Sentinel-2和ICESat-2密集时序数据反演浅平型内陆湖泊水量变化

doi:10.11947/j.AGCS.2023.20220602

测绘学报 ›› 2023, Vol. 52 ›› Issue (12): 2078-2088.doi: 10.11947/j.AGCS.2023.20220602

Sentinel-2和ICESat-2密集时序数据反演浅平型内陆湖泊水量变化

吴浩儒^1,2, 李均力^1,3, 包安明^1,3, 张久丹^1,2, 马英莲⁴

1. 中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室, 新疆乌鲁木齐 830011;
2. 中国科学院大学, 北京 100049;
3. 新疆遥感与地理信息系统应用重点实验室, 新疆乌鲁木齐 830011;
4. 新疆维吾尔自治区测绘科学研究院, 新疆乌鲁木齐 830002

收稿日期:2022-10-21 修回日期:2023-06-06 发布日期:2024-01-03
通讯作者: 李均力 E-mail:lijl@ms.xjb.ac.cn
作者简介:吴浩儒(1999-),男,硕士,研究方向为干旱区水文水资源及湿地生态环境遥感。E-mail:wuhaoru20@mails.ucas.ac.cn
基金资助:
新疆天山科技创新团队(2022TSYCTD0006);国家自然科学基金(U2003201;41671034);第三次新疆综合科学考察项目(2021xjkk1403)

Retrieving water volume changes of shallow inland lakes with dense time-series Sentinel-2 and ICESat-2 data

WU Haoru^1,2, LI Junli^1,3, BAO Anming^1,3, ZHANG Jiudan^1,2, MA Yinglian⁴

1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Xinjiang Laboratory of Remote Sensing and GIS Application, Urumqi 830011, China;
4. Xinjiang Academy of Surveying & Mapping, Urumqi 830002, China

Received:2022-10-21 Revised:2023-06-06 Published:2024-01-03
Supported by:
Tianshan Talent-Science and Technology Innovation Team (No. 2022TSYCTD0006);The National Natural Science Foundation of China (Nos. U2003201;41671034);The Third Integrated Scientific Expedition Project in Xinjiang (No. 2021xjkk1403)

摘要/Abstract

摘要： 干旱区内陆尾闾湖泊由于湖盆地形浅平、岸线复杂等特点,采用传统的水位-面积关系法难以反演高精度的水量变化信息。本文提出了一种基于密集时序ICESat-2和Sentinel-2数据反演浅平型内陆湖泊湖盆地形和重建水量时序的方法。本文方法利用浅平型湖泊季节性变化显著的特性,筛选和计算不同时期湖盆内非水面区域的所有ICESat-2激光光子点的高程信息,并根据水面等高的特性内插得到Sentinel-2不同时相水面线的高程信息,在此基础上通过这些加密的高程点构建高精度湖盆地形信息,并结合水面时序重建湖泊的水量变化。以新疆塔里木河尾闾台特玛湖为试验区,基于132期Sentinel-2卫星影像和28个时相的ICESat-2激光脉冲数据,重建了2016—2022年的湖泊水量时序。结果表明,本文方法获取的湖盆地形高程中误差为0.103 m,可为无资料浅平型湖泊水量信息的时序重建提供一种思路。

关键词: 湖盆地形, 内陆湖, 水量, 时序重建, ICESat-2

Abstract: The inland endorheic lakes in arid regions have shallow-flat basins and complex shorelines, which makes it hard to retrieve high-accuracy water volume changes through traditional 'water level-area curve’ methods. In this paper, a method is proposed to retrieve basin topography and reconstruct time-series water volumes for shallow-flat inland lakes based on multi-temporal ICESat-2 and Sentinel-2 data. Firstly, all the multi-temporal ICESat-2 photons inside the non-water areas of the lake basin were selected and their elevations were retrieved. Secondly, the multi-temporal lake boundaries were delineated from the Sentinel-2 images, and their elevations were interpolated by these ICESat-2 points due to the fact that a lake water boundary is equivalent to a contour line. Finally, the lake basin topography was retrieved based on these densified ICESat-2 photon altimetric points, and the time-series lake volumes were reconstructed according to the basin DEM and time-series lake area extents. The method was tested by the Taitema Lake which is the terminal lake of the Tarim river, and about 132 scenes of Sentinel-2 satellite remote sensing images and 28 phases of ICESat-2 laser beam data were used to reconstructed water volume changes from 2016 to 2022. The result showed that the RMSE error of the lake DEM is 0.103 m, which can provide a way of time series reconstruction of shallow-flat lakes in un-gauged basins.

Key words: lake basin topography, inland lake, water volume, time-series reconstruction, ICESat-2

中图分类号:

P227

吴浩儒, 李均力, 包安明, 张久丹, 马英莲. Sentinel-2和ICESat-2密集时序数据反演浅平型内陆湖泊水量变化[J]. 测绘学报, 2023, 52(12): 2078-2088.

WU Haoru, LI Junli, BAO Anming, ZHANG Jiudan, MA Yinglian. Retrieving water volume changes of shallow inland lakes with dense time-series Sentinel-2 and ICESat-2 data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(12): 2078-2088.

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Sentinel-2和ICESat-2密集时序数据反演浅平型内陆湖泊水量变化

Retrieving water volume changes of shallow inland lakes with dense time-series Sentinel-2 and ICESat-2 data

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