Preprints
https://doi.org/10.5194/essd-2021-468
https://doi.org/10.5194/essd-2021-468
 
01 Feb 2022
01 Feb 2022
Status: this preprint was under review for the journal ESSD but the revision was not accepted.

Landsat and Sentinel-derived glacial lake dataset in the China-Pakistan Economic Corridor from 1990 to 2020

Muchu Lesi1, Yong Nie1, Dan H. Shugar2, Jida Wang3, Qian Deng1,4, and Huayong Chen1 Muchu Lesi et al.
  • 1Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, China
  • 2Water, Sediment, Hazards, and Earth-surface Dynamics (waterSHED) Lab, Department of Geoscience, University of Calgary, Alberta, T2N 1N4, Canada
  • 3Department of Geography and Geospatial Sciences, Kansas State University, Manhattan, Kansas 66506, USA
  • 4University of Chinese Academy of Sciences, Beijing 100190, China

Abstract. The China-Pakistan Economic Corridor (CPEC) is one of flagship projects of the One Belt One Road Initiative, which faces threats from mountain disasters in the high altitude region, such as glacial lake outburst floods (GLOFs). An up-to-date high-quality glacial lake dataset with critical parameters (e.g. lake types), which is fundamental to flood risk assessments and predicting glacier-lake evolutions, is still largely absent for the entire CPEC. This study describes a glacial lake dataset in 2020 for CPEC at 10–30 m resolution, which was produced from both Landsat and Sentinel optical images as well as glacial lake inventories in 1990 and 2000 from Landsat observation, using an advanced object-oriented mapping method associated with rigorous visual inspection workflows. The results show that Landsat derived 2234 glacial lakes in 2020, covering a total area of 86.31 ± 14.98 km2 with a minimum mapping unit of 5 pixels (4500 m2), whereas Sentinel derived 7560 glacial lakes in 2020 with a total area of 103.70 ± 8.45 km2 with a minimum mapping unit of 5 pixels (500 m2). The discrepancy implies that there is a significant quantity of small glacier lakes not recognized in existing glacial lake inventories and a more thorough inclusion of them require future efforts using higher resolution data. The total number and area of glacial lakes from consistent 30 m resolution Landsat images remain relatively stable despite a slight increase from 1990 to 2020. A range of critical attributes have been generated in the dataset, including lake types of two classification systems and mapping uncertainty estimated by an improved equation. This comprehensive glacial lake dataset has potentials to be widely applied in studies on glacial lake-related hazards and glacier-lake interactions, and is freely available at https://doi.org/10.12380/Glaci.msdc.000001 (Lesi et al., 2022).

Muchu Lesi et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-468', Anonymous Referee #1, 14 Feb 2022
    • AC1: 'Reply on RC1', Yong Nie, 21 Mar 2022
  • RC2: 'Comment on essd-2021-468', Anonymous Referee #2, 14 Feb 2022
    • AC2: 'Reply on RC2', Yong Nie, 21 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-468', Anonymous Referee #1, 14 Feb 2022
    • AC1: 'Reply on RC1', Yong Nie, 21 Mar 2022
  • RC2: 'Comment on essd-2021-468', Anonymous Referee #2, 14 Feb 2022
    • AC2: 'Reply on RC2', Yong Nie, 21 Mar 2022

Muchu Lesi et al.

Data sets

Landsat and Sentinel-derived glacial lake dataset in the China-Pakistan Economic Corridor from 1990 to 2020 Muchu Lesi, Yong Nie, Dan H. Shugar, Jida Wang, Qian Deng, Huayong Chen https://doi.org/10.12380/Glaci.msdc.000001

Muchu Lesi et al.

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Short summary
The China-Pakistan Economic Corridor plays a vital role in foreign trade, facing threats from glacial lake outburst floods. An up-to-date glacial lake dataset with critical parameters is basic to flood risk and glacier-lake evolution researches, which is absent for the corridor. This study creates a glacial lake dataset in 2020 from Landsat and Sentinel images, in 1990 and 2000 from Landsat images, using an advanced object-oriented mapping method. Our dataset has potentials to be widely applied.