mewes et al. https://doi.org/10.1038/s42005-026-02490-1
5. Supraglacial Lake Bathymetry Retrieval from ICESat-2 Altimetry Data and Sentinel-2 Imagery Using Deep Learning Algorithms Y. Wu et al. https://doi.org/10.3390/rs18162726
6. Climatology and Interannual Variations in Arctic Winter Sea Ice Leads in the ICESat-2 Era M. Zhao et al. https://doi.org/10.5194/tc-20-4313-2026
7. Mechanism and algorithm for addressing the impact of multiple scattering on surface elevation extraction in photon-counting LiDAR data Z. Wang et al. https://doi.org/10.1016/j.rse.2025.114603
8. Mangrove canopy-height estimation using LiDAR and multispectral remote sensing: linking spatiotemporal species composition to restoration baselines Z. Afif et al. https://doi.org/10.1080/01431161.2026.2734354
9. Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics C. Henley et al. https://doi.org/10.1017/jog.2024.81
10. Analysis of the Precision and Bias of ICESat-2 Sea Surface Height Product H. Sun et al. https://doi.org/10.1080/01490419.2024.2443921
11. Light detection and ranging of natural systems L. Irwin et al. https://doi.org/10.1038/s43586-025-00446-3
12. Understanding biases in ICESat-2 data due to subsurface scattering using Airborne Topographic Mapper waveform data B. Smith et al. https://doi.org/10.5194/tc-19-975-2025
13. Anticipating CRISTAL: an exploration of multi-frequency satellite altimeter snow depth estimates over Arctic sea ice, 2018–2023 J. Landy et al. https://doi.org/10.5194/tc-20-183-2026
14. Quantifying the influence of snow over sea ice morphology on L-band passive microwave satellite observations in the Southern Ocean L. Zhou et al. https://doi.org/10.5194/tc-18-4399-2024