Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1529-1533, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 1529-1533, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2017

14 Sep 2017

WATER LEVEL MONITORING ON TIBETAN LAKES BASED ON ICESAT AND ENVISAT DATA SERIES

H. W. Li, G. Qiao, Y. J. Wu, Y. J. Cao, and H. Mi H. W. Li et al.
  • College of Surveying and Geo-Informatics, Tongji University, Siping Road 1239, Shanghai 200092, China

Keywords: Satellite Altimetry, Tibet Plateau (TP), ICESat, Water Level, ENVISat

Abstract. Satellite altimetry technique is an effective method to monitor the water level of lakes in a wide range, especially in sparsely populated areas, such as the Tibet Plateau (TP). To provide high quality data for time-series change detection of lake water level, an automatic and efficient algorithm for lake water footprint (LWF) detection in a wide range is used. Based on ICESat GLA14 Release634 data and ENVISat GDR 1Hz data, water level of 167 lakes were obtained from ICESat data series, and water level of 120 lakes were obtained from ENVISat data series. Among them, 67 lakes contained two data series. Mean standard deviation of all lakes is 0.088 meters (ICESat), 0.339 meters (ENVISat). Combination of multi-source altimetry data is helpful for us to get longer and more dense periods cover water level, study the lake level changes, manage water resources and understand the impacts of climate change better. In addition, the standard deviation of LWF elevation used to calculate the water level were analyzed by month. Based on lake data set for the TP from the 1960s, 2005, and 2014 in Scientific Data, it is found that the water level changes in the TP have a strong spatial correlation with the area changes.