Inventory and activities of rockglaciers in Northern Tien Shan (Kazakhstan, Krygyzstan, China) using satellite SAR interferometry and optical imagery
1Department of Geography, University of Zurich, Zurich, Switzerland; 2Earth System Science Programme, Faculty of Science, The Chinese University of Hong Kong, Hong Kong, China; 3Gamma Remote Sensing, Gümligen, Switzerland; 4Chair of Cartography, Technische Universität München, Munich, Germany; 5Department of Geosciences, University of Oslo, Oslo, Norway
Rockglaciers are the best visual expression of mountain permafrost and are widespread in the Tien Shan. These ice-debris landforms can, in contrast to permafrost itself, be mapped and monitored directly using remotely sensed data. Previous studies showed that changes in rockglacier flow can be related to climate conditions. However, no consistent rock glacier inventory of the whole Tien Shan exists and information about rockglacier flow is rare. Most previous studies concentrated in a few valleys in the Ile Range of Northern Tien Shan (Kazakhstan).
We have systematically mapped active rock glaciers of Northern Tien Shan located in Kazakhstan, Kyrgyzstan and Xinjiang, China’s north-western-most province, based on differential SAR interferograms and the best available optical imagery from Google Earth or other sources. Different SAR interferograms from various sources, including ERS-1/2, ALOS-1/2 and Sentinel-1, were used to identify and manually map surface deformations at elevations where rockglaciers can occur. The optical imagery were subsequently applied to distinguish rockglaciers from other deformations, e.g. due to subsidence, landsliding or solifluction. The rockglaciers were finally classified according to their state of activity (surface velocity), origin of the debris and topographic parameters (e.g. aspect, slope).
We identified so far more than 700 objects with an extent of about 250 km² within an area of 4000 km². Most of the rockglaciers are moraine-derived and have a northern exposition. The altitude distribution varies significantly depending on the location. Work is ongoing to extend the study region, refine the inventory, classify the rock glaciers according to their activity, and investigate the changes in velocity and surface elevation of selected rockglaciers over time.
Mapping of (rock)glaciers and observation of glacier area and volume changes in High Mountain Asia using earth observation data
1Institute of Tibetan Plateau Research, Chinese Academy of Sciences; 2The Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences
Global warming caused significant changes in mountain glaciers. Observations showed on average clear glacier mass loss. However, recent studies revealed also regions with balanced mass budgets especially in parts of High Mountain Asia (HMA). These heterogeneous changes significantly influence the hydrology, i.e. regionally they alter the river run-off and cause the rise of endorheic lakes on the Tibetan Plateau and globally they affect the sea-level. Glaciers are a major contributor of sea-level rise and affect population that rely on fresh water from glaciers. Rock glaciers have so far only rarely been investigated in HMA but may also of hydrological importance.
The purpose of this sub-project within the more general cryosphere project is to generate an up to date glacier and a rock glacier inventory for selected benchmark regions located in different climatic settings in HMA. Glacier mapping will be based both on optical and radar imagery distributed by the Chinese and European Space programs and combine information about surface flow (as derived in the subproject 2), surface reflectance and backscatter. The generated outlines will be compared to existing ones of previous periods to detect changes in glacier area. As area changes can only indirectly related to climate and hydrology, we will also investigate glacier mass changes using digital elevation models from different time periods (DEM differencing) and altimetry data. Both data sources are complimentary in regard to their spatiotemporal coverage. We will apply ICESat and Cryosat-2 altimetry data to investigate the trends over the whole of HMA and apply DEM differencing in the benchmark regions using existing DEMs (e.g. SRTM, ASTER or TanDEM-X DEMs) or DEMs derived from stereo data. Field measurements and high resolution data will be employed to validate and calibrate the remote-sensing derived results.
The outcome of this project will be improved methodologies for glacier mapping and glacier change assessments and a better knowledge about rock glacier occurrence, the spatial and temporal variability of glacier area and mass changes in HMA, its influence on hydrology and its control by local and climatic forcing. This will be realised thanks to the large archive of satellite data available via Dragon, data available from other sources and thanks to the coordinated effort of the several institutions partnering in the project. The link to hydrology, local and climate forcing will be investigated within this subproject via data assimilation into mass balance models, interaction with the two other sub-projects under the umbrella of cryosphere, and via interaction with the hydrology consortium.
An Assessment of Cloud Detection Methods in High Altitude Snow and Glacial Environments With Sentinel-2
TU Delft, Netherlands, The
Glacier fluctuations are regarded one of the most significant indicators of climate change. The expansion and contraction of glaciers can be observed by outlining glacier boundaries or measuring snow lines with optical Earth observation satellites. New satellites, such as Sentinel-2A/B, provide high spatial resolution images and short revisit times that can be used to make ample measurements to accurately determine glacial variability. Likewise, ever increasing volumes of satellite data make automated boundary and snow line detection a desirable solution for researchers. Two regions of interest for boundary and snow line detection are the Himalaya and Tibetan Plateau. They are home to the world's highest mountains and some of the world's largest non-polar glaciers. These regions also provided valuable water resources to over a billion people in nearby countries, and therefore are not just ecologically, but also economically important. Clouds, however, present a challenge to obtaining useful image data. Mountainous regions are often surrounded or covered by clouds. Clouds can be a menacing phenomenon in remote sensing because they greatly attenuate and reflect short wavelengths used by optical Earth observation satellites. Currently, many techniques exist to automatically detect clouds and classify them. However, they are not perfect. Many techniques have encountered difficulties in cases where snowy and icy landscapes share similar properties with clouds. The Himalaya topographic relief also adds to the challenge. Steep slopes and topographic shadows have a profound effect on surface reflectances and can lead to misclassifications. To address these issues, this study presents an assessment of multiple cloud detection techniques. For initial analysis, 19 Sentinel-2A images were acquired at various times between 12/07/15 and 31/12/16. The images are centered on the Bara Shigri Glacier in Himachal Pradesh, India, a large 10 km long glacier which drains into the Chenab River (an Indus River tributary). The images vary from cloudy to clear (cloud-free), but also have variations in snow cover and cloud shadows. The set was reduced to 6 images that were selected for further classification analysis, as partly shown in Figure 1. Figure 1 shows, starting from the top-left, a natural color image for reference, a manually created cloud mask for validation, and well-known spectral analysis methods: Fmask and maximum likelihood classification. Goal of the study is to first evaluate the performance of existing methods in the automatic identification of pixels contaminated by clouds, and secondly, if necessary, design an improved method, for example, by incorporating the high temporal revisit time of the Sentinel-2 imagery. In doing so, this research seeks to better understand cloud cover over mountainous regions and distinguish them from snow cover and glaciers. It should be noted that cloud detection is a valuable pre-processing step that, when successful, will increase data availability to glacier researchers. Thus, the final goal is to incorporate the cloud-free pixel identification in automated workflows for snow cover studies.
Glacier Motion Monitoring with Sentinel-1A feature-tracking, Kongur Mountain, Pamirs
1Hunan University of Science and Tenchnology, China, People's Republic of; 2State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineer Research Institute; 3Institute for Cartography, Technische Universität Dresden
Catastrophic event - fast moving glacier destroying pastures and killing livestock near the glacier tongue in Kongur Mountains, Xinjiang Uygur Autonomous Region, was reported on May 14th, 2015. In this letter, Sentinel-1 SAR and ALOS/PALSAR data feature-tracking was employed to obtain the glacier surface velocities. Time series of the estimated glacier surface velocities suggested that the left tributary had been a fast moving flow for eight years at least. Analysis of the obtained glacier surface velocities Variation made the surge occurrence confirmed, and from Mar 24th, 2015 to May 11th, 2015, the left tributary has pushed the trunk gradually detected by the analysis of glacier flow vector. Surface velocities of three stages, prior to the surging, during surging and post surging were mapped and analyzed. This research suggested that monitoring glacier surface velocities could be regarded as an effective way for glacier catastrophic warning.
Recent accelerating mass loss of southeast Tibetan glaciers and the relationship with changes in macroscale atmospheric circulations
Chinese Academy of Sciences, China, People's Republic of
The mass balance history (1980–2010) of a monsoon-dominated glacier in the southeast Tibetan Plateau is reconstructed using an energy balance model and later interpreted with regard to macroscale atmospheric variables. The results show that this glacier is characterized by significant interannual mass fluctuations over the past three decades, with a remarkably high mass loss during the recent period of 2003–2010. Analysis of the relationships between glacier mass balance and climatic variables shows that interannual temperature variability in the monsoonal season (June–September) is a primary driver of its mass balance fluctuations, but monsoonal precipitation tends to play an accentuated role for driving the observed glacier mass changes due to their covariation (concurrence of warm/dry and cold/wet climates) in the monsoon-influenced southeast Tibetan Plateau. Analysis of the atmospheric circulation pattern reveals that the predominance of anticyclonic/cyclonic circulations prevailing in the southeastern/northern Tibetan Plateau during 2003–2010 contributes to increased air temperature and decreased precipitation in the southeast Tibetan Plateau. Regionally contrasting atmospheric circulations explain the distinct mass changes between in the monsoon-influenced southeast Tibetan Plateau and in the north Tibetan Plateau/Tien Shan Mountains during 2003–2010. The macroscale climate change seems to be linked with the Europe-Asia teleconnection.
Lake volume and groundwater storage variations in Tibetan Plateau’s endorheic basin
1Chinese Academy of Sciences, China, People's Republic of; 2Department of Geography, University of Zurich
The Tibetan Plateau (TP), the highest and largest plateau in the world, with complex and competing cryospheric-hydrologic-geodynamic processes, is particularly sensitive to anthropogenic warming. The quantitative water mass budget in the TP is poorly known. Here we examine annual changes in lake area, level, and volume during 1970s −2015. We find that a complex pattern of lake volume change during 1970s−2015: a slight decrease of –2.78 Gt yr-1 during 1970s−1995, followed by a rapid increase of 12.53 Gt yr-1 during 1996−2010, and then a recent deceleration (1.46 Gt yr-1) during 2011−2015. We then estimated the recent water mass budget for the Inner TP, 2003−2009, including changes in terrestrial water storage (TWS), lake volume, glacier mass, snow water equivalent (SWE), soil moisture, and permafrost. The dominant components of water mass budget, namely changes in lake volume (7.72 ± 0.63 Gt yr-1) and groundwater storage (5.01 ± 1.59 Gt yr-1), increased at similar rates. We find that increased net precipitation contributes the majority of water supply (74%) for the lake volume increase, followed by glacier mass loss (13%), and ground ice melt due to permafrost degradation (12%). Other term such as SWE (1%) make a relatively small contribution. These results suggest that the hydrologic cycle in the TP has intensified remarkably during recent decades.