---
res:
  bibo_abstract:
  - Obtaining detailed information about high mountain snowpacks is often limited
    by insufficient ground-based observations and uncertainty in the (re)distribution
    of solid precipitation. We utilize high-resolution optical images from Pléiades
    satellites to generate a snow depth map, at a spatial resolution of 4 m, for a
    high mountain catchment of central Chile. Results are negatively biased (median
    difference of −0.22 m) when compared against observations from a terrestrial Light
    Detection And Ranging scan, though replicate general snow depth variability well.
    Additionally, the Pléiades dataset is subject to data gaps (17% of total pixels),
    negative values for shallow snow (12%), and noise on slopes >40–50° (2%). We correct
    and filter the Pléiades snow depths using surface classification techniques of
    snow-free areas and a random forest model for data gap filling. Snow depths (with
    an estimated error of ~0.36 m) average 1.66 m and relate well to topographical
    parameters such as elevation and northness in a similar way to previous studies.
    However, estimations of snow depth based upon topography (TOPO) or physically
    based modeling (DBSM) cannot resolve localized processes (i.e., avalanching or
    wind scouring) that are detected by Pléiades, even when forced with locally calibrated
    data. Comparing these alternative model approaches to corrected Pléiades snow
    depths reveals total snow volume differences between −28% (DBSM) and +54% (TOPO)
    for the catchment and large differences across most elevation bands. Pléiades
    represents an important contribution to understanding snow accumulation at sparsely
    monitored catchments, though ideally requires a careful systematic validation
    procedure to identify catchment-scale biases and errors in the snow depth derivation.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Thomas E.
      foaf_name: Shaw, Thomas E.
      foaf_surname: Shaw
  - foaf_Person:
      foaf_givenName: Simon
      foaf_name: Gascoin, Simon
      foaf_surname: Gascoin
  - foaf_Person:
      foaf_givenName: Pablo A.
      foaf_name: Mendoza, Pablo A.
      foaf_surname: Mendoza
  - foaf_Person:
      foaf_givenName: Francesca
      foaf_name: Pellicciotti, Francesca
      foaf_surname: Pellicciotti
      foaf_workInfoHomepage: http://www.librecat.org/personId=b28f055a-81ea-11ed-b70c-a9fe7f7b0e70
  - foaf_Person:
      foaf_givenName: James
      foaf_name: McPhee, James
      foaf_surname: McPhee
  bibo_doi: 10.1029/2019wr024880
  bibo_issue: '2'
  bibo_volume: 56
  dct_date: 2020^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/0043-1397
  - http://id.crossref.org/issn/1944-7973
  dct_language: eng
  dct_publisher: American Geophysical Union@
  dct_subject:
  - Water Science and Technology
  dct_title: Snow depth patterns in a high mountain Andean catchment from satellite
    optical tristereoscopic remote sensing@
...