Mirbach, Charlotta; Rehder, Zoé; Kutzbach, Lars; Boike, Julia (2022): Land cover and polygonal pond classification of the Holocene Terrace on Samoylov Island [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.944071
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Abstract:
This dataset contains two sub-datasets:
1) A land cover classification for the Holocene terrace on Samoylov island. The land cover classification is based on a high-resolution near-infrared (NIR) orthomosaic of Samoylov Island, Siberia from summer 2008 (Boike et al., 2012) as well as an existing land cover classification of part of the Holocene terrace by Muster et al. (2012).
2) A shapefile containing all waterbodies on the Holocene terrace on Samoylov island. Here, we applied minimum bounding geometry to each individual pond in order to calculate its compactness, i.e. the extent to which the ponds approximate a circular shape. The extended land cover classification was produced using ArcMap 10.8 (ESRI Inc., USA). As training data, we used a subset of the existing land cover classification by Muster et al. (2012), and applied a maximum likelihood algorithm to the near-infrared (NIR) orthomosaic of Samoylov island. The land cover classes are: wet tundra, dry tundra, open water, and overgrown water. For the water body classification, we applied a majority filter to the new classification and extracted all waterbodies, regardless of whether they were classified as open or overgrown water. After extraction, the minimum bounding distance of the smallest circle was calculated for each waterbody. In order to determine the compactness of each water body, the area of the smallest bounding circle was then divided by the area of the corresponding pond using the field calculator in ArcMap 10.8. Ponds which more closely resemble a circle have a lower measure of compactness. The pond classification was validated using the ponds classified by Rehder et al. (2020). In the data, we used the flag ‚1' for polygonal-center ponds, ‚2' signifies ice-wedge ponds and larger ponds made up of several submerged polygons (merged polygonal ponds) are indicated by the flag ‚3'. Waterbodies which do not fall into any of the three categories were excluded from the classification (‚-1').
Keyword(s):
Related to:
Beckebanze, Lutz; Rehder, Zoé; Holl, David; Mirbach, Charlotta; Wille, Christian; Kutzbach, Lars (in review): Small waterbodies reduce the carbon sink of a polygonal tundra landscape. Biogeosciences Discussions, https://doi.org/10.5194/bg-2021-212
Source:
Boike, Julia; Veh, Georg; Stoof, Günter; Grüber, Maren; Langer, Moritz; Muster, Sina (2015): Visible and near-infrared orthomosaic and orthophotos of Samoylov Island, Siberia, summer 2008, with links to data files. Alfred Wegener Institute - Research Unit Potsdam, PANGAEA, https://doi.org/10.1594/PANGAEA.847343
Further details:
Muster, Sina; Langer, Moritz; Heim, Birgit; Westermann, Sebastian; Boike, Julia (2012): Subpixel heterogeneity of ice-wedge polygonal tundra: a multi-scale analysis of land cover and evapotranspiration in the Lena River Delta, Siberia. Tellus Series B-Chemical and Physical Meteorology, 64, 17301, https://doi.org/10.3402/tellusb.v64i0.17301
Rehder, Zoé; Zaplavnova, Anna; Kutzbach, Lars (2020): Dissolved-gas concentrations, physical and chemical properties of 41 ponds as well as key meteorological parameters in the Lena River Delta, Siberia. PANGAEA, https://doi.org/10.1594/PANGAEA.922399
Project(s):
Funding:
German Research Foundation (DFG), grant/award no. 390683824: EXC 2037: Climate, Climatic Change, and Society (CLICCS)
Coverage:
Latitude: 72.376480 * Longitude: 126.489230
Minimum Elevation: 8.0 m * Maximum Elevation: 8.0 m
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | File content | Content | Mirbach, Charlotta | |||
| 2 | Binary Object | Binary | Mirbach, Charlotta | |||
| 3 | Binary Object (File Size) | Binary (Size) | Bytes | Mirbach, Charlotta |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
4 data points