Quantifying ice cliff evolution with multi-temporal point clouds on the debris-covered Khumbu Glacier, Nepal

Watson, C. Scott; Quincey, Duncan J.; Smith, Mark W.; Carrivick, Jonathan L.; Rowan, Ann V.; James, Michael

doi:10.1017/jog.2017.47

Cited by 57 publications

(75 citation statements)

References 68 publications

(140 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, it is too early to conclude if the differences in the literature reflect the inconsistencies amongst the different methods used or the glacier-toglacier variability. For instance, models (Sakai et al, 1998;Juen et al, 2014;Buri et al, 2016b;Reid and Brock, 2014) are 5 not directly comparable with the observations (Thompson et al, 2016;Watson et al, 2017). Up to now both neglected the flow components, and we advocate for a more consistent framework.…”

Section: Applicability To Other Glaciersmentioning

confidence: 77%

“…We surveyed a total of 12 cliffs (Table 1) with methods similar to Brun et al (2016) and Watson et al (2017). Between 200 and 400 photographs of each cliff were taken from various camera positions using a Canon EOS5D Mark II digital reflex camera with a Canon 50 mm f/2.8 fixed focal length lens (Vincent et al, 2016).…”

Section: Terrestrial Photogrammetrymentioning

confidence: 99%

“…Recent studies advocate the use of terrestrial photogrammetry to understand patterns of ice cliff retreat (e.g., Watson et al, 2017). Nevertheless, these data can only be collected in the field with some difficulty, and can only be acquired on a limited …”

mentioning

confidence: 99%

See 2 more Smart Citations

Can ice-cliffs explain the debris-cover anomaly? New insights from Changri Nup Glacier, Nepal, Central Himalaya

Brun

Wagnon

Shea

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Ice cliff backwasting on debris-covered glaciers is recognized as an important process, potentially responsible for the so-called "debris-cover anomaly", i.e. the fact that debris-covered and debris-free glacier tongues appear to have similar thinning rates in Himalaya. In this study, we assess the total contribution of ice cliff backwasting to the net ablation of the tongue of the Changri Nup Glacier over two years. Detailed terrestrial photogrammetry surveys were conducted on select ice cliffs in November 2015 and 2016, and the entire glacier tongue was surveyed with unmanned air vehicles (UAVs) and 5Pléiades tri-stereo imagery in November 2015, November 2016, and November 2017. The total difference between the volume loss from ice cliffs measured with the terrestrial photogrammetry, considered as the reference data, and the UAV and Pléiades was less than 3 % and 7 %, respectively, demonstrating the ability of these datasets to measure volume loss from ice cliffs. For the period November 2015-November 2016 (resp. November 2016-November 2017), using UAV and Pléiades over the entire glacier tongue, we found that ice cliffs, which cover 7 % (resp. 8 %) of the planar area, contribute to 23 ± 5 % (resp. 24 ± 10 5 %) of the total net ablation of Changri Nup Glacier tongue. Ice cliffs have a net ablation rate 3.1 ± 0.6 (resp. 3.0 ± 0.6) times higher than the average glacier tongue surface. However, on Changri Nup Glacier, ice cliffs cannot compensate for the reduction of ablation due to debris-cover. Reduced ablation and lower emergence velocities on debris-covered glacier tongues could be responsible for the debris-cover anomaly.

show abstract

Section: Applicability To Other Glaciersmentioning

confidence: 77%

Section: Terrestrial Photogrammetrymentioning

confidence: 99%

See 1 more Smart Citation

Can ice-cliffs explain the debris-cover anomaly? New insights from Changri Nup Glacier, Nepal, Central Himalaya

Brun

Wagnon

Shea

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Although Photoscan is the most commonly used SfM-MVS software in geoscience applications (e.g., Lucieer et al, 2013;Turner et al, 2014;Ryan et al, 2015;Kraaijenbrink P.D.A. et al, 2016;Mallalieu et al, 2017;Ryan et al, 2017;Watson et al, 2017), and it has also been proven to work with thermal imagery (Turner et al, 2014), we chose to use Postflight because of its seamless integration with the thermoMAP camera (SenseFly, 2017a).…”

Section: Thermal Imagery Processingmentioning

confidence: 99%

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

et al. 2018

View full text Add to dashboard Cite

A layer of debris cover often accumulates across the surface of glaciers in active mountain ranges with exceptionally steep terrain, such as the Andes, Himalaya, and New Zealand Alps. Such a supraglacial debris layer has a major influence on a glacier's surface energy budget, enhancing radiation absorption, and melt when the layer is thin, but insulating the ice when thicker than a few cm. Information on spatially distributed debris surface temperature has the potential to provide insight into the properties of the debris, its effects on the ice below and its influence on the near-surface boundary layer. Here, we deploy an unmanned aerial vehicle (UAV) equipped with a thermal infrared sensor on three separate missions over one day to map changing surface temperatures across the debris-covered Lirung Glacier in the Central Himalaya. We present a methodology to georeference and process the acquired thermal imagery, and correct for emissivity and sensor bias. Derived UAV surface temperatures are compared with distributed simultaneous in situ temperature measurements as well as with Landsat 8 thermal satellite imagery. Results show that the UAV-derived surface temperatures vary greatly both spatially and temporally, with −1.4 ± 1.8, 11.0 ± 5.2, and 15.3 ± 4.7 • C for the three flights (mean ± sd), respectively. The range in surface temperatures over the glacier during the morning is very large with almost 50 • C. Ground-based measurements are generally in agreement with the UAV imagery, but considerable deviations are present that are likely due to differences in measurement technique and approach, and validation is difficult as a result. The difference in spatial and temporal variability captured by the UAV as compared with much coarser satellite imagery is striking and it shows that satellite derived temperature maps should be interpreted with care. We conclude that UAVs provide a suitable means to acquire surface temperature maps of debris-covered glacier surfaces at high spatial and temporal resolution, but that there are caveats with regard to absolute temperature measurement.

show abstract

“…DEM of difference, C2C, M3C2) to measure the distance between two point clouds. The M3C2 tool is available in the open source CloudCompare software and has been widely used in a range of environments (Barnhart and Crosby, 2013;Lague et al, 2013;Gómez-Gutiérrez et al, 2015;Stumpf et al, 2015;Mallalieu et al, 2017;Morgan et al, 2017;Watson et al, 2017). The M3C2 tool is available in the open source CloudCompare software and has been widely used in a range of environments (Barnhart and Crosby, 2013;Lague et al, 2013;Gómez-Gutiérrez et al, 2015;Stumpf et al, 2015;Mallalieu et al, 2017;Morgan et al, 2017;Watson et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Patterns and drivers of peat topographic changes determined from Structure‐from‐Motion photogrammetry at field plot and laboratory scales

Grayson

Smith

et al. 2019

Earth Surf Processes Landf

View full text Add to dashboard Cite

Little is known about the spatial and temporal variability of peat erosion nor some of its topographic and weather‐related drivers. We present field and laboratory observations of peat erosion using Structure‐from‐Motion (SfM) photogrammetry. Over a 12 month period, 11 repeated SfM surveys were conducted on four geomorphological sites of 18–28 m2 (peat hagg, gully wall, riparian area and gully head) in a blanket peatland in northern England. A net topographic change of –14 to +30 mm yr–1 for the four sites was observed during the whole monitoring period. Cold conditions in the winter of 2016 resulted in highly variable volume change (net surface topographic rise first and lowering afterwards) via freeze–thaw processes. Long periods of dry conditions in the summer of 2017 led to desiccation and drying and cracking of the peat surface and a corresponding surface lowering. Topographic changes were mainly observed over short‐term intervals when intense rainfall, flow wash, needle‐ice production or surface desiccation was observed. In the laboratory, we applied rainfall simulations on peat blocks and compared the peat losses quantified by traditional sediment flux measurements with SfM derived topographic data. The magnitude of topographic change determined by SfM (mean value: 0.7 mm, SD: 4.3 mm) was very different to the areal average determined by the sediment yield from the blocks (mean value: –0.1 mm, SD: 0.1 mm). Topographic controls on spatial patterns of topographic change were illustrated from both field and laboratory surveys. Roughness was positively correlated to positive topographic change and was negatively correlated to negative topographic change at field plot scale and laboratory macroscale. Overall, the importance of event‐scale change and the direct relationship between surface roughness and the rate of topographic change are important characteristics which we suggest are generalizable to other environments. © 2018 John Wiley & Sons, Ltd.

show abstract

Quantifying ice cliff evolution with multi-temporal point clouds on the debris-covered Khumbu Glacier, Nepal

Cited by 57 publications

References 68 publications

Can ice-cliffs explain the debris-cover anomaly? New insights from Changri Nup Glacier, Nepal, Central Himalaya

Can ice-cliffs explain the debris-cover anomaly? New insights from Changri Nup Glacier, Nepal, Central Himalaya

Mapping Surface Temperatures on a Debris-Covered Glacier With an Unmanned Aerial Vehicle

Patterns and drivers of peat topographic changes determined from Structure‐from‐Motion photogrammetry at field plot and laboratory scales

Contact Info

Product

Resources

About