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

Abstract

Abstract: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.

Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples

“…As an example, Figure 1c shows the atmospherically-corrected B8a BoA reflectance (at 865 nm). Sen2Cor includes a scene classification module (example in Figure 1b) to map no data or defective pixels (pixel value = 0-1), four different cloud clover class probabilities (7)(8)(9)(10), and six different classes including shadows (2), cloud shadows (3), vegetation (4), soils and deserts (5), water (6), and snow (11).…”

“…Together with its twin satellite (to be launched beginning 2017), Sentinel-2 will cover the entire Earth every five days. The excellent performance characteristics of Sentinel-2 were shown already for different applications, such as crop and forest classification [2], sub-pixel landscape feature detection [3], mapping of built-up areas [4,5], as well as monitoring of glacier and water bodies [6,7]. Currently, users can find data at the ESA's Scientific Data Hub (SDH), or using alternative platforms such as Amazon Web Service (AWS) or Google's Earth Engine.…”

Ready-to-Use Methods for the Detection of Clouds, Cirrus, Snow, Shadow, Water and Clear Sky Pixels in Sentinel-2 MSI Images

“…The retrieval of surface reflection becomes impossible for optically thick clouds and pixels affected by cirrus and shadows must be treated as individual cases for a physically correct retrieval. Many applications benefit if a detection of snow and water is additionally performed (e.g., see [5,6]). In that respect, such a classification is an essential pre-processing step before higher-level algorithms can be applied (e.g., see [7,8]).…”

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

“…Part 2 of the study [10] focuses on exploitation of the Sentinel-2 spectral content for mapping of glaciers, glacier facies, and other glacier processes. It is important to note that our analyses are based on first Sentinel-2A Level 1C data acquired during the commissioning and ramp-up phases and describe first experiences with Sentinel-2A, and not systematic assessments of larger data volumes acquired over a longer time period.…”