Landsat subpixel water cover of Lena River Delta, Siberia, with link to ESRI grid files

Landsat data for Samoylov Island (Lena Delta, Siberia) was classified using a k-means unsupervised algorithm in the ENVI 4.7 software. Unsupervised classifications are based solely on the natural groupings within the image, i.e. the spectral properties of the surface, and as such return classes containing spectrally similar pixels. The resulting satellite spectral classification was compared with the aerial land cover classification in order to assess the fine-scale land cover variability within each satellite pixel and k-means class. Classification of was performed with 15 clusters and 15 iterations. The 15 clusters were reduced to 9 groups by merging clusters with little pixel count into spectrally adjacent classes. k-means classification of Landsat pixels is determined by the proportions of open water and dry tundra within each pixel. Class 1 is a water class. Classes 2-9 are characterized by a gradual decrease in open water and an increase in dry tundra. […]

Data and Resources

Dataset extent

Map data © OpenStreetMap contributors
Source https://doi.pangaea.de/10.1594/PANGAEA.786926
Version 1.0
Citation https://doi.org/10.3402/tellusb.v64i0.17301
Authors
  • Author Name: Sina Muster
Temporal coverage
Spatial coverage { "coordinates": [ [ [ 129.5, 72.0 ], [ 129.5, 73.9 ], [ 123.6, 73.9 ], [ 123.6, 72.0 ], [ 129.5, 72.0 ] ] ], "type": "Polygon" }
Station research-station-samoylov-island
Collaborator
Variable measured
Measurement Technique
    Date published 2012-08-03
    Date modified
    Status
    Publisher
    • Publisher name: PANGAEA  Publisher URL: https://www.pangaea.de/
    Provider
    License https://creativecommons.org/licenses/by/3.0/