Special Issue "Remote Sensing of Land Ice"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Geophysics".

Deadline for manuscript submissions: closed (31 July 2018).

Special Issue Editor

Dr. Sebastian Bjerregaard Simonsen
E-Mail Website
Guest Editor
DTU Space, National Space Institute, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
Interests: ice sheet mass balance; ice dynamics; radar and laser altimetry; CryoSat-2, ICESat-1 and ICESat-2, Cal/Val campaigns; firn compaction; surface processes
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Special Issue Information

Dear Colleagues,

The application of remote sensing data has long been recognized as an invaluable source of information in areas covered by land ice. These areas are often located in remote and hostile environments were remote sensing is the sole source of high-temporal/spatial data.

This Special Issue of Geosciences aims at gathering high-quality original research articles, reviews, and technical notes on the use of remote sensing studies for land ice. We invite contributions from a wide spectrum of remote sensing techniques that are presently available, e.g., optical, multi/hyper-spectral imagery, altimetry, and gravimetry. Both the application of remote sensing datasets to monitor land ice and studies applying in situ data to provide ground truth of remote sensing data are encouraged.

I also encourage you to send me a short abstract outlining the purpose of the research and the principal results obtained, in order to verify (at an early stage) if the contribution you intend to submit fits with the objectives of this Special Issue.

Dr. Sebastian Bjerregaard Simonsen
Guest Editor

Manuscript Submission Information

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Keywords

  • Sea level rise
  • Ice sheets, Ice caps and glaciers
  • Land ice volume and mass change
  • Ice/snow Albedo
  • Ice velocities
  • New opportunities in remote sensing
  • Ground truth

Published Papers (5 papers)

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Research

Open AccessArticle
Modeling Dry-Snow Densification without Abrupt Transition
Geosciences 2018, 8(12), 464; https://doi.org/10.3390/geosciences8120464 - 07 Dec 2018
Abstract
An empirical model for the densification of dry snow has been calibrated using strain-rate data from Pine Island Glacier basin, Antarctica. The model provides for a smooth transition between Stage 1 and Stage 2 densification, and leads to an analytical expression for density [...] Read more.
An empirical model for the densification of dry snow has been calibrated using strain-rate data from Pine Island Glacier basin, Antarctica. The model provides for a smooth transition between Stage 1 and Stage 2 densification, and leads to an analytical expression for density as a function of depth. It introduces two new parameters with a simple physical basis: transition density ρ T and a scaling factor, M, which controls the extent of the transition zone. The standard (Herron and Langway) parameterization is used for strain rates away from the transition zone. Calibration, though tentative, produces best parameter values of ρ T = 580 kg m 3 and M = 7 for the region. Using these values, the transition model produces better simulations of snow profiles from Pine Island Glacier basin than the well-established Herron and Langway and Ligtenberg models, both of which postulate abrupt transition. Simulation of density profiles from other sites using M = 7 produces the best values of ρ T = 550 kg m 3 for a high accumulation site and 530 kg m 3 for a low accumulation site, suggesting that transition density may vary with climatic conditions. The variation of bubble close-off depth and depth-integrated porosity with mean annual accumulation predicted by the transition model is similar to that predicted by the Simonsen model tuned for Greenland. Full article
(This article belongs to the Special Issue Remote Sensing of Land Ice)
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Open AccessArticle
Present Glaciers of Tavan Bogd Massif in the Altai Mountains, Central Asia, and Their Changes since the Little Ice Age
Geosciences 2018, 8(11), 414; https://doi.org/10.3390/geosciences8110414 - 12 Nov 2018
Abstract
The Tavan Bogd mountains (of which, the main peak, Khuiten Uul, reaches 4374 m a.s.l.) are situated in the central part of the Altai mountain system, in the territories of Russia, Mongolia and China. The massif is the largest glacierized area of Altai. [...] Read more.
The Tavan Bogd mountains (of which, the main peak, Khuiten Uul, reaches 4374 m a.s.l.) are situated in the central part of the Altai mountain system, in the territories of Russia, Mongolia and China. The massif is the largest glacierized area of Altai. The purposes of this study were to provide a full description of the scale and structure of the modern glacierized area of the Tavan Bogd massif, to reconstruct the glaciers of the Little Ice Age (LIA), to estimate the extent of the glaciers in 1968, and to determine the main glacial trends, and their causes, from the peak of the LIA. This work was based on the results of long-term field studies and analysis of satellite and aerial data. At the peak of the LIA, Tavan Bogd glaciation comprised 243 glaciers with a total area of 353.4 km2. From interpretation of Corona images, by 1968 the number of glaciers had decreased to 236, with a total area of 242 km2. In 2010, there were 225 glaciers with a total area of 201 km2. Thus, since the peak of the LIA, the glacierized area of the Tavan Bogd mountains decreased by 43%, which is somewhat less than for neighboring glacial centers (i.e., Ikh-Turgen, Tsambagarav, Tsengel-Khairkhan and Mongun-Taiga mountains). The probable causes are higher altitude and the predominance of larger glaciers resistant to warming. Accordingly, the smallest decline in Tavan Bogd occurred in the basins of the Tsagan-Gol (31.7%) and Sangadyr (36.4%) rivers where the largest glaciers are located. In contrast, on the lower periphery of the massif, where small glaciers predominate, the relative reduction was large (74–79%). In terms of general retreat trends, large valley glaciers retreated faster in 1968–1977 and after 2010. During the 1990s, the retreat was slow. After 2010, glacial retreat was rapid. The retreat of glaciers in the last 50–60 years was caused by a trend decrease in precipitation until the mid-1970s, and a sharp warming in the 1990s and early 2000s. Full article
(This article belongs to the Special Issue Remote Sensing of Land Ice)
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Open AccessArticle
HF/VHF Radar Sounding of Ice from Manned and Unmanned Airborne Platforms
Geosciences 2018, 8(5), 182; https://doi.org/10.3390/geosciences8050182 - 16 May 2018
Cited by 2
Abstract
Ice thickness and bed topography of fast-flowing outlet glaciers are large sources of uncertainty for the current ice sheet models used to predict future contributions to sea-level rise. Due to a lack of coverage and difficulty in sounding and imaging with ice-penetrating radars, [...] Read more.
Ice thickness and bed topography of fast-flowing outlet glaciers are large sources of uncertainty for the current ice sheet models used to predict future contributions to sea-level rise. Due to a lack of coverage and difficulty in sounding and imaging with ice-penetrating radars, these regions remain poorly constrained in models. Increases in off-nadir scattering due to the highly crevassed surfaces, volumetric scattering (due to debris and/or pockets of liquid water), and signal attenuation (due to warmer ice near the bottom) are all impediments in detecting bed-echoes. A set of high-frequency (HF)/very high-frequency (VHF) radars operating at 14 MHz and 30–35 MHz were developed at the University of Kansas to sound temperate ice and outlet glaciers. We have deployed these radars on a small unmanned aircraft system (UAS) and a DHC-6 Twin Otter. For both installations, the system utilized a dipole antenna oriented in the cross-track direction, providing some performance advantages over other temperate ice sounders operating at lower frequencies. In this paper, we describe the platform-sensor systems, field operations, data-processing techniques, and preliminary results. We also compare our results with data from other ice-sounding radars that operate at frequencies both above (Center for Remote Sensing of Ice Sheets (CReSIS) Multichannel Coherent Depth Sounder (MCoRDS)) and below (Jet Propulsion Laboratory (JPL) Warm Ice Sounding Explorer (WISE)) our HF/VHF system. During field campaigns, both unmanned and manned platforms flew closely spaced parallel and repeat flight lines. We examine these data sets to determine image coherency between flight lines and discuss the feasibility of forming 2D synthetic apertures by using such a mission approach. Full article
(This article belongs to the Special Issue Remote Sensing of Land Ice)
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Open AccessArticle
Mapping the Loss of Mt. Kenya’s Glaciers: An Example of the Challenges of Satellite Monitoring of Very Small Glaciers
Geosciences 2018, 8(5), 174; https://doi.org/10.3390/geosciences8050174 - 11 May 2018
Cited by 2
Abstract
Since the last complete glacier mapping of Mt. Kenya in 2004, strong glacier retreat and glacier disintegration have been reported. Here, we compile and present a new glacier inventory of Mt. Kenya to document recent glacier change. Glacier area and mass changes were [...] Read more.
Since the last complete glacier mapping of Mt. Kenya in 2004, strong glacier retreat and glacier disintegration have been reported. Here, we compile and present a new glacier inventory of Mt. Kenya to document recent glacier change. Glacier area and mass changes were derived from an orthophoto and digital elevation model extracted from Pléiades tri-stereo satellite images. We additionally explore the feasibility of using freely available imagery (Sentinel-2) and an alternative elevation model (TanDEM-X-DEM) for monitoring very small glaciers in complex terrain, but both proved to be inappropriate; Sentinel-2 because of its too coarse horizontal resolution compared to the very small glaciers, and TanDEM-X-DEM because of errors in the steep summit area of Mt. Kenya. During 2004–2016, the total glacier area on Mt. Kenya decreased by 121.0 × 10³ m² (44%). The largest glacier (Lewis) lost 62.8 × 10³ m² (46%) of its area and 1.35 × 10³ m³ (57%) of its volume during the same period. The mass loss of Lewis Glacier has been accelerating since 2010 due to glacier disintegration, which has led to the emergence of a rock outcrop splitting the glacier in two parts. If the current retreat rates prevail, Mt. Kenya’s glaciers will be extinct before 2030, implying the cessation of the longest glacier monitoring record of the tropics. Full article
(This article belongs to the Special Issue Remote Sensing of Land Ice)
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Open AccessArticle
Glacier Changes on the Pik Topografov Massif, East Sayan Range, Southeast Siberia, from Remote Sensing Data
Geosciences 2018, 8(5), 148; https://doi.org/10.3390/geosciences8050148 - 24 Apr 2018
Cited by 1
Abstract
Small mountain glaciers represent the most abundant class in many glaciarized areas around the world; however, less is known about their recent area changes under climatic variability of the last decades. The recent fluctuations of glaciers located in the inner parts of continents [...] Read more.
Small mountain glaciers represent the most abundant class in many glaciarized areas around the world; however, less is known about their recent area changes under climatic variability of the last decades. The recent fluctuations of glaciers located in the inner parts of continents are the least studied. In this study we present the results of repeated mapping of seven small (<1.5 km2) glaciers located in a continental setting on the northern slope of the Pik Topografov massif, East Sayan Range, southeast Siberia. The multitemporal glacier inventory was derived from the late summer Landsat TM/ETM+ scenes acquired between 1986 and 2010. Glacier outlines were mapped with thresholded ratio (TM3/TM5) method. Topographic inventory parameters were measured from SRTM DEM. Glacier outlines of the Little Ice Age maximum (LIA, ~1850) were reconstructed from terminal moraines widely distributed around the glacier snouts. The results indicate a total ice area decrease from 8.1 km2 in the LIA to 3.8 km2 in 2010 (53%, 0.33% year−1). We revealed accelerated area shrinkage between 1991 and 2001 (almost two times higher than during the period 1986–2010), while between 2001 and 2010, the ice area did not change significantly. Overall, the glacier changes are consistent with the regional climatic trends (winter precipitation and summer temperature). Local topographic settings significantly impacted the glacier dynamics. Full article
(This article belongs to the Special Issue Remote Sensing of Land Ice)
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