74 citations as recorded by crossref.

1. Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions L. Meriö et al. 10.5194/tc-17-4363-2023
2. Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains P. Krajčí et al. 10.1515/johh-2016-0038
3. Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles T. Niedzielski et al. 10.1007/s00024-018-1843-8
4. Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain J. Revuelto et al. 10.1016/j.coldregions.2021.103344
5. Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
6. Application of Low-Cost UASs and Digital Photogrammetry for High-Resolution Snow Depth Mapping in the Arctic E. Cimoli et al. 10.3390/rs9111144
7. Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives B. Acharya et al. 10.1029/2021WR029925
8. Snow depth time series retrieval by time-lapse photography: Finnish and Italian case studies M. Bongio et al. 10.5194/tc-15-369-2021
9. Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States J. Jacobs et al. 10.5194/tc-15-1485-2021
10. Quality Assessment of DSMs Produced from UAV Flights Georeferenced with On-Board RTK Positioning G. Forlani et al. 10.3390/rs10020311
11. Light and Shadow in Mapping Alpine Snowpack With Unmanned Aerial Vehicles in the Absence of Ground Control Points J. Revuelto et al. 10.1029/2020WR028980
12. Learning about precipitation lapse rates from snow course data improves water balance modeling F. Avanzi et al. 10.5194/hess-25-2109-2021
13. Assessing the seasonal evolution of snow depth spatial variability and scaling in complex mountain terrain Z. Miller et al. 10.5194/tc-16-4907-2022
14. Factors Influencing the Accuracy of Shallow Snow Depth Measured Using UAV-Based Photogrammetry S. Lee et al. 10.3390/rs13040828
15. Mapping snow depth in open alpine terrain from stereo satellite imagery R. Marti et al. 10.5194/tc-10-1361-2016
16. A Comparative Analysis of UAV-RTK and UAV-PPK Methods in Mapping Different Surface Types R. EKER et al. 10.33904/ejfe.938067
17. Mapping snow depth and spatial variability using SFM photogrammetry of UAV images over rugged mountainous regions of the Western Himalaya S. Dewali et al. 10.1080/10106049.2022.2127923
18. Improving the snowpack monitoring in the mountainous areas of Sweden from space: a machine learning approach J. Zhang et al. 10.1088/1748-9326/abfe8d
19. Towards a webcam-based snow cover monitoring network: methodology and evaluation C. Portenier et al. 10.5194/tc-14-1409-2020
20. Accounting for permafrost creep in high-resolution snow depth mapping by modelling sub-snow ground deformation J. Goetz et al. 10.1016/j.rse.2019.111275
21. Real-Time Alpine Measurement System Using Wireless Sensor Networks S. Malek et al. 10.3390/s17112583
22. Drones in carbonate geology: Opportunities and challenges, and application in diagenetic dolomite geobody mapping M. Madjid et al. 10.1016/j.marpetgeo.2018.02.002
23. Image acquisition effects on Unmanned Air Vehicle snow depth retrievals A. Tekeli & S. Dönmez 10.5194/piahs-380-81-2018
24. Improving sub-canopy snow depth mapping with unmanned aerial vehicles: lidar versus structure-from-motion techniques P. Harder et al. 10.5194/tc-14-1919-2020
25. Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area J. Goetz & A. Brenning 10.1029/2019WR025251
26. Application of Fixed-Wing UAV-Based Photogrammetry Data for Snow Depth Mapping in Alpine Conditions M. Masný et al. 10.3390/drones5040114
27. Multitemporal Accuracy and Precision Assessment of Unmanned Aerial System Photogrammetry for Slope-Scale Snow Depth Maps in Alpine Terrain M. Adams et al. 10.1007/s00024-017-1748-y
28. Albedo change from snow algae blooms can contribute substantially to snow melt in the North Cascades, USA S. Healy & A. Khan 10.1038/s43247-023-00768-8
29. Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment A. Rauhala et al. 10.5194/tc-17-4343-2023
30. Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle P. Harder et al. 10.5194/tc-10-2559-2016
31. 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 10.1016/j.coldregions.2017.03.006
32. Comparing Interpretation of High-Resolution Aerial Imagery by Humans and Artificial Intelligence to Detect an Invasive Tree Species R. Rodriguez et al. 10.3390/rs13173503
33. The use of unmanned aerial vehicles (UAVs) for engineering geology applications D. Giordan et al. 10.1007/s10064-020-01766-2
34. Drone testing for 3D reconstruction of massive mounted skeletons in museums: the case of Mammuthus meridionalis (Nesti 1825) from Madonna della Strada (Scoppito, L’Aquila, Italy) M. Romano et al. 10.1080/08912963.2021.1975278
35. Snow profile temperature measurements in spatiotemporal analysis of snowmelt in a subarctic forest-mire hillslope L. Meriö et al. 10.1016/j.coldregions.2018.03.013
36. Accuracy assessment of late winter snow depth mapping for tundra environments using Structure-from-Motion photogrammetry B. Walker et al. 10.1139/as-2020-0006
37. sUAS-Based Remote Sensing in Mountainous Areas: Benefits, Challenges, and Best Practices D. Burchfield et al. 10.1080/23754931.2020.1716385
38. Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry T. Redpath et al. 10.5194/tc-12-3477-2018
39. Geomorphometry today I. Florinsky 10.35595/2414-9179-2021-2-27-394-448
40. Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. 10.5194/tc-17-3383-2023
41. Combining Daily Sensor Observations and Spatial LiDAR Data for Mapping Snow Water Equivalent in a Sub‐Alpine Forest J. Geissler et al. 10.1029/2023WR034460
42. 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. 10.5194/tc-12-3535-2018
43. Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations Y. Bühler et al. 10.5194/tc-10-1075-2016
44. Estimating Snow Depth and Leaf Area Index Based on UAV Digital Photogrammetry T. Lendzioch et al. 10.3390/s19051027
45. Influence of Block Geometry Configuration on Multi-Image Dense Matching N. Bruno et al. 10.3390/rs14153784
46. Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
47. Synergistic analysis of satellite, unmanned aerial vehicle, terrestrial laser scanner data and process-based modelling for understanding the dynamics and morphological changes around the snout of Gangotri Glacier, India P. Dhote et al. 10.1016/j.geomorph.2021.108005
48. Measurement of snow cover depth using 100 × 100 meters sampling plot and Structure from Motion method in Adventdalen, Svalbard R. Stuchlík et al. 10.5817/CPR2016-2-14
49. Snowdrift Landscape Patterns: An Arctic Investigation C. Parr et al. 10.1029/2020WR027823
50. Monitoring of Snow Cover Ablation Using Very High Spatial Resolution Remote Sensing Datasets R. Eker et al. 10.3390/rs11060699
51. A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests V. Dharmadasa et al. 10.1016/j.coldregions.2024.104134
52. Deep Learning Low-cost Photogrammetry for 4D Short-term Glacier Dynamics Monitoring F. Ioli et al. 10.1007/s41064-023-00272-w
53. Surface Reflectance and Sun-Induced Fluorescence Spectroscopy Measurements Using a Small Hyperspectral UAS R. Garzonio et al. 10.3390/rs9050472
54. Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation K. Maier et al. 10.1016/j.isprsjprs.2022.01.020
55. Mapping Glacier Ablation With a UAV in the North Cascades: A Structure-from-Motion Approach S. Healy & A. Khan 10.3389/frsen.2021.764765
56. Unmanned Aerial Vehicle-Based Structure from Motion Technique for Precise Snow Depth Retrieval—Implication for Optimal Ground Control Point Deployment Strategy S. Shu et al. 10.3390/rs15092297
57. Investigating the development of shallow snowpacks on arable land, using comprehensive field observations and spatially distributed snow modelling T. Starkloff et al. 10.2166/nh.2017.269
58. Centimetric Accuracy in Snow Depth Using Unmanned Aerial System Photogrammetry and a MultiStation F. Avanzi et al. 10.3390/rs10050765
59. Aerial and UAV Images for Photogrammetric Analysis of Belvedere Glacier Evolution in the Period 1977–2019 C. De Gaetani et al. 10.3390/rs13183787
60. Tundra shrub expansion may amplify permafrost thaw by advancing snowmelt timing E. Wilcox et al. 10.1139/as-2018-0028
61. Structure from Motion of Multi-Angle RPAS Imagery Complements Larger-Scale Airborne Lidar Data for Cost-Effective Snow Monitoring in Mountain Forests P. Broxton & W. van Leeuwen 10.3390/rs12142311
62. Multifeature GNSS-R Snow Depth Retrieval Using GA-BP Neural Network W. Liu et al. 10.1109/LGRS.2023.3291404
63. Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery Y. Bühler et al. 10.1080/01431161.2016.1275060
64. Canopy structure and topography effects on snow distribution at a catchment scale: Application of multivariate approaches M. Jenicek et al. 10.1515/johh-2017-0027
65. Winter mass balance of Drangajökull ice cap (NW Iceland) derived from satellite sub-meter stereo images J. Belart et al. 10.5194/tc-11-1501-2017
66. An Accuracy Assessment of Snow Depth Measurements in Agro-Forested Environments by UAV Lidar V. Dharmadasa et al. 10.3390/rs14071649
67. Gap-filling snow-depth time-series with Kalman Filtering-Smoothing and Expectation Maximization: Proof of concept using spatially dense wireless-sensor-network data F. Avanzi et al. 10.1016/j.coldregions.2020.103066
68. IT-SNOW: a snow reanalysis for Italy blending modeling, in situ data, and satellite observations (2010–2021) F. Avanzi et al. 10.5194/essd-15-639-2023
69. Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping L. Eberhard et al. 10.5194/tc-15-69-2021
70. Mid-Term Monitoring of Glacier’s Variations with UAVs: The Example of the Belvedere Glacier F. Ioli et al. 10.3390/rs14010028
71. Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data C. Deschamps-Berger et al. 10.5194/tc-14-2925-2020
72. European In-Situ Snow Measurements: Practices and Purposes R. Pirazzini et al. 10.3390/s18072016
73. 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. 10.7163/PrzG.2020.3.4
74. A Computational Design Analysis of UAV’s Rotor Blade in Low-Temperature Conditions for the Defence Applications S. Chevula et al. 10.1155/2021/8843453