49 citations as recorded by crossref.

1. Enhancing the Representation of Glaciers and Ice Sheets in the ecLand Land-Surface Model: Impacts on Surface Energy Balance and Hydrology Across Scales G. Arduini et al. https://doi.org/10.5194/tc-20-1119-2026
2. Automated Glacier Snow Line Altitude Calculation Method Using Landsat Series Images in the Google Earth Engine Platform X. Li et al. https://doi.org/10.3390/rs14102377
3. Topographic associations with glacier albedo in the southeastern Tibetan Plateau D. Ma et al. https://doi.org/10.1016/j.accre.2026.08.001
4. Spatiotemporal variations in surface albedo during the ablation season and linkages with the annual mass balance on Muz Taw Glacier, Altai Mountains X. Yue et al. https://doi.org/10.1080/17538947.2022.2148766
5. Towards the assimilation of satellite reflectance into semi-distributed ensemble snowpack simulations B. Cluzet et al. https://doi.org/10.1016/j.coldregions.2019.102918
6. A Novel Method Combining Remote Sensing Albedo and Differencing DEM to Estimate Annual Glacier Mass Balance Y. Liu et al. https://doi.org/10.1109/JSTARS.2025.3570800
7. Retreat of Machoi Glacier, Kashmir Himalaya between 1972 and 2019 using remote sensing methods and field observations I. Rashid et al. https://doi.org/10.1016/j.scitotenv.2021.147376
8. Estimating glacier mass balance in High Mountain Asia based on Moderate Resolution Imaging Spectroradiometer retrieved surface albedo from 2000 to 2020 Y. Xiao et al. https://doi.org/10.1002/joc.7873
9. Global glacier albedo changes in the 21st century revealed by MODIS and CMIP6 models Y. Xiao et al. https://doi.org/10.1080/17538947.2026.2681373
10. Constraining sub-seasonal glacier mass balance in the Swiss Alps using Sentinel-2-derived snow-cover observations A. Cremona et al. https://doi.org/10.1017/jog.2025.1
11. The sub-seasonal and interannual spatio-temporal variability of bare-ice albedo of Abramov Glacier, Kyrgyzstan A. Volery et al. https://doi.org/10.1017/jog.2024.90
12. CrocO_v1.0: a particle filter to assimilate snowpack observations in a spatialised framework B. Cluzet et al. https://doi.org/10.5194/gmd-14-1595-2021
13. What drives the decrease of glacier surface albedo in High Mountain Asia in the past two decades? Y. Xiao et al. https://doi.org/10.1016/j.scitotenv.2022.160945
14. Development of adaptive phenology metrics based on MODIS albedo and temperature observations and its global-scale assessment for glacier mass balance monitoring C. Xin & Y. Sheng https://doi.org/10.1080/01431161.2025.2549537
15. Surface mass balance of the Northern Patagonian Ice Field and links with climate variability modes and atmospheric variables G. Collao-Barrios et al. https://doi.org/10.1017/jog.2025.10106
16. Annual mass-balance time series of Dongkemadi Glacier, 2000–20, from a linear albedo-based model using geodetic data and validated with the glaciological method L. Liu et al. https://doi.org/10.1017/jog.2024.1
17. Variation in Glacier Albedo on the Tibetan Plateau between 2001 and 2022 Based on MODIS Data P. Liu et al. https://doi.org/10.3390/rs16183472
18. Regional glacier melt modeling: insights from surface energy balance and positive degree-day comparisons H. Phelps et al. https://doi.org/10.1017/S0022143025100531
19. Observed and projected declines in glacier albedo across the Third Pole in the 21st century S. Ren et al. https://doi.org/10.1016/j.oneear.2024.08.010
20. Annual Glacier-Wide Mass Balance (2000–2016) of the Interior Tibetan Plateau Reconstructed from MODIS Albedo Products Z. Zhang et al. https://doi.org/10.3390/rs10071031
21. Lengthening ablation seasons are associated with declining minimum albedo of global glaciers Y. Xiao et al. https://doi.org/10.1016/j.accre.2026.06.025
22. Variability in glacier albedo and links to annual mass balance for the gardens of Eden and Allah, Southern Alps, New Zealand A. Dowson et al. https://doi.org/10.5194/tc-14-3425-2020
23. Change detection of bare-ice albedo in the Swiss Alps K. Naegeli et al. https://doi.org/10.5194/tc-13-397-2019
24. Comparing simple albedo scaling methods for estimating Arctic glacier mass balance S. Williamson et al. https://doi.org/10.1016/j.rse.2020.111858
25. Remote sensing-based assessment of albedo changes on benchmark glaciers in the Western Himalaya, India, between 2001 and 2022 using Google Earth Engine: implications for glacier mass loss S. Magray et al. https://doi.org/10.1007/s12665-025-12749-5
26. Disaggregating geodetic glacier mass balance to annual scale using remote-sensing proxies A. Banerjee et al. https://doi.org/10.1017/jog.2022.89
27. Estimation of Shortwave Solar Radiation on Clear-Sky Days for a Valley Glacier with Sentinel-2 Time Series Y. Zhang et al. https://doi.org/10.3390/rs12060927
28. Less water from glaciers during future megadroughts in the Southern Andes Á. Ayala et al. https://doi.org/10.1038/s43247-025-02845-6
29. Quantification of annual glacier surface mass balance for the Chhota Shigri Glacier, Western Himalayas, India using an Equilibrium-Line Altitude (ELA) based approach A. Chandrasekharan et al. https://doi.org/10.1080/01431161.2018.1506182
30. Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt F. Avanzi et al. https://doi.org/10.5194/gmd-15-4853-2022
31. Processing of VENµS Images of High Mountains: A Case Study for Cryospheric and Hydro-Climatic Applications in the Everest Region (Nepal) Z. Bessin et al. https://doi.org/10.3390/rs14051098
32. Analysis of snow cover pollution in Arctic cities based on satellite albedo measurements P. Mikhaylyukova et al. https://doi.org/10.35595/2414-9179-2021-1-27-394-408
33. Use of ablation-season albedo as an indicator of annual mass balance of four glaciers in the Tien Shan X. Yue et al. https://doi.org/10.3389/feart.2023.974739
34. Reconstructing 32 years (1989–2020) of annual glacier surface mass balance in Chandra Basin, Western Himalayas, India A. Chandrasekharan & R. Ramsankaran https://doi.org/10.1007/s10113-023-02112-4
35. Seasonal and interannual variability of Karakoram glacier surface albedo from AVHRR-MODIS data, 1982–2020 F. Xie et al. https://doi.org/10.1016/j.gloplacha.2025.104914
36. Interrelation Between Glacier Summer Mass Balance And Runoff In Mountain River Basins V. Konovalov et al. https://doi.org/10.24057/2071-9388-2018-26
37. Pan-Alpine glacier phenology reveals lowering albedo and increase in ablation season length B. Di Mauro & D. Fugazza https://doi.org/10.1016/j.rse.2022.113119
38. Reconstruction of Annual Glacier Mass Balance from Remote Sensing-Derived Average Glacier-Wide Albedo Z. Zhang et al. https://doi.org/10.3390/rs15010031
39. Remote glacier monitoring through semantic fusion of geographic and contextual data G. Albamonte et al. https://doi.org/10.1016/j.engappai.2025.111366
40. Effect of shadow on atmospheric and topographic processed NDSI values in Chenab basin, western Himalayas A. Jasrotia et al. https://doi.org/10.1016/j.coldregions.2022.103561
41. Wind and topography underlie correlation between seasonal snowpack, mountain glaciers, and late-summer streamflow E. Boardman et al. https://doi.org/10.5194/tc-19-3193-2025
42. Sports Dance Action Recognition System Oriented to Human Motion Monitoring and Sensing S. Ni et al. https://doi.org/10.1155/2021/5515352
43. Changes in glacier albedo and the driving factors in the Western Nyainqentanglha Mountains from 2001 to 2020 S. Ren et al. https://doi.org/10.1017/jog.2023.45
44. Unveiling Glacier Mass Balance: Albedo Aggregation Insights for Austrian and Norwegian Glaciers F. Ye et al. https://doi.org/10.3390/rs16111914
45. Retrieval of high-resolution melting-season albedo and its implications for the Karakoram Anomaly F. Xie et al. https://doi.org/10.1016/j.rse.2024.114438
46. Regional differences in global glacier retreat from 1980 to 2015 Y. Li et al. https://doi.org/10.1016/j.accre.2020.03.003
47. Changes in Glaciers of the Vakhsh River Basin, Tajikistan Under Global Climate Change F. Nasrulloev et al. https://doi.org/10.3390/rs18091436
48. Glacier Monitoring Based on Multi-Spectral and Multi-Temporal Satellite Data: A Case Study for Classification with Respect to Different Snow and Ice Types J. Florath et al. https://doi.org/10.3390/rs14040845
49. The Determination of the Snow Optical Grain Diameter and Snowmelt Area on the Greenland Ice Sheet Using Spaceborne Optical Observations B. Vandecrux et al. https://doi.org/10.3390/rs14040932