<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Naegeli, Kathrin</dc:creator>
  <dc:creator>Damm, Alexander</dc:creator>
  <dc:creator>Huss, Matthias</dc:creator>
  <dc:creator>Wulf, Hendrik</dc:creator>
  <dc:creator>Schaepman, Michael</dc:creator>
  <dc:creator>Hoelzle, Martin</dc:creator>
  <dc:date>2017-01-27</dc:date>
  <dc:description xmlns:ns0="xml" ns0:lang="en">Surface albedo partitions the amount of energy received by glacier surfaces from  shortwave fluxes and modulates the energy available for melt processes. The ice- albedo feedback, influenced by the contamination of bare-ice surfaces with light- absorbing impurities, plays a major role in the melting of mountain glaciers in a warming  climate. However, little is known about the spatial and temporal distribution and  variability of bare-ice glacier surface albedo under changing conditions. In this study,  we focus on two mountain glaciers located in the western Swiss Alps and perform a  cross-comparison of different albedo products. We take advantage of high spectral  and spatial resolution (284 bands, 2 m) imaging spectrometer data from the Airborne  Prism Experiment (APEX) and investigate the applicability and potential of Sentinel-2  and Landsat 8 data to derive broadband albedo products. The performance of  shortwave broadband albedo retrievals is tested and we assess the reliability of  published narrow-to-broadband conversion algorithms. The resulting albedo products  from the three sensors and different algorithms are further cross-compared.  Moreover, the impact of the anisotropy correction is analysed depending on different  surface types. While degradation of the spectral resolution impacted glacier-wide mean  albedo by about 5%, reducing the spatial resolution resulted in changes of less than  1%. However, in any case, coarser spatial resolution was no longer able to represent  small-scale variability of albedo on glacier surfaces. We discuss the implications when  using Sentinel-2 and Landsat 8 to map dynamic glaciological processes and to monitor  glacier surface albedo on larger spatial and more frequent temporal scales.</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>https://folia.unifr.ch/global/documents/305210</dc:identifier>
  <dc:identifier>https://folia.unifr.ch/documents/305210/files/nae_cca.pdf</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.3390/rs9020110</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>License undefined</dc:rights>
  <dc:source>Remote Sensing. - 2017, vol. 9, no. 2, p. 110</dc:source>
  <dc:subject xmlns:ns1="xml" ns1:lang="en">glacier</dc:subject>
  <dc:subject xmlns:ns2="xml" ns2:lang="en">Albedo</dc:subject>
  <dc:subject xmlns:ns3="xml" ns3:lang="en">Light-absorbing impurities</dc:subject>
  <dc:subject xmlns:ns4="xml" ns4:lang="en">APEX</dc:subject>
  <dc:subject xmlns:ns5="xml" ns5:lang="en">Sentinel-2</dc:subject>
  <dc:subject xmlns:ns6="xml" ns6:lang="en">Landsat</dc:subject>
  <dc:subject xmlns:ns7="xml" ns7:lang="en">narrow-to-broadband</dc:subject>
  <dc:subject>info:eu-repo/classification/udc/556</dc:subject>
  <dc:title xmlns:ns8="xml" ns8:lang="en">Cross-comparison of albedo products for glacier surfaces derived from airborne and satellite (sentinel-2 and landsat 8) optical data</dc:title>
  <dc:type>http://purl.org/coar/resource_type/c_6501</dc:type>
</oai_dc:dc>
