Frank Rau

Remote sensing and GIS technology in the Global Land Ice Measurements from Space (GLIMS) Project

Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the worlds glaciers, analyze them for glacier extent and changes, and to assess these change data in terms of forcings. The consortium is organized into a system of Regional Centers, each of which is responsible for glaciers in their region of expertise. Specialized needs for mapping glaciers in a distributed analysis environment require considerable work developing software tools: terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; change detection and analysis; visualization of images and derived data; interpretation and archival of derived data; and analysis to ensure consistency of results from different Regional Centers. A global glacier database has been designed and implemented at the National Snow and Ice Data Center (Boulder, CO); parameters have been expanded from those of the World Glacier Inventory (WGI), and the database has been structured to be compatible with (and to incorporate) WGI data. The project as a whole was originated, and has been coordinated by, the US Geological Survey (Flagstaff, AZ), which has also led the development of an interactive tool for automated analysis and manual editing of glacier images and derived data (GLIMSView). This article addresses remote sensing and Geographic Information Science techniques developed within the framework of GLIMS in order to fulfill the goals of this distributed project. Sample applications illustrating the developed techniques are also shown.

New eyes in the sky measure glaciers and ice sheets

The mapping and measurement of glaciers and their changes are useful in predicting sea-level and regional water supply, studying hazards and climate change [Haeberli et al., 1998],and in the hydropower industry Existing inventories cover only about 67,000 of the worlds estimated 160,000 glaciers and are based on data collected over 50 years or more [e.g.,Haeberli et al., 1998]. The data available have proven that small ice bodies are disappearing at an accelerating rate and that the Antarctic ice sheet and its fringing ice shelves are undergoing unexpected, rapid change. According to many glaciologists, much larger fluctuations in land ice—with vast implications for society—are possible in the coming decades and centuries due to natural and anthropogenic climate change [Oppenheimer, 1998].

Variations of glacier frontal positions on the northern Antarctic Peninsula

Abstract Changes in the ice fronts on the Antarctic Peninsula north of 70˚ S are currently being investigated through a comprehensive analysis of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat Thematic Mapper (TM) data as part of the international research initiative ‘Global land Ice Measurements from Space’ (GLIMS). Regional case studies are presented that cover a variety of glacial systems distributed over the northern Antarctic Peninsula and provide data on glacier front variations during the period 1986–2002. The results confirm a general trend of regional glacier front recession, but a range of different glacier variations are observed throughout the study area. Areas of predominant retreat are located in the northeastern and southwestern sectors, while stationary ice fronts characterize glacial behaviour on the northwestern coast of the peninsula. In addition, a significant increase in glacier recession is identified on James Ross Island, where retreat rates doubled during the period 1988–2001 compared to the previous investigation period, 1975–88. These observations are interpreted as being direct consequences of the rapidly changing climate in the region, which differentially affects the local accumulation and ablation patterns of the glacial systems.

Development of radar glacier zones on the King George Island ice cap, Antarctica, during austral summer 1996/97 as observed in ERS-2 SAR data

Abstract Based on a time series of European remote-sensing satellite (ERS-2) synthetic-aperture radar (SAR) images from 1996/97, ablation on the King George Island (Antarctica) ice cap is documented. Snowmelt patterns were monitored by mapping the dynamic evolution of radar glacier zones and their boundaries. On the ice cap, all major radar glacier zones except the dry-snow radar zone were identified during the observed period While winter was characterized by a frozen-percolation radar zone, the ablation season was characterized by wet-snow and bare-ice radar zones. A striking bright backscatter signature indicated the presence of a highly reflective zone in the lower parts of the wet-snow zone. It was attributed to a phase 2 melt (P2) radar zone, which is characterized by a metamorphosed and roughened surface of a melting snow cover. Due to the absence of simultaneously acquired ground-truth information, concurrent meteorological data proved to be essential for interpreting the SAR images. Although the maximum elevation of the ice cap does not exceed 680 ma.s.L, ablation patterns obviously reflect altitudinal control. Melt onset up to 530 m a.s.l. was initiated by an advection event at the end of October 1996. A wet snowpack on the entire ice cap corresponds with a prolonged period of high temperatures in January 1997. However, the highest parts of the ice cap were affected by occasional melt-freeze cycles. The transient snowline at the end of February was determined as being at 250 m a i l. This late-summer snowline was regarded as an approximation of the equilibrium-line altitude for the 1996/97 ablation season.

The regional distribution of the dry-snow zone on the Antarctic Peninsula north of 70˚ S

Abstract In order to estimate the contribution of the Antarctic Peninsula to global sea-level rise as a result of the observed warming in this region, the spatial extent of snow-melt-producing areas needs to be quantified. By using the dry-snow line derived from synthetic aperture radar (SAR) imagery as the uppermost limit of frequent or occasional surface melt, an estimation of the spatial extent of areas with non-zero ablation rates is facilitated. Three calibrated RADARSAT ScanSAR mosaics covering the northern Antarctic Peninsula were analyzed applying a threshold of –14 dB to identify the dry-snow line. The area of the dry-snow radar zone was determined to be 23300±2000 km2.Areas affected frequently or occasionally by snowmelt cover 85 000±9000 km2. In addition, the dry-snow line as derived from multi-temporal ERS-1/-2 imagery serves as an indicator of climate variability in the uppermost areas of polar glaciers and ice sheets. The upward shift of the dry-snow line between 1992 and 1998 on the eastern side of the Antarctic Peninsula at 68˚ S is interpreted as a direct response to the increasing number of high-temperature events during the 1991–2000 decade.

Remote Sensing of Snow Cover

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

A time series of SAR data for monitoring changes in boundaries of glacier zones on the Antarctic Peninsula

Abstract Drastic changes have been detected in glacial systems of the Antarctic Peninsula in the last few decades and are well documented in numerous scientific publications. However, the spatial and temporal distribution of glacier changes on the Antarctic Peninsula remains largely restricted to ice fronts. To expand the current monitoring of a few glaciers, unevenly distributed along the peninsula, to a representative set, we developed a method to simplify the detection of boundaries between glacier zones using satellite SAR data. The evolution of glacier zones is greatly influenced by local and regional climatic and meteorological settings. Their variations in response to changes in energy or mass balance are considered as good indicators of climatic changes. In this paper, we describe the results of knowledge-based image analysis algorithms on test areas located at Trinity Peninsula and near Marguerite Bay. In general, the two analyzed areas show different patterns of glacier zone development. The bare-ice zone occurs mainly on glaciers located on the eastern side of Trinity Peninsula. Its upper boundary shows a good correlation with the mean summer air temperature. Finally, the position of the dry-snow line shows different spatial patterns of change in both study areas.

Ground ice in permafrost on Seymour (Marambio) and Vega Islands, Antarctic Peninsula

Abstract Seymour (Marambio) and Vega Islands occur within the continuous permafrost zone of the northeastern Antarctic Peninsula. Results are presented of investigations on the occurrence, distribution, morphology and genesis of ground ice, a key aspect of permafrost research in this region. According to its morphology, ice content, buried ice type and possible upper Quaternary conditions, permafrost is divided into two cryoformations: epigenetic and syngenetic. Based on field and remote-sensing data, 76.6 km2 of Seymour Island and 81.0 km2 of Vega Island are characterized by permafrost, with estimated ice contents of 0.06 and 1.41 km3, respectively. Different genetic ground-ice types are distinguished and a regional morphogenetic classification of ground ice is proposed.

A GIS-Based Glacier Inventory for the Antarctic Peninsula and the South Shetland Islands-A First Case Study on King George Island

The aim of the international project “Global Land Ice Measurements from Space (GLIMS)” headed by the US Geological Survey is to establish a world wide glacier inventory based on satellite imagery. This data set will form a first digital baseline study for future glacier monitoring. The presented GIS-based glacier inventory for King George Island is a case study for the area of the Antarctic Peninsula. In the database of the glacier inventory topographic information, specific glaciological parameters as well as metadata will be included. The topographic data consists of drainage basin limits, basin areas, altitudinal ranges, perimeters and mean lengths. Glaciological data sets should comprise information on glacier retreat in different periods, glacier velocities, ice thickness and bedrock topography as well as derived parameters. Modelled and measured mass balance parameters could be included as additional data layers. In particular, these metadata records must comprise background information on data accuracy and data sources and should be compatible with a future data model for the King George Island GIS (KGIS). Three examples illustrate that the GLIMS database will not only contain information valuable for glaciological applications, but also other environmental studies on the island will benefit from this standardised remote sensing data sets. Therefore, a very close link between the data models of KGIS and GLIMS has to be established to enable these synergisms. Finally, better access to historic aerial photography would enable a continuous record of glacier retreat from the beginning of the 1950s onward.