Optical remote sensing of glacier characteristics::A review with focus on the Himalaya

The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya

An integrated deep learning and object-based image analysis approach for mapping debris- covered glaciers

Evaluating glacial change and the subsequent water stores in high mountains is becoming increasingly necessary, and in order to do this, models need reliable and consistent glacier data. These often come from global inventories, usually constructed from multi-temporal satellite imagery. However, there are limitations to these datasets. While clean ice can be mapped relatively easily using spectral band ratios, mapping debris-covered ice is more difficult due to the spectral similarity of supraglacial debris to the surrounding terrain. Therefore, analysts often employ manual delineation, a time-consuming and subjective approach to map debris-covered ice extents. Given the increasing prevalence of supraglacial debris in high mountain regions, such as High Mountain Asia, a systematic, objective approach is needed. The current study presents an approach for mapping debris-covered glaciers that integrates a convolutional neural network and object-based image analysis into one seamless classification workflow, applied to freely available and globally applicable Sentinel-2 multispectral, Landsat-8 thermal, Sentinel-1 interferometric coherence, and geomorphometric datasets. The approach is applied to three different domains in the Central Himalayan and the Karakoram ranges of High Mountain Asia that exhibit varying climatic regimes, topographies and debris-covered glacier characteristics. We evaluate the performance of the approach by comparison with a manually delineated glacier inventory, achieving F-score classification accuracies of 89.2%–93.7%. We also tested the performance of this approach on declassified panchromatic 1970 Corona KH-4B satellite imagery in the Manaslu region of Nepal, yielding accuracies of up to 88.4%. We find our approach to be robust, transferable to other regions, and accurate over regional (>4,000 km2) scales. Integrating object-based image analysis with deep-learning within a single workflow overcomes shortcomings associated with convolutional neural network classifications and permits a more flexible and robust approach for mapping debris-covered glaciers. The novel automated processing of panchromatic historical imagery, such as Corona KH-4B, opens the possibility of exploiting a wealth of multi-temporal data to understand past glacier changes.publishedVersio

Recent Evolution of Glaciers in the Manaslu Region of Nepal From Satellite Imagery and UAV Data (1970–2019)

Glacierized mountain ranges such as the Himalaya comprise a variety of glacier types, including clean and debris-covered glaciers. Monitoring their behaviour over time requires an assessment of changes in area and elevation along with surface features and geomorphology. In this paper we quantify the surface evolution of glacier systems in the Manaslu region of Nepal over the last five decades using 2013/2019 multi-sensor imagery and elevation data constructed from 1970 declassified Corona imagery and 1970 declassified Corona imagery. We investigate area changes, glacier thickness, geodetic glacier mass balance and surface velocity changes at regional scales and focus on the Ponkar Glacier and Thulagi Glacier and Lake for an in-depth assessment of surface geomorphology and surface feature dynamics (ponds, vegetation and ice cliffs). The time series of surface elevation changes for the lower ablation area of Ponkar Glacier is extended using 2019 UAV-based imagery and field-based ablation rates measured over the period 2016–2019. Glaciers in the Manaslu region experienced a mean area loss of −0.26 ± 0.0001% a−1 between 1970 and 2019. The mean surface lowering was −0.20 ± 0.02 ma−1 over the period 1970 to 2013, corresponding to a regional geodetic mass balance of −0.17 ± 0.03 m w. e.a−1. Overall, debris-covered glaciers had slightly higher thinning rates compared to clean ice glaciers; lake-terminating glaciers had double thinning rates compared to land-terminating glaciers. Individual glacier mass balance was negatively controlled by glacier slope and mean glacier elevation. During the period 1970 to 2013, Ponkar Glacier had a geodetic mass balance of −0.06 ± 0.01 m w. e.a−1, inversely correlated with parts of the central trunk thickening. Between 2013 and 2019 there was a nine-fold increase in the thinning rates over the lower parts of the glacier tongue relative to the period 1970–2013. Ice-surface morphology changes between 1970 and 2019 on Ponkar Glacier include a decrease in ogives and open crevasses, an increase in ice cliffs and ponds and the expansion of the supraglacial debris and ice-surface vegetation. These changes point to reduced ice-dynamic activity and are commensurate with the observed recession and negative glacier mass balance over the last five decades.publishedVersio

Recent Evolution of Glaciers in the Manaslu Region of Nepal From Satellite Imagery and UAV Data (1970–2019)

Glacierized mountain ranges such as the Himalaya comprise a variety of glacier types, including clean and debris-covered glaciers. Monitoring their behaviour over time requires an assessment of changes in area and elevation along with surface features and geomorphology. In this paper we quantify the surface evolution of glacier systems in the Manaslu region of Nepal over the last five decades using 2013/2019 multi-sensor imagery and elevation data constructed from 1970 declassified Corona imagery and 1970 declassified Corona imagery. We investigate area changes, glacier thickness, geodetic glacier mass balance and surface velocity changes at regional scales and focus on the Ponkar Glacier and Thulagi Glacier and Lake for an in-depth assessment of surface geomorphology and surface feature dynamics (ponds, vegetation and ice cliffs). The time series of surface elevation changes for the lower ablation area of Ponkar Glacier is extended using 2019 UAV-based imagery and field-based ablation rates measured over the period 2016–2019. Glaciers in the Manaslu region experienced a mean area loss of −0.26 ± 0.0001% a−1 between 1970 and 2019. The mean surface lowering was −0.20 ± 0.02 ma−1 over the period 1970 to 2013, corresponding to a regional geodetic mass balance of −0.17 ± 0.03 m w. e.a−1. Overall, debris-covered glaciers had slightly higher thinning rates compared to clean ice glaciers; lake-terminating glaciers had double thinning rates compared to land-terminating glaciers. Individual glacier mass balance was negatively controlled by glacier slope and mean glacier elevation. During the period 1970 to 2013, Ponkar Glacier had a geodetic mass balance of −0.06 ± 0.01 m w. e.a−1, inversely correlated with parts of the central trunk thickening. Between 2013 and 2019 there was a nine-fold increase in the thinning rates over the lower parts of the glacier tongue relative to the period 1970–2013. Ice-surface morphology changes between 1970 and 2019 on Ponkar Glacier include a decrease in ogives and open crevasses, an increase in ice cliffs and ponds and the expansion of the supraglacial debris and ice-surface vegetation. These changes point to reduced ice-dynamic activity and are commensurate with the observed recession and negative glacier mass balance over the last five decades.publishedVersio

Challenges and recommendations in mapping of glacier parameters from space::Results of the 2008 global land ice measurements from space (GLIMS) workshop, Boulder, Colorado, USA

On 16–18 June 2008 the US National Snow and Ice Data Center held a GLIMS workshop inBoulder, CO, USA, focusing on formulating procedures and best practices for operational glaciermapping using satellite imagery. Despite the progress made in recent years, there still remain many cases where automatic delineation of glacier boundaries in satellite imagery is difficult, error prone or timeconsuming. This workshop identified six themes for consideration by focus groups: (1) mapping clean ice and lakes; (2) mapping ice divides; (3) mapping debris-covered glaciers; (4) assessing changes in glacier area and elevation through comparisons with older data; (5) digital elevation model (DEM) generation from satellite stereo pairs; and (6) accuracy and error analysis. Talks presented examples and work in progress for each of these topics, and focus groups worked on compiling a summary of available algorithms and procedures to address and avoid identified hurdles. Special emphasis was given to establishing standard protocols for glacier delineation and analysis, creating illustrated tutorials and providing source code for available methods. This paper summarizes the major results of the 2008 GLIMS workshop, with an emphasis on definitions, methods and recommendations for satellite data processing. While the list of proposed methods and recommendations is not comprehensive and is still a work in progress, our goal here is to provide a starting point for the GLIMS regional centers as well as for the wider glaciological community in terms of documentation on possible pitfalls along with potential solutions

Himalayan Glaciers (India, Bhutan, Nepal): Satellite Observations of Thinning and Retreat

This chapter summarizes the current state of remote sensing of glaciers in the India, Nepal, and Bhutan regions of the Himalaya, and focuses on new methods for assessing glacier change. Glaciers in these Himalaya regions exhibit complex patterns of changes due to the unique and variable climatic, topographic, and glaciological parameters present in this region. The theoretical understanding of glaciers in the Himalaya is limited by lack of sufficient observations due to terrain breadth and complexity, severe weather conditions, logistic difficulties, and geopolitics. Mapping and assessing these glaciers with satellite imagery is also challenging due to inherent sensor limitations and information extraction issues. Thus, we still lack a complete understanding of the magnitude of feedbacks, and in some places even their sign, between climate changes and glacier response in this region. In this chapter we present the current status of glaciers in various climatic regimes of the Himalaya, ranging from the monsoon-influenced regions of the central–eastern Himalaya (Nepal, Garhwal, Sikkim, and Bhutan) through the monsoon transition zone of Himachal Pradesh (India), to the dry areas of Ladakh (western Himalaya). The case studies presented here illustrate the use of remote sensing and elevation data coupled with glaciermapping techniques for glacier area and elevation change detection and ice flow modeling in the context of the Himalaya