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Innovative and Synergistic Approaches for Multi-Scale Glacier Monitoring Using Remote Sensing Technologies

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (1 October 2021) | Viewed by 10798

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Special Issue Editors

Dr. Ryan Wilson

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Guest Editor

Department of Biological and Geographical Sciences, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
Interests: glacial hazards; remote sensing; glacier mapping; glacier dynamics; andean glaciers; satellite-based mapping; UAV-based mapping

Dr. Daniel Falaschi

E-Mail Website
Guest Editor

Instituto Argentino de Nivologia, Glaciologia y Ciencias Ambientales (IANIGLA) Mendoza, Argentina
Interests: remote sensing of glaciers; glacier change; glacier dynamics; glacier instabilities; digital terrain analysis; central and patagonian andes

Dr. Adina Racoviteanu

E-Mail Website
Guest Editor

Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK
Interests: glacier changes in the high mountains using remote sensing and geospatial techniques; glacial hazards; himalayas and the andes

Special Issue Information

Dear Colleagues,

In recent decades, advances in space and air-borne remote sensing technology have led to a massive increase in data available for glacier monitoring. These advances have improved our ability to observe and understand glacier changes at multiple spatial and temporal scales, allowing the scientific community to investigate remote, difficult to access glaciers. However, there are now opportunities to push our understanding of glacier behaviour forward through the development of multi-sensor, web-based data platforms. This can be facilitated by implementing a synergistic approach, which may include innovative glacier mapping techniques, open-source coding and sophisticated geospatial methodologies, among others. With this in mind, we invite research papers that 1) highlight cutting-edge remote sensing and geospatial technologies to monitor high mountain glaciers, 2) address the current gaps, state and remaining challenges faced in using such new technologies and 3) review data challenges, data sharing difficulties and present innovative solutions to overcome them.

Potential paper topics include, but are not limited to:

Use of innovative, cutting-edge remote sensing technologies, including thermal data and/or newly launched sensors to monitor the current state of glaciers;

Use of web-based interfaces such as Google Earth Engine, big data and open source coding that incorporate multi-sensor data and facilitate automated mapping of glacier boundaries, surface characteristics and their changes over time;

Development of cross-disciplinary approaches that allow for holistic glacier assessments;

Adapting micro-scale image analysis tools routinely used in other fields (e.g. medical imaging, material texture analysis, etc.) for application in larger-scale glacier monitoring;

Synergy between traditional GIS technologies and recent, advanced technologies (g. machine learning, object oriented approaches, etc.);

Fusion of multi-sensor optical remote sensing with microwave data;

Assessments of current uncertainties related to space- and/or air-borne glacier mapping and outlook for future developments.

We would like to encourage submissions from early-career researchers, particularly those based in countries encompassing the high mountain ranges of the world.

Dr. Ryan Wilson
Dr. Daniel Falaschi
Dr. Adina Racoviteanu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Glacier monitoring
High Mountain areas
Multi-sensor
Big data
Machine learning
Cross-disciplinary

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Research

28 pages, 5817 KiB

Open AccessArticle

Co-Registration Methods and Error Analysis for Four Decades (1979–2018) of Glacier Elevation Changes in the Southern Patagonian Icefield

by Paulina Vacaflor, Maria Gabriela Lenzano, Alberto Vich and Luis Lenzano

Remote Sens. 2022, 14(4), 820; https://doi.org/10.3390/rs14040820 - 9 Feb 2022

Cited by 4 | Viewed by 2718

Abstract

The main goal of this paper is to compare two co-registration methods for geodetic mass balance (GMB) calculation in 28 glaciers making up the Upper Santa Cruz River basin, Southern Patagonian Icefield (SPI), from 1979 to 2018. For this purpose, geospatial data have been used as primary sources: Hexagon KH-9, ASTER, and LANDSAT optical images; SRTM digital radar elevation model; and ICESat elevation profiles. After the analyses, the two co-registration methods, namely M1, based on horizontal displacements and 3D shift vectors, and M2, based on three-dimensional transformations, turned out to be similar. The errors in the GMB were analyzed through a k index that considers, among other variables, the error in elevation change by testing four interpolation methods for filling gaps. We found that, in 63% of the cases, the relative error in elevation change contributes 90% or more to k index. The GMB throughout our study area reported that a loss value of −1.44 ± 0.15 m w. e. a⁻¹ (−3.0 Gt a⁻¹) and an ice thinning median of −1.38 ± 0.11 m a⁻¹ occurred within the study period. The glaciers that showed the most negative GMB values were Upsala, with an annual elevation change median of −2.07 ± 0.18 m w. e. a⁻¹, and Ameghino, with −2.31 ± 0.22 m w. e. a⁻¹. Full article

(This article belongs to the Special Issue Innovative and Synergistic Approaches for Multi-Scale Glacier Monitoring Using Remote Sensing Technologies)

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15 pages, 2994 KiB

Open AccessArticle

Geodetic Mass Balance of Haxilegen Glacier No. 51, Eastern Tien Shan, from 1964 to 2018

by Chunhai Xu, Zhongqin Li, Feiteng Wang, Jianxin Mu and Xin Zhang

Remote Sens. 2022, 14(2), 272; https://doi.org/10.3390/rs14020272 - 7 Jan 2022

Cited by 2 | Viewed by 2501

Abstract

The eastern Tien Shan hosts substantial mid-latitude glaciers, but in situ glacier mass balance records are extremely sparse. Haxilegen Glacier No. 51 (eastern Tien Shan, China) is one of the very few well-measured glaciers, and comprehensive glaciological measurements were implemented from 1999 to 2011 and re-established in 2017. Mass balance of Haxilegen Glacier No. 51 (1999–2015) has recently been reported, but the mass balance record has not extended to the period before 1999. Here, we used a 1:50,000-scale topographic map and long-range terrestrial laser scanning (TLS) data to calculate the area, volume, and mass changes for Haxilegen Glacier No. 51 from 1964 to 2018. Haxilegen Glacier No. 51 lost 0.34 km² (at a rate of 0.006 km² a⁻¹ or 0.42% a⁻¹) of its area during the period 1964–2018. The glacier experienced clearly negative surface elevation changes and geodetic mass balance. Thinning occurred almost across the entire glacier surface, with a mean value of −0.43 ± 0.12 m a⁻¹. The calculated average geodetic mass balance was −0.36 ± 0.12 m w.e. a⁻¹. Without considering the error bounds of mass balance estimates, glacier mass loss over the past 50 years was in line with the observed and modeled mass balance (−0.37 ± 0.22 m w.e. a⁻¹) that was published for short time intervals since 1999 but was slightly less negative than glacier mass loss in the entire eastern Tien Shan. Our results indicate that Riegl VZ^®-6000 TLS can be widely used for mass balance measurements of unmonitored individual glaciers. Full article

(This article belongs to the Special Issue Innovative and Synergistic Approaches for Multi-Scale Glacier Monitoring Using Remote Sensing Technologies)

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22 pages, 5695 KiB

Open AccessArticle

Temporal Variability of Surface Reflectance Supersedes Spatial Resolution in Defining Greenland’s Bare-Ice Albedo

by Tristram D. L. Irvine-Fynn, Pete Bunting, Joseph M. Cook, Alun Hubbard, Nicholas E. Barrand, Edward Hanna, Andy J. Hardy, Andrew J. Hodson, Tom O. Holt, Matthias Huss, James B. McQuaid, Johan Nilsson, Kathrin Naegeli, Osian Roberts, Jonathan C. Ryan, Andrew J. Tedstone, Martyn Tranter and Christopher J. Williamson

Remote Sens. 2022, 14(1), 62; https://doi.org/10.3390/rs14010062 - 23 Dec 2021

Cited by 4 | Viewed by 4251

Abstract

Ice surface albedo is a primary modulator of melt and runoff, yet our understanding of how reflectance varies over time across the Greenland Ice Sheet remains poor. This is due to a disconnect between point or transect scale albedo sampling and the coarser spatial, spectral and/or temporal resolutions of available satellite products. Here, we present time-series of bare-ice surface reflectance data that span a range of length scales, from the 500 m for Moderate Resolution Imaging Spectrometer’s MOD10A1 product, to 10 m for Sentinel-2 imagery, 0.1 m spot measurements from ground-based field spectrometry, and 2.5 cm from uncrewed aerial drone imagery. Our results reveal broad similarities in seasonal patterns in bare-ice reflectance, but further analysis identifies short-term dynamics in reflectance distribution that are unique to each dataset. Using these distributions, we demonstrate that areal mean reflectance is the primary control on local ablation rates, and that the spatial distribution of specific ice types and impurities is secondary. Given the rapid changes in mean reflectance observed in the datasets presented, we propose that albedo parameterizations can be improved by (i) quantitative assessment of the representativeness of time-averaged reflectance data products, and, (ii) using temporally-resolved functions to describe the variability in impurity distribution at daily time-scales. We conclude that the regional melt model performance may not be optimally improved by increased spatial resolution and the incorporation of sub-pixel heterogeneity, but instead, should focus on the temporal dynamics of bare-ice albedo. Full article

(This article belongs to the Special Issue Innovative and Synergistic Approaches for Multi-Scale Glacier Monitoring Using Remote Sensing Technologies)

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