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.