140 citations as recorded by crossref.

1. Mapping snow depth and spatial variability using SFM photogrammetry of UAV images over rugged mountainous regions of the Western Himalaya S. Dewali et al. https://doi.org/10.1080/10106049.2022.2127923
2. Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry T. Redpath et al. https://doi.org/10.5194/tc-12-3477-2018
3. Detecting short-term surface melt over Vestre Broggerbreen, Arctic glacier using indigenously developed unmanned air vehicles M. Geetha Priya et al. https://doi.org/10.1080/10106049.2020.1849416
4. A Call for More Snow Sampling S. Fassnacht https://doi.org/10.3390/geosciences11110435
5. Low-budget topographic surveying comes of age: Structure from motion photogrammetry in geography and the geosciences K. Anderson et al. https://doi.org/10.1177/0309133319837454
6. Location Dictates Snow Aerodynamic Roughness S. Fassnacht et al. https://doi.org/10.3390/glacies1010001
7. STUDY ON EFFECTIVE INSTALLATION OF GROUND REFERENCE POINTS FOR UAV-SfM SURVEYING METHOD IN THE SNOW SEASON K. TAKAHASHI et al. https://doi.org/10.2208/jscejj.23-22005
8. Measurement of snow distribution using small UAV H. OBANAWA et al. https://doi.org/10.5331/seppyo.78.5_317
9. Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. https://doi.org/10.3389/frsen.2021.675846
10. Potential of the Bi-Static SAR Satellite Companion Mission Harmony for Land-Ice Observations A. Kääb et al. https://doi.org/10.3390/rs16162918
11. Reconstruction of former glacier surface topography from archive oblique aerial images N. Midgley & T. Tonkin https://doi.org/10.1016/j.geomorph.2017.01.008
12. A novel approach for extraction of ripple mark parameters based on SfM L. Li et al. https://doi.org/10.1016/j.sedgeo.2019.105523
13. Interannual snow accumulation variability on glaciers derived from repeat, spatially extensive ground-penetrating radar surveys D. McGrath et al. https://doi.org/10.5194/tc-12-3617-2018
14. Using a fixed-wing UAS to map snow depth distribution: an evaluation at peak accumulation C. De Michele et al. https://doi.org/10.5194/tc-10-511-2016
15. Sediment redistribution beneath the terminus of an advancing glacier, Taku Glacier (T'aakúKwáan Sít'i), Alaska J. Zechmann et al. https://doi.org/10.1017/jog.2020.101
16. Mapping snow depth in open alpine terrain from stereo satellite imagery R. Marti et al. https://doi.org/10.5194/tc-10-1361-2016
17. Multitemporal Accuracy and Precision Assessment of Unmanned Aerial System Photogrammetry for Slope-Scale Snow Depth Maps in Alpine Terrain M. Adams et al. https://doi.org/10.1007/s00024-017-1748-y
18. Thaw slump activity measured using stationary cameras in time-lapse and Structure-from-Motion photogrammetry L. Armstrong et al. https://doi.org/10.1139/as-2018-0016
19. Potential of Balloon Photogrammetry for Spatially Continuous Snow Depth Measurements D. Li et al. https://doi.org/10.1109/LGRS.2019.2953481
20. Ground-Control Networks for Image Based Surface Reconstruction: An Investigation of Optimum Survey Designs Using UAV Derived Imagery and Structure-from-Motion Photogrammetry T. Tonkin & N. Midgley https://doi.org/10.3390/rs8090786
21. Image acquisition effects on Unmanned Air Vehicle snow depth retrievals A. Tekeli & S. Dönmez https://doi.org/10.5194/piahs-380-81-2018
22. Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States J. Jacobs et al. https://doi.org/10.5194/tc-15-1485-2021
23. The Effects of Dry Snow on the SAR Impulse Response and Feasibility for Single Channel Snow Water Equivalent Estimation J. Eppler & B. Rabus https://doi.org/10.1109/TGRS.2021.3089131
24. MOBILE SCANNING MEASUREMENT METHOD FOR MEASURING THE SHAPE OF THE SNOW SURFACE FORMED AROUND SNOW PROTECTION EQUIPMENT K. TAKAHASHI et al. https://doi.org/10.2208/jscejj.24-00102
25. Improving sub-canopy snow depth mapping with unmanned aerial vehicles: lidar versus structure-from-motion techniques P. Harder et al. https://doi.org/10.5194/tc-14-1919-2020
26. Brief Communication: Mapping river ice using drones and structure from motion K. Alfredsen et al. https://doi.org/10.5194/tc-12-627-2018
27. Use of modern software solutions and systems for analysis and reconstruction of road accidents I. Damyanov https://doi.org/10.1088/1757-899X/878/1/012043
28. Aufeis thickness and volume estimations from stereo satellite imagery and terrestrial photographs: Evidence from Central Ladakh, India D. Brombierstäudl et al. https://doi.org/10.1016/j.scitotenv.2024.176180
29. Snow depth variability in the Northern Hemisphere mountains observed from space H. Lievens et al. https://doi.org/10.1038/s41467-019-12566-y
30. Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain J. Revuelto et al. https://doi.org/10.1016/j.coldregions.2021.103344
31. Snow water equivalent change mapping from slope-correlated synthetic aperture radar interferometry (InSAR) phase variations J. Eppler et al. https://doi.org/10.5194/tc-16-1497-2022
32. The Utility of Infrequent Snow Depth Images for Deriving Continuous Space‐Time Estimates of Seasonal Snow Water Equivalent S. Margulis et al. https://doi.org/10.1029/2019GL082507
33. Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data Z. Zheng et al. https://doi.org/10.5194/tc-10-257-2016
34. Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area J. Goetz & A. Brenning https://doi.org/10.1029/2019WR025251
35. Remote Sensing of Landscape Change in Permafrost Regions M. Jorgenson & G. Grosse https://doi.org/10.1002/ppp.1914
36. A Study of a Parametric Method for the Snow Reflection Coefficient Estimation Using Air-Coupled Ultrasonic Waves K. Herman et al. https://doi.org/10.3390/s20154267
37. Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations Y. Bühler et al. https://doi.org/10.5194/tc-10-1075-2016
38. Multi-year evaluation of airborne geodetic surveys to estimate seasonal mass balance, Columbia and Rocky Mountains, Canada B. Pelto et al. https://doi.org/10.5194/tc-13-1709-2019
39. Understanding wind-driven melt of patchy snow cover L. van der Valk et al. https://doi.org/10.5194/tc-16-4319-2022
40. Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote Sensing Datasets R. Eker et al. https://doi.org/10.3390/rs11060699
41. Design of a scanning laser meter for monitoring the spatio-temporal evolution of snow depth and its application in the Alps and in Antarctica G. Picard et al. https://doi.org/10.5194/tc-10-1495-2016
42. A New Formulation and Code to Compute Aerodynamic Roughness Length for Gridded Geometry—Tested on Lidar-Derived Snow Surfaces R. Neville et al. https://doi.org/10.3390/rs17121984
43. Accuracy Assessment of a UAV Direct Georeferencing Method and Impact of the Configuration of Ground Control Points X. Liu et al. https://doi.org/10.3390/drones6020030
44. A comparison of three surface roughness characterization techniques: photogrammetry, pin profiler, and smartphone-based LiDAR Z. Alijani et al. https://doi.org/10.1080/17538947.2022.2160842
45. Automated mapping of relict patterned ground: An approach to evaluate morphologically subdued landforms using unmanned-aerial-vehicle and structure-from-motion technologies A. Mather et al. https://doi.org/10.1177/0309133318788966
46. Application of Fixed-Wing UAV-Based Photogrammetry Data for Snow Depth Mapping in Alpine Conditions M. Masný et al. https://doi.org/10.3390/drones5040114
47. The challenge of monitoring snow surface sublimation in winter could be resolved with structure-from-motion photogrammetry J. Liu et al. https://doi.org/10.1016/j.jhydrol.2024.130733
48. New opportunities for low-cost LiDAR-derived snow depth estimates from a consumer drone-mounted smartphone F. King et al. https://doi.org/10.1016/j.coldregions.2022.103757
49. Modeling the precision of structure-from-motion multi-view stereo digital elevation models from repeated close-range aerial surveys J. Goetz et al. https://doi.org/10.1016/j.rse.2018.03.013
50. Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation K. Maier et al. https://doi.org/10.1016/j.isprsjprs.2022.01.020
51. The evolution of embryonic creek systems in a recently inundated large open coast managed realignment site J. Dale et al. https://doi.org/10.1139/anc-2017-0005
52. Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice E. Trujillo et al. https://doi.org/10.1002/2016JF003893
53. The state and future of the cryosphere in Central Asia M. Barandun et al. https://doi.org/10.1016/j.wasec.2020.100072
54. Image-based surface reconstruction in geomorphometry – merits, limits and developments A. Eltner et al. https://doi.org/10.5194/esurf-4-359-2016
55. Thermal photogrammetric imaging: A new technique for monitoring dome eruptions S. Thiele et al. https://doi.org/10.1016/j.jvolgeores.2017.03.022
56. Investigating snowpack volumes and icing dynamics in the moraine of an Arctic catchment using UAV photogrammetry É. Bernard et al. https://doi.org/10.1111/phor.12217
57. Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain Z. Miller et al. https://doi.org/10.5194/tc-16-4907-2022
58. Modeling snowdrift habitat for polar bear dens G. Liston et al. https://doi.org/10.1016/j.ecolmodel.2015.09.010
59. Monitoring Spatial and Temporal Differences in Andean Snow Depth Derived From Satellite Tri-Stereo Photogrammetry T. Shaw et al. https://doi.org/10.3389/feart.2020.579142
60. European In-Situ Snow Measurements: Practices and Purposes R. Pirazzini et al. https://doi.org/10.3390/s18072016
61. Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing P. Schattan et al. https://doi.org/10.1002/2016WR020234
62. Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. https://doi.org/10.5194/tc-17-3383-2023
63. UAV Based Estimation of Forest Leaf Area Index (LAI) through Oblique Photogrammetry L. Lin et al. https://doi.org/10.3390/rs13040803
64. Analyzing vegetation effects on snow depth variability in Alaska's boreal forests with airborne lidar L. May et al. https://doi.org/10.5194/tc-19-3477-2025
65. Drone applications in hydrogeophysics: Recent examples and a vision for the future A. Mangel et al. https://doi.org/10.1190/tle41080540.1
66. Local-scale deposition of surface snow on the Greenland ice sheet A. Zuhr et al. https://doi.org/10.5194/tc-15-4873-2021
67. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers S. Gindraux et al. https://doi.org/10.3390/rs9020186
68. Factors Influencing the Accuracy of Shallow Snow Depth Measured Using UAV-Based Photogrammetry S. Lee et al. https://doi.org/10.3390/rs13040828
69. Snow Depth Retrieval With an Autonomous UAV-Mounted Software-Defined Radar S. Prager et al. https://doi.org/10.1109/TGRS.2021.3117509
70. Mapping snow depth and volume at the alpine watershed scale from aerial imagery using Structure from Motion J. Meyer et al. https://doi.org/10.3389/feart.2022.989792
71. The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters R. Webb et al. https://doi.org/10.1002/2017WR020866
72. Effects of meteorology and soil moisture on the spatio-temporal evolution of the depth hoar layer in the polar desert snowpack G. Davesne et al. https://doi.org/10.1017/jog.2021.105
73. Accounting for permafrost creep in high-resolution snow depth mapping by modelling sub-snow ground deformation J. Goetz et al. https://doi.org/10.1016/j.rse.2019.111275
74. Assessing patterns of annual change to permafrost bluffs along the North Slope coast of Alaska using high-resolution imagery and elevation models A. Gibbs et al. https://doi.org/10.1016/j.geomorph.2019.03.029
75. Snow Surface Roughness across Spatio-Temporal Scales S. Fassnacht et al. https://doi.org/10.3390/w15122196
76. High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut J. Meloche et al. https://doi.org/10.1002/hyp.14546
77. The Runoff Observation and Composition Analysis in the Niyang River Basin on the Tibetan Plateau H. Liu et al. https://doi.org/10.5194/piahs-383-85-2020
78. UAV-SfM SURVEYING METHOD FOR MEASURING SNOW SURFACE PROFILE FORMED AROUND SNOW FENCES K. TAKAHASHI et al. https://doi.org/10.2208/jscejj.22-00139
79. Cost‐effective non‐metric photogrammetry from consumer‐grade sUAS: implications for direct georeferencing of structure from motion photogrammetry P. Carbonneau & J. Dietrich https://doi.org/10.1002/esp.4012
80. Snow depth from ICESat laser altimetry — A test study in southern Norway D. Treichler & A. Kääb https://doi.org/10.1016/j.rse.2017.01.022
81. Detecting Short-Term Surface Melt on an Arctic Glacier Using UAV Surveys E. Bash et al. https://doi.org/10.3390/rs10101547
82. High-resolution monitoring of complex coastal morphology changes: cross-efficiency of SfM and TLS-based survey (Vaches-Noires cliffs, Normandy, France) M. Medjkane et al. https://doi.org/10.1007/s10346-017-0942-4
83. Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain R. Hugonnet et al. https://doi.org/10.1109/JSTARS.2022.3188922
84. Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle P. Harder et al. https://doi.org/10.5194/tc-10-2559-2016
85. Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms M. Kalacska et al. https://doi.org/10.3390/drones4020013
86. Quantifying snow drift on Arctic structures: A case study at Summit, Greenland, using UAV-based structure-from-motion photogrammetry R. Hawley & J. Millstein https://doi.org/10.1016/j.coldregions.2018.10.007
87. An Arctic watershed observatory at Lake Peters, Alaska: weather–glacier–river–lake system data for 2015–2018 E. Broadman et al. https://doi.org/10.5194/essd-11-1957-2019
88. Evaluation of SfM for surface characterization of a snow-covered glacier through comparison with aerial lidar E. Bash et al. https://doi.org/10.1139/juvs-2019-0006
89. Hydrologic connectivity at the hillslope scale through intra‐snowpack flow paths during snowmelt R. Webb et al. https://doi.org/10.1002/hyp.13686
90. Modelling snowpack bulk density using snow depth, cumulative degree‐days, and climatological predictor variables A. Szeitz & R. Moore https://doi.org/10.1002/hyp.14800
91. Snowcover Survey over an Arctic Glacier Forefield: Contribution of Photogrammetry to Identify “Icing” Variability and Processes É. Bernard et al. https://doi.org/10.3390/rs13101978
92. Fine-Scale Sea Ice Structure Characterized Using Underwater Acoustic Methods V. Lucieer et al. https://doi.org/10.3390/rs8100821
93. Improvement of microwave emissivity parameterization of frozen Arctic soils using roughness measurements derived from photogrammetry J. Meloche et al. https://doi.org/10.1080/17538947.2020.1836049
94. Local variability of a taiga snow cover due to vegetation and microtopography A. Komarov & M. Sturm https://doi.org/10.1080/15230430.2023.2170086
95. Application of Low-Cost UASs and Digital Photogrammetry for High-Resolution Snow Depth Mapping in the Arctic E. Cimoli et al. https://doi.org/10.3390/rs9111144
96. Monitoring snow depth variations in an avalanche release area using low-cost lidar and optical sensors P. Ruttner et al. https://doi.org/10.5194/nhess-25-1315-2025
97. Remote sensing from unoccupied aerial systems: Opportunities to enhance Arctic plant ecology in a changing climate D. Yang et al. https://doi.org/10.1111/1365-2745.13976
98. Szorstkość pokrycia terenu jako źródło błędu metody SfM zastosowanej do rekonstrukcji zasięgu pokrywy śnieżnej = Terrain roughness as a source of error with the SfM method applied to the reconstruction of snow cover extent D. Szafert et al. https://doi.org/10.7163/PrzG.2020.3.4
99. Monitoring the crisis of a rock glacier with repeated UAV surveys S. Vivero & C. Lambiel https://doi.org/10.5194/gh-74-59-2019
100. Which are the highest peaks in the US Arctic? Fodar settles the debate M. Nolan & K. DesLauriers https://doi.org/10.5194/tc-10-1245-2016
101. Using structure from motion photogrammetry to measure past glacier changes from historic aerial photographs L. VARGO et al. https://doi.org/10.1017/jog.2017.79
102. Mosaicking Opportunistically Acquired Very High-Resolution Helicopter-Borne Images over Drifting Sea Ice Using COTS Sensors C. Hyun et al. https://doi.org/10.3390/s19051251
103. Suitability of Aerial Photogrammetry for Dump Documentation and Volume Determination in Large Areas Ľ. Kovanič et al. https://doi.org/10.3390/app11146564
104. Change Detection Applications in the Earth Sciences Using UAS-Based Sensing: A Review and Future Opportunities C. Andresen & E. Schultz-Fellenz https://doi.org/10.3390/drones7040258
105. Seasonal Subsurface Thaw Dynamics of an Aufeis Feature Inferred From Geophysical Methods N. Terry et al. https://doi.org/10.1029/2019JF005345
106. Fully-automated estimation of snow depth in near real time with the use of unmanned aerial vehicles without utilizing ground control points B. Miziński & T. Niedzielski https://doi.org/10.1016/j.coldregions.2017.03.006
107. UAV LiDAR surveys and machine learning improve snow depth and water equivalent estimates in boreal landscapes M. Ylönen et al. https://doi.org/10.5194/tc-19-4585-2025
108. Scales of snow depth variability in high elevation rangeland sagebrush M. Tedesche et al. https://doi.org/10.1007/s11707-017-0662-z
109. Monitoring snow depth change across a range of landscapes with ephemeral snowpacks using structure from motion applied to lightweight unmanned aerial vehicle videos R. Fernandes et al. https://doi.org/10.5194/tc-12-3535-2018
110. Time‐Lapse Photogrammetry of Distributed Snow Depth During Snowmelt S. Filhol et al. https://doi.org/10.1029/2018WR024530
111. Determining the Suitable Number of Ground Control Points for UAS Images Georeferencing by Varying Number and Spatial Distribution V. Oniga et al. https://doi.org/10.3390/rs12050876
112. Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj https://doi.org/10.3390/rs12060948
113. Snowdrift Landscape Patterns: An Arctic Investigation C. Parr et al. https://doi.org/10.1029/2020WR027823
114. Early twentieth century evolution of Ferdinand glacier, Svalbard, based on historic photographs and structure-from-motion technique J. Kavan https://doi.org/10.1080/04353676.2020.1715124
115. Snow process monitoring using time-lapse structure-from-motion photogrammetry with a single camera J. Liu et al. https://doi.org/10.1016/j.coldregions.2021.103355
116. An Examination of Water‐Related Melt Processes in Arctic Snow on Tundra and Sea‐Ice A. Pinzner et al. https://doi.org/10.1029/2022WR033440
117. Growth of Retrogressive Thaw Slumps in the Noatak Valley, Alaska, 2010–2016, Measured by Airborne Photogrammetry D. Swanson & M. Nolan https://doi.org/10.3390/rs10070983
118. The impact of terrain model source and resolution on snow avalanche modeling A. Miller et al. https://doi.org/10.5194/nhess-22-2673-2022
119. Spatial controls on the distribution and dynamics of a marginal snowpack in the Australian Alps S. Bilish et al. https://doi.org/10.1002/hyp.13435
120. Modelling spatial patterns of near-surface air temperature over a decade of melt seasons on McCall Glacier, Alaska P. Troxler et al. https://doi.org/10.1017/jog.2020.12
121. Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery Y. Bühler et al. https://doi.org/10.1080/01431161.2016.1275060
122. Dynamics of the Bingham Canyon rock avalanches (Utah, USA) resolved from topographic, seismic, and infrasound data J. Moore et al. https://doi.org/10.1002/2016JF004036
123. Photogrammetric Monitoring of Rock Glacier Motion Using High-Resolution Cross-Platform Datasets: Formation Age Estimation and Modern Thinning Rates T. Meng et al. https://doi.org/10.3390/rs15194779
124. Terrain changes from images acquired on opportunistic flights by SfM photogrammetry L. Girod et al. https://doi.org/10.5194/tc-11-827-2017
125. Arctic coastal erosion: UAV-SfM data collection strategies for planimetric and volumetric measurements A. Clark et al. https://doi.org/10.1139/as-2020-0021
126. Rigorous 3D change determination in Antarctic Peninsula glaciers from stereo WorldView-2 and archival aerial imagery K. Fieber et al. https://doi.org/10.1016/j.rse.2017.10.042
127. Monitoring Mining Surface Subsidence with Multi-Temporal Three-Dimensional Unmanned Aerial Vehicle Point Cloud X. Liu et al. https://doi.org/10.3390/rs15020374
128. Review of methodological considerations and recommendations for mapping remote glaciers from aerial photography surveys in suboptimal conditions D. Medrzycka et al. https://doi.org/10.5194/gi-14-69-2025
129. Centimetric Accuracy in Snow Depth Using Unmanned Aerial System Photogrammetry and a MultiStation F. Avanzi et al. https://doi.org/10.3390/rs10050765
130. Measuring historical flooding and erosion in Goodnews Bay using datasets commonly available to Alaska communities R. Buzard et al. https://doi.org/10.34237/1008831
131. Measurement of snow cover depth using 100 × 100 meters sampling plot and Structure from Motion method in Adventdalen, Svalbard R. Stuchlík et al. https://doi.org/10.5817/CPR2016-2-14
132. Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar E. Cho et al. https://doi.org/10.1016/j.jhydrol.2021.126722
133. Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods H. Wainwright et al. https://doi.org/10.5194/tc-11-857-2017
134. Simulating optical top-of-atmosphere radiance satellite images over snow-covered rugged terrain M. Lamare et al. https://doi.org/10.5194/tc-14-3995-2020
135. Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. https://doi.org/10.5194/tc-18-5407-2024
136. Integrating local environmental observations and remote sensing to better understand the life cycle of a thermokarst lake in Arctic Alaska B. Jones et al. https://doi.org/10.1080/15230430.2023.2195518
137. Terminus change of Kaskawulsh Glacier, Yukon, under a warming climate: retreat, thinning, slowdown and modified proglacial lake geometry B. Main et al. https://doi.org/10.1017/jog.2022.114
138. The 2015 landslide and tsunami in Taan Fiord, Alaska B. Higman et al. https://doi.org/10.1038/s41598-018-30475-w
139. Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping L. Eberhard et al. https://doi.org/10.5194/tc-15-69-2021
140. Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data C. Deschamps-Berger et al. https://doi.org/10.5194/tc-14-2925-2020