Glacier mapping in high mountains using DEMs, Landsat and ASTER data

Glaciers are sensitive climate indicators and thus subject to monitoring of environmental and climate changes. Remote sensing techniques are often the only way to analyze glaciers in remote mountains and to monitor a large number of glaciers at the same time. Although several glacier mapping methods exist, often, results are still not good enough for in-depth conclusions. In particular, this is true for debris-covered glaciers. For the Bernina Group in the Swiss Alps and for the northern Tien Shan in Kazakhstan and Kyrgyzstan a glacier mapping was undertaken employing digital elevation models (DEMs). DEMs were generated from ASTER and SRTM3 data and compared with each other and -for the Bernina Group-compared with the Swiss DHM25L2. Whereas ASTER DEM elevations are too high on average, SRTM3 DEM elevations are slightly too low. However, both DEMs are of good use for glacier delineation. The glacier mapping approach includes Landsat TM4/TM5-ratio images, multispectral and morphometric analysis. Results are satisfying for debris-free and larger debris-covered glaciers in both study areas. The next step should be an automated glacier mapping method

Rock glaciers

Rock glaciers, a key element of alpine mountain geomorphic systems, consist of coarse surface debris that insulates an ice-core or ice-debris mixture. Rates of movement of active rock glaciers vary from 1 to more than 100 cm yr–1. Rock glaciers exist in all major mountain ranges where permafrost occurs but are more common in dryer climates with high talus accumulation rates. New geospatial techniques, high-resolution data sources, and improved technology will contribute to a better understanding of these landforms. This chapter provides an in-depth summary of important research findings pertaining to rock glaciers and offers insight to future research.Preprin

Mapping of glacial lakes using Sentinel-1 and Sentinel-2 data and a random forest classifier : strengths and challenges

Sonam Wangchuk acknowledges ESKAS - Swiss Government Excellence Scholarship for Foreign Scholars, Swiss Polar Institute, and University of Zurich for supporting the research. Tobias Bolch thanks the Swiss National Science Foundation [IZLCZ2_169979/1].Glacial lakes pose a serious threat to downstream areas and significantly impact glacier melt. The number and area of lakes has grown in most regions during the last decades due to the ongoing atmospheric warming and retreating glaciers. It is therefore important to identify and monitor these lakes. However, mapping of glacial lakes in alpine regions is challenged by many factors. These factors include small size of glacial lakes, cloud cover in optical satellite images, cast shadows from mountains and clouds, seasonal snow in satellite images, varying degrees of turbidity amongst glacial lakes, and frozen glacial lake surface. In our study, we have developed a fully automated method for mapping glacial lake across alpine regions including the Python package called “GLakeMap”. The method uses multi-source data such as Sentinel-1 Synthetic Aperture Radar and Sentinel-2 Multi-spectral Instrument data, digital elevation model, and a random forest classifier model. We use multi-source datasets as inputs for rule-based segmentation of images, mainly aiming at extracting glacial lake objects from satellite images using a set of rules. Segmented objects are then classified either as glacial lake or non-glacial lake objects by the random forest classifier model. The method was tested in eight sites across alpine regions mainly located in High Mountain Asia but also in the Alps and the Andes. We show that the proposed method overcomes a majority of the aforementioned challenges to detect and delineate glacial lakes. The method performs efficiently irrespective of geographic, geologic, and climatic conditions of glacial lakes.Publisher PDFPeer reviewe

The presence and influence of glacier surging around the Geladandong ice caps, North East Tibetan Plateau

This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA20100300).Many glaciers and ice caps on the Tibetan Plateau have retreated and lost mass in recent years in response to temperature increases, providing clear evidence of the impact of climate change on the region. There is increasing evidence that many of the glaciers on the Tibetan Plateau have also shown periodically dynamic behaviour in the form of glacier surging and some even catastrophic collapse events. In this study, we examine the prevalence of glacier surging at the Geladandong ice caps, North East Tibetan Plateau, to better understand the role of surge events in the evolution of glacier mass loss budgets. Using glacier surface elevation change data over the period 1969–2018 and glacier surface velocity data from the ITS_LIVE dataset, we find that 19 outlet glaciers of the ice caps are of surge-type. Our multi-temporal measurements of glacier mass balance show that surge-type glacier mass budgets vary depending on the portion of the surge-cycle captured by geodetic data. At the regional level, pre- and post-surge glacier mass loss variability does not bias regional mass budget estimates, but enhanced, or suppressed, mass loss estimates are likely when small groups of glaciers are examined. Our results emphasise the importance of accurate surge-type glacier inventories and the need to maximise geodetic data coverage over glacierised regions known to contain surge-type glaciers.Publisher PDFPeer reviewe

Using ASTER and SRTM DEMs for studying geomorphology and glaciation in high mountain areas

For selected peaks in high mountains of diverse climatic regions (Andes, Hindu Kush, Tien Shan) digital elevation models (DEMs) have been generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data using PCI Geomatica 8.1/8.2 software. Artifacts in the ASTER DEM were eliminated using data from the Space Shuttle Radar Topography Mapping mission (SRTM). For two of the four case studies, accuracy was evaluated by comparison the ASTER/SRTM DEM with DEMs derived from contour maps. Whereas the SRTM DEM shows correct elevations in all altitudes, elevations in the ASTER DEM are slightly to low in higher altitudes and south-exposed aspects. Geomorphic analyses were undertaken using the software ArcInfo, ArcView and SAGA. Cluster analyses including tangetial, vertical curvature and slope combined with spectral information helped identifying debris-covered glaciers and geomorphologic forms and processes. Results show that ASTER/SRTM DEMs are useful for an interpretation of the macro- and mesorelief. The DEM scale sets limits for the level in analysis detail. Whereas SRTM DEMs offer more precise elevations, ASTER DEMs offer more geomorphologic details

Heterogeneous glacier thinning patterns over the last 40 years in Langtang Himal

Himalayan glaciers are losing mass at rates similar to glaciers elsewhere, but heavily debris-covered glaciers are receding less than debris-free glaciers or even have stable fronts. There is a need for multi-temporal mass balance data to determine if glacier wastage of debris-covered glaciers is accelerating. Here, we present glacier volume and mass changes of seven glaciers (5 partially debris-covered, 2 debris-free) in the upper Langtang catchment in Nepal of 28 different periods between 1974 and 2015 based on 8 digital elevation models (DEMs) derived from high-resolution stereo satellite imagery. We show that glacier volume decreased during all periods between 2006 and 2015 (2006–2015: −0.60 ± 0.34 m a−1) and at higher rates than between 1974 and 2006 (−0.28 ± 0.42 m a−1). However, the behavior of glaciers in the study area was highly heterogeneous, and the presence of debris itself does not seem to be a good predictor for mass balance trends. Debris-covered tongues have highly non-linear thinning profiles, and we show that local accelerations in thinning correlate with complex thinning patterns characteristic of areas with a high concentration of supraglacial cliffs and lakes. At stagnating glacier area near the glacier front, on the other hand, thinning rates may even decrease over time. We conclude that trends of glacier mass loss rates in this part of the Himalaya cannot be generalized, neither for debris-covered nor for debris-free glaciers

Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry

Funding to support this research from the University of St Andrews and the School of Geography and Sustainable Development is gratefully acknowledged.Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer lake area change using a time-series radar backscatter intensity data such as the rapid expansion of Bechung Tsho. The PSI analysis showed that all the terminal moraines were stable except Drukchung Tsho. Its terminal moraine showed subsidence at the rate of –5.18 mm/yr. Sidewalls of lakes were also stable with the exception of Lugge Tsho at site 4. Due to the free availability of S-1 SAR data, the efficiency of processing a large amount of imagery within GEE, and the PSI technique, we were able to understand the outburst susceptibility of glacial lakes in the region at great detail. The regular acquisition of S-1 SAR data enables continuous monitoring of glacial lakes. A similar approach and concept can be transferred to any geographic region on earth that shares similar challenges in glacial lake monitoring.Publisher PDFPeer reviewe

A pipeline for automated processing of declassified Corona KH-4 (1962-1972) stereo imagery

This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA20100300) and the Swiss National Science Foundation (200021E 177652/1) within the framework of the DFG Research Unit GlobalCDA (FOR2630).The Corona KH-4 reconnaissance satellite missions acquired panoramic stereo imagery with high spatial resolution of 1.8–7.5m from 1962-1972. The potential of 800,000+ declassified Corona images has not been leveraged due to the complexities arising from handling of panoramic imaging geometry, film distortions and limited availability of the metadata required for georeferencing of the Corona imagery. This paper presents the Corona Stereo Pipeline (CoSP): A pipeline for processing of Corona KH-4 stereo panoramic imagery. CoSP utilizes deep learning based feature matcher SuperGlue to automatically match features point between Corona KH-4 images and recent satellite imagery to generate Ground Control Points (GCPs). To model the imaging geometry and the scanning motion of the panoramic KH-4 cameras, a rigorous camera model consisting of modified collinearity equations with time-dependent exterior orientation parameters is employed. Using the entire frame of the Corona image, bundle adjustment with well-distributed GCPs results in an average standard deviation or σ0 of less than two pixels. We evaluate fiducial marks on the Corona films and show that pre-processing the Corona images to compensate for film bending improves the 3D reconstruction accuracy. The distortion pattern of image residuals of GCPs and y-parallax in epipolar resampled images suggest that film distortions due to long-term storage likely cause systematic deviations of up to six pixels. Compared to the SRTM DEM, the Corona DEM computed using CoSP achieved a Normalized Median Absolute Deviation of elevation differences of ≈ 4m over an area of approx. 4000km2 after a tile-based fine coregistration of the DEMs. We further assess CoSP on complex scenes involving high relief and glacierized terrain and show that the resulting DEMs can be used to compute long-term glacier elevation changes over large areas.PostprintPeer reviewe

Structure-from-motion using historical aerial images to analyse changes in glacier surface elevation

This study was performed within and funded by the Swiss National Science Foundation project No. 200021 169775.The application of structure-from-motion (SfM) to generate digital terrain models (DTMs) derived from different image sources has strongly increased, the major reason for this being that processing is substantially easier with SfM than with conventional photogrammetry. To test the functionality in a demanding environment, we applied SfM and conventional photogrammetry to archival aerial images from Zmuttgletscher, a mountain glacier in Switzerland, for nine dates between 1946 and 2005 using the most popular software packages, and compared the results regarding bundle adjustment and final DTM quality. The results suggest that by using SfM it is possible to produce DTMs of similar quality as with conventional photogrammetry. Higher point cloud density and less noise allow a higher ground resolution of the final DTM, and the time effort from the user is 3-6 times smaller, while the controls of the commercial software packages Agisoft PhotoScan (Version 1.2; Agisoft, St. Petersburg, Russia) and Pix4Dmapper (Version 3.0; Pix4D, Lausanne, Switzerland) are limited in comparison to ERDAS photogrammetry. SfM performs less reliably when few images with little overlap are processed. Even though SfM facilitates the largely automated production of high quality DTMs, the user is not exempt from a thorough quality check, at best with reference data where available. The resulting DTM time series revealed an average change in surface elevation at the glacier tongue of -67.0 ± 5.3 m. The spatial pattern of changes over time reflects the influence of flow dynamics and the melt of clean ice and that under debris cover. With continued technological advances, we expect to see an increasing use of SfM in glaciology for a variety of purposes, also in processing archival aerial imagery.Publisher PDFPeer reviewe