Environmental Earth Sciences

, 77:773 | Cite as

An insight into the surface velocity of Inylchek Glacier and its effect on Lake Merzbacher during 2006–2016 with Landsat time-series imagery

  • Shiyong Yan
  • Yi Li
  • Zhiguo Li
  • Guang LiuEmail author
  • Zhixing Ruan
  • Zian LiEmail author
Original Article


Mountain glacier is one of the extremely sensitive indicators for climate change, and its surface motion distribution and corresponding variation are valuable information for understanding ice mass exchange and glacier dynamics. This paper presents the long-term ice velocity distributions of Inylchek Glacier in the Tianshan region by pixel-tracking algorithm with time-series Landsat imagery acquired during 2006–2016. Then the monitored ice motion fields of Inylchek Glacier were carefully analyzed and revealed a generally similar spatial distribution characteristic. Most of the ice of the North Inylchek Glacier remains in a stagnant state except for the upstream part, but a relatively high velocity of 20–40 cm/day with an RMSE of 3 cm/day was observed on most part of the South Inylchek Glacier, except for the slow-moving glacier terminus. We also state the glacier dynamics around Lake Merzbacher and their possible effect on its glacier lake outburst flood (GLOF) risk. Besides, the surface velocity distribution on South Inylchek Glacier surface during the ablation period from 2014 to 2016 was also established and also compared with annual velocity. The corresponding difference yields that there is a positive relation between ice motion and temperature variation. Therefore, the time-series ice surface motion yielded by the Landsat imagery thus could provide us an efficient and low-cost way to analyze the current state and changes in glaciers, thanks to the continuous and regular spaceborne observations provided by the Landsat satellites.


Inylchek Glacier Glacier surface velocity Landsat time-series imagery Pixel-tracking algorithm Velocity variation 



This research was supported by the Fundamental Research Funds for the Central Universities (No. 2015QNA32). The work was also supported by a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions, National Natural Science Foundation of China (No. 41590852) and the Key Research Program of Frontier Sciences, CAS (No. QYZDY-SSW-DQC02). The Landsat images employed in this study were archived and provided by the United States Geological Survey (USGS).

Compliance with ethical standards

Conflict of interest

No potential conflict of interest was reported by the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.NASG Key Laboratory of Land Environment and Disaster MonitoringChina University of Mining and TechnologyXuzhouChina
  2. 2.Department of Surveying and PlanningShangqiu Normal UniversityShangqiuChina
  3. 3.Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  4. 4.School of Marine sciencesSun Yat-sen UniversityGuangzhouChina

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