Abstract. The Himalaya mountain range is characterized by highly glacierized, complex,
dynamic topography. The ablation area of Himalayan glaciers often features a highly
heterogeneous debris mantle comprising ponds, steep and shallow slopes of
various aspects, variable debris thickness, and exposed ice cliffs
associated with differing ice ablation rates. Understanding the composition
of the supraglacial debris cover is essential for a proper understanding of glacier
hydrology and glacier-related hazards. Until recently, efforts to map
debris-covered glaciers from remote sensing focused primarily on glacier
extent rather than surface characteristics and relied on traditional
whole-pixel image classification techniques. Spectral unmixing routines,
rarely used for debris-covered glaciers, allow decomposition of a pixel into
constituting materials, providing a more realistic representation of glacier
surfaces. Here we use linear spectral unmixing of Landsat 8 Operational Land Imager (OLI) images (30 m) to obtain fractional abundance maps of the various supraglacial surfaces
(debris material, clean ice, supraglacial ponds and vegetation) across the
Himalaya around the year 2015. We focus on the debris-covered glacier
extents as defined in the database of global distribution of supraglacial debris cover. The spectrally
unmixed surfaces are subsequently classified to obtain maps of composition
of debris-covered glaciers across sample regions. We test the unmixing approach in the Khumbu region of the central Himalaya,
and we evaluate its performance for supraglacial ponds by comparison with
independently mapped ponds from high-resolution Pléiades (2 m) and
PlanetScope imagery (3 m) for sample glaciers in two other regions with
differing topo-climatic conditions. Spectral unmixing applied over the
entire Himalaya mountain range (a supraglacial debris cover area of 2254 km2) indicates that at the end of the ablation season, debris-covered
glacier zones comprised 60.9 % light debris, 23.8 % dark debris, 5.6 % clean ice, 4.5 % supraglacial vegetation, 2.1 % supraglacial
ponds, and small amounts of cloud cover (2 %), with 1.2 % unclassified
areas. The spectral unmixing performed
satisfactorily for the supraglacial pond and vegetation classes (an F score
of ∼0.9 for both classes) and reasonably for the debris
classes (F score of 0.7). Supraglacial ponds were more prevalent in the monsoon-influenced
central-eastern Himalaya (up to 4 % of the debris-covered area) compared
to the monsoon-dry transition zone (only 0.3 %) and in regions with lower
glacier elevations. Climatic controls (higher average temperatures and more
abundant precipitation), coupled with higher glacier thinning rates and
lower average glacier velocities, further favour pond incidence and the
development of supraglacial vegetation. With continued advances in satellite data and
further method refinements, the approach presented here provides avenues
towards achieving large-scale, repeated mapping of supraglacial features.
Umbrella Starwort Stellaria umbellata Turcz. (Caryophyllaceae): a new record to the flora of the western Himalaya, India
