Proceedings Article | 4 April 2023
KEYWORDS: Satellites, Remote sensing, Data storage, Landsat, Earth observing sensors, Atmospheric corrections, Visible radiation, Technology, Satellite imaging, Optical resolution
Selinco Lake is located in the hinterland of the Qinghai-Tibet Plateau. In the context of global climate change, the water area of Selinco Lake is expanding increasingly. Using medium-high resolution optical satellite remote sensing image data such as Landsat5 / 7 / 8 and GF-1 WFV data as the main data sources, this paper carries out the remote sensing survey on the area of Selinco Lake during the non-snow and freezing season (May-October) 2003-2020. Using ICESat-2 and other altimetry satellite data, the long time series water level of the lake from 2003 to 2020 was obtained through the water surface mask processing, water level elevation extraction, and water level information processing. At last, based on altimetry data and lake area based on optical data, the trapezoidal cylindrical volume formula is used to calculate the lake annual storage capacity change, and reveals the trend of water storage over the years through trapezoidal cylindrical volume formula. The results of the study are as follows: from 2003 to 2010, the overall water surface area of Selinco Lake expanded by 315 square kilometers, with an expansion ratio of 14.91%; The water level also showed an obvious and continuous rising trend, the overall water level increased by 7.4 meters, with an average annual growth of 0.5 meters. According to the estimation, compared with 2003, the overall water storage in Selinco Lake has increased by 20 billion cubic meters by 2020, with an average annual growth of 1.1 billion cubic meters. This paper is based on surface remote sensing information extraction, water level elevation extraction, water storage change trend estimation methods, using visible light remote sensing satellite, laser altimetry satellite data to dynamically monitor the water surface, water level, and water storage of Selinco Lake, making up for the shortage of the data from plateau lake water level monitoring stations and providing technical support for all-round dynamic monitoring of plateau lakes.
