Solveig Havstad Winsvold

On the accuracy of glacier outlines derived from remote-sensing data

Abstract Deriving glacier outlines from satellite data has become increasingly popular in the past decade. In particular when glacier outlines are used as a base for change assessment, it is important to know how accurate they are. Calculating the accuracy correctly is challenging, as appropriate reference data (e.g. from higher-resolution sensors) are seldom available. Moreover, after the required manual correction of the raw outlines (e.g. for debris cover), such a comparison would only reveal the accuracy of the analyst rather than of the algorithm applied. Here we compare outlines for clean and debris-covered glaciers, as derived from single and multiple digitizing by different or the same analysts on very high- (1 m) and medium-resolution (30 m) remote-sensing data, against each other and to glacier outlines derived from automated classification of Landsat Thematic Mapper data. Results show a high variability in the interpretation of debris-covered glacier parts, largely independent of the spatial resolution (area differences were up to 30%), and an overall good agreement for clean ice with sufficient contrast to the surrounding terrain (differences ∼5%). The differences of the automatically derived outlines from a reference value are as small as the standard deviation of the manual digitizations from several analysts. Based on these results, we conclude that automated mapping of clean ice is preferable to manual digitization and recommend using the latter method only for required corrections of incorrectly mapped glacier parts (e.g. debris cover, shadow).

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

With its temporal resolution of 10 days (five days with two satellites, and significantly more at high latitudes), its swath width of 290 km, and its 10 m and 20 m spatial resolution bands from the visible to the shortwave infrared, the European Sentinel-2 satellites have significant potential for glacier remote sensing, in particular mapping of glacier outlines and facies, and velocity measurements. Testing Level 1C commissioning and ramp-up phase data for initial sensor quality experiences, we find a high radiometric performance, but with slight striping effects under certain conditions. Through co-registration of repeat Sentinal-2 data we also find lateral offset patterns and noise on the order of a few metres. Neither of these issues will complicate most typical glaciological applications. Absolute geo-location of the data investigated was on the order of one pixel at the time of writing. The most severe geometric problem stems from vertical errors of the DEM used for ortho-rectifying Sentinel-2 data. These errors propagate into locally varying lateral offsets in the images, up to several pixels with respect to other georeferenced data, or between Sentinel-2 data from different orbits. Finally, we characterize the potential and limitations of tracking glacier flow from repeat Sentinel-2 data using a set of typical glaciers in different environments: Aletsch Glacier, Swiss Alps; Fox Glacier, New Zealand; Jakobshavn Isbree, Greenland; Antarctic Peninsula at the Larsen C ice shelf.

Glacier Remote Sensing Using Sentinel-2. Part II: Mapping Glacier Extents and Surface Facies, and Comparison to Landsat 8

Mapping of glacier extents from automated classification of optical satellite images has become a major application of the freely available images from Landsat. A widely applied method is based on segmented ratio images from a red and shortwave infrared band. With the now available data from Sentinel-2 (S2) and Landsat 8 (L8) there is high potential to further extend the existing time series (starting with Landsat 4/5 in 1982) and to considerably improve over previous capabilities, thanks to increased spatial resolution and dynamic range, a wider swath width and more frequent coverage. Here, we test and compare a variety of previously used methods to map glacier extents from S2 and L8, and investigate the mapping of snow facies with S2 using top of atmosphere reflectance. Our results confirm that the band ratio method works well with S2 and L8. The 15 m panchromatic band of L8 can be used instead of the red band, resulting in glacier extents similar to S2 (0.7% larger for 155 glaciers). On the other hand, extents derived from the 30 m bands are 4%–5% larger, indicating a more generous interpretation of mixed pixels. Mapping of snow cover with S2 provided accurate results, but the required topographic correction would benefit from a better orthorectification with a more precise DEM than currently used.

A new glacier inventory for the Jostedalsbreen region, Norway, from Landsat TM scenes of 2006 and changes since 1966

Abstract Pronounced changes in glacier mass and length were observed for the monitored glaciers in the Jostedalsbreen region, Norway, since the last glacier inventories were compiled in the 1960s and 1980s. However, the current overall extent of the glaciers in the region is not well known. To obtain this information, we have compiled a new inventory from two mosaicked Landsat Thematic Mapper (TM) scenes acquired in 2006 that have excellent snow conditions for glacier mapping, the first suitable scenes for this purpose after 22 years of imaging with TM. Drainage divides and topographic inventory parameters were derived from a 25 m national digital elevation model for 1450 glaciers. By digitizing glacier outlines from 1 : 50 000 scale topographic maps of 1966, we calculated changes in glacier area for ~300 glaciers. Cumulative length changes for the 1997–2006 period were derived from an additional TM scene and compared with field measurements for nine glaciers. Overall, we find a 9% area loss since 1966, with a clear dependence on glacier size; however, seasonal snow in 1966 in some regions made area determination challenging. The satellite-derived length changes confirmed the observed high spatial variability and were in good agreement with field data (±1 pixel), apart from glacier tongues in cast shadow. The new inventory will be freely available from the Global Land Ice Measurements from Space (GLIMS) glacier database.

Regional Glacier Mapping Using Optical Satellite Data Time Series

The first of two Sentinel-2 satellites, launched mid2015, has similar characteristics as the Landsat TM/ETM + /OLI satellites. Together, these satellites will produce a tremendous quantity of optical images worldwide for glacier mapping, with increasing temporal coverage toward the more glacierized higher latitudes due to convergence of near-polar orbits. To exploit the potential of such near-future dense time series, methods for mapping glaciers from space should be revisited. Currently, snow and ice are typically classified from an optical satellite image using a multispectral band ratio. For each scene, mapping conditions will vary (e.g., snow, ice, and clouds) and not be equally optimal over the entire scene. The increasing amount of images makes it difficult to manually select the best glacier mapping scene as is the current practice. This work is based on the above robust image ratio method for exploiting the dense temporal image coverage. Four application scenarios using time series of Landsat type data for glacier mapping are presented. First, we synthesize an optimal band ratio image from a stack of images within one season to compensate for regional differences. The second application scenario introduces robust methods to improve automatic glacier mapping by exploiting the seasonal variation in spectral properties of snow. Third, we explore the spatio-temporal variation of glacier surface types. Finally, we show how the synthesized band ratio images from the first application scenario can be used for automatic glacier change detection. In summary, we explore automatic algorithms for glacier mapping applications that exploit the temporal signatures in the satellite data time series.

Regional glacier mapping from time-series of Landsat type data

The Sentinel-2 satellite launch in mid-2015 has similar characteristics as the Landsat TM/ETM+/OLI satellites. Together, these satellites will in the future produce a tremendous quantity of optical images worldwide, with increasing temporal coverage towards higher latitudes due to their polar orbits. Due to this large amount of images, it will be increasingly difficult to manually choose the best glacier mapping scenes as currently done for glacier mapping methods. Often it is also not optimal to use only one scene due to regionally varying mapping conditions. To fully exploit the volume of multi-temporal images, methods for mapping glaciers should be revisited. To this end, we aim to create robust, automatic algorithms for glacier mapping applications, exploiting the multi-temporal signatures in the satellite data.