The high-resolution imagery recorded by systems such as the multi-spectral scanners (MSSs) of the Landsat satellites has revolutionized the study of all types of surface in the polar regions. Visible and near-infra-red imagery has found a wide range of glaciological uses. There is, however, a lack of comparability within and between MSS data which may be a contributary factor to some current problems in interpretation of remotely sensed glaciological data.

With the expected continuity of MSS coverage for the forseeable future, it is highly desirable to extend use of the data beyond the basic mapping and feature identification which has made it such a valuable resource. One of the most obvious developments is to investigate characteristics of the reflecting surfaces and to achieve absolute identification of snow and ice surfaces. Although conversion of digital MSS grey tones to radiances enables direct comparison with other sources, automatic identification requires detailed and extensive knowledge of the spectral and reflecting characteristics of surfaces which are to be monitored. This is often best achieved through ground-based observation.

In order to provide a base line against which corrected radiances from Landsat MSS data can be compared, a spectrally gated photometer has been used to measure albedo at MSS wave bands in a wide range of conditions. The surfaces monitored in several parts of Norway include sea ice, lake ice, snow, firn and glacier ice, permafrost, and reference surfaces. A range of supporting measurements (including grain-size, surface irregularity, density, level, and free-water content) allows accurate characterization of each surface. This enables identification of spectral-response patterns for each surface category and hence the classification of their reflectances as recorded by the MSS. Examples are given of the application of such classifications to imagery of the polar regions.

Finland has such a climate that all its harbours in the Baltic Sea are frozen every winter. Ice may sometimes be more than 1 m thick, as it was in the Bay of Bothnia, the northernmost basin of the Baltic Sea, during the winter of 1985.

The Finnish Institute of Marine Research has used the imagery of the Tiros-N series of satellites successfully in sea-ice mapping for some years. In the Institute daily ice charts have been prepared and sent by facsimile to icebreakers in the Baltic Sea. In 1985, an experiment was conducted to transmit the same imagery to an icebreaker operating in the Bay of Bothnia. Existing telecommunication networks were used. The image data transmitted by NOAA-6 and NOAA-9 satellites were received at Tromsø Telemetry Station in Norway and then transmitted to Espoo in Finland. The data processing consisted of geometric correction, edge enhancement, and drawing the coastline with location symbols. The most interesting area was extracted and transmitted by NMT mobile telephone to the icebreaker.

The almost real-time image transmission turned out to be useful from the point of view of icebreaker operation. The images could be used to identify cracks and narrow leads in the ice. Such very detailed information cannot be included in routine ice charts. The icebreaker can use this information for giving instructions to other ships to find easier routes. This reduces the need for icebreaker assistance. The images can also help the icebreaker to avoid wide heavily ridged areas.

This experiment was at low cost and can be technically developed further. It showed that this kind of assistance for icebreakers is economically profitable for winter navigation.

A snow survey in north-west China has been carried out using meteorological satellite NOAA-9 imagery. A two-step geometric correction method is presented. The first step involves a large-scale geometric correction, and the second step concentrates on a small area of interest, using the control-point correction method. A high precision of geometric correction can beachieved by using this method. The snow-covered area of the Qilian Mountains basin is calculated.

The US Geological Survey is conducting a program to prepare digitally enhanced Multispectral Scanner (MSS) Landsat images of Antarctica. The goal is to furnish accurate planimetric, false-colour composite image maps in Lambert conformal conic projection for the following purposes: (1) to locate and delineate blue-ice areas for the collection of meteorites; (2) to produce special purpose maps showing selected features; (3) to provide synoptic views that aid in the detection and interpretation of glaciological features associated with the inland ice sheet, outlet glaciers, ice streams, and ice shelves; (4) to monitor changes in coastline and glacial features; (5) to enable the superposition and correlation of different types of digital cartographic data; and (6) to furnish spectral and (or) structural information in areas of limited bedrock outcrop to aid in regional geologic interpretation. Only the first four of these objectives are addressed here.

About 170 Landsat computer-compatible tapes covering Victoria Land, the coastline of West Antarctica, the Antarctic Peninsula, and other selected areas were assembled into false-color, multi-spectral, digital composites of band 4 (0.5 to 0.6 μm, green), band 5 (0.6 to 0.7 μm, red) and band 7 (0.8 to 1.1 μm, near infra-red). The tapes were subjected to routine image-processing procedures, such as noise removal and radiometric and geometric corrections. Further processing included haze removal and enhancement by linear stretching of individual MSS bands based on inspection of gray-value (digital-number) histograms. Saturation of snow-covered scenes in bands 4, 5, and 6 is a severe problem in Landsat MSS images of Antarctica and makes many images unsuitable for multi-spectral work. We have developed special techniques to restore the saturated snow-and-ice information in these bands to overcome this problem.

The Landsat image maps have different formats, depending on their planned applications. An example of a planimetric image map is the one of the McMurdo Sound area; it is based on excellent ground control and processed at full spatial resolution. It comprises five complete and three partial 1 : 250 000 scale topographic quadrangles. One of these is the Convoy Range quadrangle which includes the Allan Hills meteorite-collection site. Blue-ice areas show exceptionally well on this quadrangle, and new information on blue-ice locations and delineations was obtained from it.

Thematic maps prepared for the Byrd Glacier area selectively show only rock or ice areas, thus depicting the location of desired features. Synoptic-view maps and mosaics provide information on flow lines associated with ice streams, the location of ice rises, ice rumples, and other possible grounded areas, and the location and extent of buried mountain ranges. Image maps which cover the same area at different times do show changes: a 10-year interval between Landsat images obtained in the Byrd Glacier area shows that crevasses had opened and rifts had drifted within the floating part of the glacier; measurements of the changed positions have yielded average velocities for glacier and ice-shelf movements in that area. The ease with which the dynamics of the coastline can be monitored on Landsat images is particularly useful, because such changes have implications for variations in world climate.

The increasing demand for water, coupled with the construction of multi-purpose reservoirs to control and regulate snow-melt run-off, requires accurate strearm-flow forecast. For making an accurate prediction of spring run-off, information on the amount of snow accumulation in winter is necessary; this may be achieved through remote-sensing techniques in any inaccessible region.

This paper outlines the snow-melt run-off study carried out in a part of Beas basin, India, using Landsat imagery for the years 1973, 1975, 1976, and 1977. The Beas basin lies between long. 76°56' to 77°52'E. and lat. 31°30' to 32°25'N., covering an area about 4900 km2, of which 1400 km2 is permanently covered by snow. The gradual melting of snow accumulated over the catchment area during the winter months is responsible for the perennial character of the Beas River.

Photohydrological investigation of the part of the Beas basin up-stream of Barji was carried out and a study was made for the estimation of the snow-melt run-off during the pre-monsoon period in the sub-basin up-stream of Manali. For this purpose, the sub-basin has been divided into permanent and temporary snow-covered zones. The degree-day method and the melt due to rainfall on snow have been used to estimate snow-melt run-off. The routing of snow-melt, after accounting for losses as well as the run-off from the excess rainfall from the permanent and temporary snow-covered areas, has also been done taking the recession coefficient K as 0.90, and the excess rain from the non-snow-covered areas has been assumed to contribute directly to the run-off for that day. Run-off coefficients of 0.595 for rainfall on the snow-covered areas and 0.278 for rainfall on the non-snow-covered areas have been determined.

Reference can be made to similar work in India and Pakistan to establish the relationship between the snow cover and the cumulative discharges for the months of March, April, and May of the years 1973, 1975, 1976, and 1977, and an exponential trend was observed with the help of Landsat Imagery. Furthermore, the snow-covered areas as determined from bands 5 and 7 of the Landsat imagery, for the same day, showed a linear trend.

The analysis of the results shows that remote-sensing data used in conjunction with conventional methods are likely to improve the accuracy of the snow-melt forecasts in remote areas like the Himalayan catchments.

Lützowholmbukta, East Antarctica, is covered by fast ice except during a short period in April and May, but occasionally the ice cover breaks up and floats out of the bay.

The fast ice was observed every day using NOAA-7, 8 infra-red imagery. The satellite signal was received at Syowa Station, located on Ongul Island. In addition, aerial photographs and video pictures were taken using aircraft every fortnight.

In 1983, before the break-up of the fast ice in April, a distinctive increase of the infra-red radiance (NOAA AVHRR) was observed, even though the aerial observation showed no change. The increase of the radiance was estimated to be 5°C. It was in this area, where the higher infra-red signal was observed, where the fast ice broke up. In December, in the central part of the northern area of the fast ice, the hummock-ice zone formed in a triangular shape. Before the hummock-ice zone floated out, observation of the infra-red radiance showed that the temperature of the ice had decreased by 3°C.

Kozel’skiy glacier is located in lat. 53.1°N., 50 km from the Pacific Ocean, and has a southern exposure. It flows from the saddle between Avachinskiy and Kozel’skiy volcanoes. Its highest point is at an altitude of 1850 m a.s.l. The glacier tongue descends to an altitude of 900 m a.s.l. At present, this is the best-studied glacier in Kamchatka.

In May and June 1981, for the purpose of organizing routine monitoring of the movement of Kozel’skiy glacier, systematic geodimeter measurements were made at the “Mishennaya” Observatory. A model 8 geodimeter (AGA, Sweden) was used for measuring straight-line distances. The source of radiation was a He–Ne laser beam with a power of 5 MW and a wavelength of 0.6328 m. In Kamchatka this geodimeter can measure distances of 60 km and in some cases 90 km. If a special (diurnal) procedure of measurements is used, one can attain an accuracy of 1 × 10−6 of the length of the line D. Sixteen prism-angle reflectors were installed on the glacier.

The entire firn area of the glacier could be seen well from the top of Mount Mishennaya. Two profiles consisting of six points on the glacier surface were constructed. A bench mark on the ancient lava flow of Kozel’skiy volcano was taken as static in elevation and was used to control the accuracy of the measurements. The points on the glacier were established by 2 m poles with a diameter of 1.5 cm. Reflectors were installed on tripods and were centred with the help of an optical plumb bob. The points for measurement of the movement velocity were located at a distance of more than 26 km from the instrument. Studies were carried out during periods of stationary images (without inversions), generally early in the morning and late in the evening.

Two-sided trigonometrical levelling was carried out simultaneously. Zenith distances were measured four times by a Teo-010A theodolite. Meteorological conditions were determined at 1.5–2 h near the reflectors and at the observatory during the whole cycle of measurements. The processing of the results of distance measurements was done according to the procedure published in Lobachev. The elevation of points over the observatory was determined from the measured zenith distances.

The error in distance measurements was ± 0.04 m and in elevation ± 0.8 m (an increase in accuracy up to 0.2 m is possible). The displacement of points of velocity changed from 0.3 to 2.37 m over the whole period of observation. This corresponds to a glacier velocity from 1 to 6 m/d. Thus, a cycle of geodimeter measurements may be carried out once a week, providing an accuracy of distance measurements of ± 4 cm. Routine measurements of the velocities of glacier movement, using geodimeters, may be organized subject to reliable long-term attachment of reflectors to the surface of the glacier.

Experience of the studies made indicated good opportunities for application of a stationary geodimeter to the investigation of glacier movement. The data obtained agree with previous measurements made by the usual geodetic methods.

Satellite imagery has substantially improved the quality of sea-Ice observation over the last decades. Therefore, for a 25-year period, a statistical study based on the monthly Arctic sea-ice data and the monthly mean 700 mbar maps of the Northern Hemisphere was carried out to establish the relationships between sea-ice conditions and the general circulation of the atmosphere. It was found that sea-ice conditions have two opposing effects on the zonal circulation intensity, depending on the season. Heavier than normal ice in winter causes stronger than normal zonal circulation in the subsequent months, whereas heavier than normal ice in the summer–fall causes weaker zonal circulation in the subsequent months. Analyzing the two sectors, the Atlantic and Pacific ones separately, a negative correlation was found, which means a heavy ice year in the Atlantic Ocean is normally associated with a light one in the Pacific Ocean and vice versa.

Ground surveys of the ice sheet in Wilkes Land, Antarctica, have been made on oversnow traverses operating out of Casey. Data collected include surface elevation, accumulation rate, snow temperature, and physical characteristics of the snow cover. By the nature of the surveys, the data are mostly restricted to line profiles. In some regions, aerial surveys of surface topography have been made over a grid network.

Satellite imagery and remote sensing are two means of extrapolating the results from measurements along lines to an areal presentation. They are also the only source of data over large areas of the continent. Landsat images in the visible and near infra-red wavelengths clearly depict many of the large- and small scale features of the surface. The intensity of the reflected radiation varies with the aspect and magnitude of the surface slope to reveal the surface topography. The multi-channel nature of the Landsat data is exploited to distinguish between different surface types through their different spectral signatures, e.g. bare ice, glaze, snow, etc. Additional information on surface type can be gained at a coarser scale from other satellite-borne sensors such as ESMR, SMMR, etc. Textural enhancement of the Landsat images reveals the surface micro-relief.

Features in the enhanced images are compared to ground-truth data from the traverse surveys to produce a classification of surface types across the images and to determine the magnitude of the surface topography and micro-relief observed. The images can then be used to monitor changes over time.