TY - JOUR
T1 - Landsat- and Sentinel-derived glacial lake dataset in the China-Pakistan Economic Corridor from 1990 to 2020
AU - Lesi, Muchu
AU - Nie, Yong
AU - Shugar, Dan Hirsh
AU - Wang, Jida
AU - Deng, Qian
AU - Chen, Huayong
AU - Fan, Jianrong
N1 - Funding Information:
This research has been supported by the Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2019QZKK0603), the National Natural Science Foundation of China (grant nos. 42171086, 41971153), the International Science & Technology Cooperation Program of China (no. 2018YFE0100100), the Chinese Academy of Sciences “Light of West China”, and the Natural Sciences and Engineering Research Council of Canada (grant no. DG-2020-04207).
Publisher Copyright:
© 2022 Muchu Lesi et al.
PY - 2022/12/15
Y1 - 2022/12/15
N2 - The China-Pakistan Economic Corridor (CPEC) is one of the flagship projects of the One Belt One Road Initiative, which faces threats from water shortage and mountain disasters in the high-elevation region, such as glacial lake outburst floods (GLOFs). An up-to-date high-quality glacial lake dataset with parameters such as lake area, volume, and type, which is fundamental to water resource and flood risk assessments and prediction of glacier-lake evolutions, is still largely absent for the entire CPEC. This study describes a glacial lake dataset for the CPEC using a threshold-based mapping method associated with rigorous visual inspection workflows. This dataset includes (1) multi-temporal inventories for 1990, 2000, and 2020 produced from 30m resolution Landsat images and (2) a glacial lake inventory for the year 2020 at 10m resolution produced from Sentinel-2 images. The results show that, in 2020, 2234 lakes were derived from the Landsat images, covering a total area of 86.31±14.98km2 with a minimum mapping unit (MMU) of 5 pixels (4500m2), whereas 7560 glacial lakes were derived from the Sentinel-2 images with a total area of 103.70±8.45km2 with an MMU of 5 pixels (500m2). The discrepancy shows that Sentinel-2 can detect a large quantity of smaller lakes compared to Landsat due to its finer spatial resolution. Glacial lake data in 2020 were validated by Google Earth-derived lake boundaries with a median (± standard deviation) difference of 7.66±4.96% for the Landsat-derived product and 4.46±4.62% for the Sentinel-derived product. The total number and area of glacial lakes from consistent 30m resolution Landsat images remain relatively stable despite a slight increase from 1990 to 2020. A range of critical attributes has been generated in the dataset, including lake types and mapping uncertainty estimated by an improved equation of Hanshaw and Bookhagen (2014). This comprehensive glacial lake dataset has the potential to be widely applied in studies on water resource assessment, glacial lake-related hazards, and glacier-lake interactions and is freely available at 10.12380/Glaci.msdc.000001 (Lesi et al., 2022).
AB - The China-Pakistan Economic Corridor (CPEC) is one of the flagship projects of the One Belt One Road Initiative, which faces threats from water shortage and mountain disasters in the high-elevation region, such as glacial lake outburst floods (GLOFs). An up-to-date high-quality glacial lake dataset with parameters such as lake area, volume, and type, which is fundamental to water resource and flood risk assessments and prediction of glacier-lake evolutions, is still largely absent for the entire CPEC. This study describes a glacial lake dataset for the CPEC using a threshold-based mapping method associated with rigorous visual inspection workflows. This dataset includes (1) multi-temporal inventories for 1990, 2000, and 2020 produced from 30m resolution Landsat images and (2) a glacial lake inventory for the year 2020 at 10m resolution produced from Sentinel-2 images. The results show that, in 2020, 2234 lakes were derived from the Landsat images, covering a total area of 86.31±14.98km2 with a minimum mapping unit (MMU) of 5 pixels (4500m2), whereas 7560 glacial lakes were derived from the Sentinel-2 images with a total area of 103.70±8.45km2 with an MMU of 5 pixels (500m2). The discrepancy shows that Sentinel-2 can detect a large quantity of smaller lakes compared to Landsat due to its finer spatial resolution. Glacial lake data in 2020 were validated by Google Earth-derived lake boundaries with a median (± standard deviation) difference of 7.66±4.96% for the Landsat-derived product and 4.46±4.62% for the Sentinel-derived product. The total number and area of glacial lakes from consistent 30m resolution Landsat images remain relatively stable despite a slight increase from 1990 to 2020. A range of critical attributes has been generated in the dataset, including lake types and mapping uncertainty estimated by an improved equation of Hanshaw and Bookhagen (2014). This comprehensive glacial lake dataset has the potential to be widely applied in studies on water resource assessment, glacial lake-related hazards, and glacier-lake interactions and is freely available at 10.12380/Glaci.msdc.000001 (Lesi et al., 2022).
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U2 - 10.5194/essd-14-5489-2022
DO - 10.5194/essd-14-5489-2022
M3 - Article
AN - SCOPUS:85145583282
SN - 1866-3508
VL - 14
SP - 5489
EP - 5512
JO - Earth System Science Data
JF - Earth System Science Data
IS - 12
ER -