Makarieva, Olga; Shikhov, Andrey; Ostashov, Andrey; Nesterova, Nataliia; Semakina, Anastassiya (2020): Characteristics of aufeis for the Chukotka region derived from Landsat images (2013-2019) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.925430
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Abstract:
Present-day aufeis dataset was created by Landsat-8 OLI images for the period 2013-2019. Each aufeis was delineated by satellite images as polygon. Cloud-free Landsat images are obtained immediately after snowmelt season, to detect the highest possible number of aufeis. Critical values of Normalized Difference Snow Index (NDSI) were used for semi-automated aufeis detection. However, a detailed expert-based verification was performed after automated procedure, to distinguish snow-covered areas from aufeis and cross-reference historical and satellite-based data collections. According to Landsat data, the number of aufeis reaches 2758, with their total area about 1147.1 km². The difference between the Cadastre (1958) and the satellite-derived data may indicate significant changes of aufeis formation environments.
Related to:
Makarieva, Olga; Nesterova, Nataliia; Shikhov, Andrey; Zemlianskova, Anastasiia; Luo, Dongliang; Ostashov, Andrey; Alexeev, Vladimir A (2022): Giant Aufeis - Unknown Glaciation in North-Eastern Eurasia According to Landsat Images 2013-2019. Remote Sensing, 14(17), 4248, https://doi.org/10.3390/rs14174248
Makarieva, Olga; Shikhov, Andrey; Ostashov, Andrey; Nesterova, Nataliia; Semakina, Anastassiya (2020): Aufeis of the North-East of Russia: GIS catalogue for the Chukotka region. PANGAEA, https://doi.org/10.1594/PANGAEA.925440
Makarieva, Olga; Shikhov, Andrey; Ostashov, Andrey; Nesterova, Nataliia; Semakina, Anastassiya (2020): Characteristics of aufeis for the Penzhina River basin derived from Landsat images (2013-2019). PANGAEA, https://doi.org/10.1594/PANGAEA.925439
Makarieva, Olga; Shikhov, Andrey; Ostashov, Andrey; Nesterova, Nataliia; Semakina, Anastassiya (2020): Characteristics of aufeis from the Cadastre of naleds of the North-East of the USSR (1958) for the Chukotka region. PANGAEA, https://doi.org/10.1594/PANGAEA.925416
Makarieva, Olga; Shikhov, Andrey; Ostashov, Andrey; Nesterova, Nataliia; Semakina, Anastassiya (2020): Characteristics of aufeis from the Cadastre of naleds of the North-East of the USSR (1958) for the Penzhina River area. PANGAEA, https://doi.org/10.1594/PANGAEA.925429
Coverage:
Median Latitude: 66.114415 * Median Longitude: 175.038391 * South-bound Latitude: 61.868900 * West-bound Longitude: 164.837000 * North-bound Latitude: 70.040500 * East-bound Longitude: -169.875000
Date/Time Start: 2013-06-17T00:00:00 * Date/Time End: 2017-06-10T00:00:00
Minimum ELEVATION: 0 m a.s.l. * Maximum ELEVATION: 994 m a.s.l.
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Reference/source | Reference | Makarieva, Olga | |||
| 2 | Identification | ID | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | Landsat scene identifier in the WRS2 graph of the US Geological Survey (USGS). The first three digits indicate the column number, and last three digits represent the line number | |
| 3 | DATE/TIME | Date/Time | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | Geocode – of Landsat image | |
| 4 | Comment | Comment | Makarieva, Olga | Additional information, for example, if the aufeis was partly covered by clouds and additional images were used to estimate the area | ||
| 5 | Identification | ID | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | CrossIndex Identifier of aufeis by Landsat images (key field for the reference to the Cadastre data) | |
| 6 | Aufeis area | Aufeis area | km2 | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | |
| 7 | LATITUDE | Latitude | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | Geocode | |
| 8 | LONGITUDE | Longitude | Makarieva, Olga | Remote sensing (Landsat) (LSAT) | Geocode | |
| 9 | ELEVATION | Elevation | m a.s.l. | Makarieva, Olga | Aster GDEM | Geocode – average, of Aufeis |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Size:
8870 data points
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