地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (7): 1510-1521.doi: 10.12082/dqxxkx.2020.190538
罗竹1,2(), 刘凯2, 张春亢1, 邓心远3, 马荣华2, 宋春桥2,*(
)
收稿日期:
2019-09-23
修回日期:
2020-02-27
出版日期:
2020-07-25
发布日期:
2020-09-25
通讯作者:
宋春桥
E-mail:m15761635597_1@163.com;cqsong@niglas.ac.cn
作者简介:
罗 竹(1994— ),女,贵州贵阳人,硕士生,主要从事环境遥感与数字地形分析研究。E-mail:基金资助:
LUO Zhu1,2(), LIU Kai2, ZHANG Chunkang1, DENG Xinyuan3, MA Ronghua2, SONG Chunqiao2,*(
)
Received:
2019-09-23
Revised:
2020-02-27
Online:
2020-07-25
Published:
2020-09-25
Contact:
SONG Chunqiao
E-mail:m15761635597_1@163.com;cqsong@niglas.ac.cn
Supported by:
摘要:
在全球变化背景下,湖泊水文的动态变化不仅是评估和预测气候与环境变化的重要指示剂,同时对社会可持续发展、水资源的开发与利用、生态文明建设等产生重要影响。湖泊水文的动态变化受到湖滨及湖底地形的控制,数字高程模型(DEM)成为湖泊水文研究的重要数据源。随着遥测技术的发展,高分辨率、区域/全球大尺度DEM数据的获取手段快速发展、数据源不断丰富,DEM对推动湖泊水文动态研究进展起到了关键作用。本文首先基于Web of Science平台对DEM在湖泊水文动态研究中的相关文献进行了分析,阐述了该主题现有研究在发文时间、发文数量增减态势、研究区域与热点地区、文献所涉及的DEM数据等方面的特点。接着,围绕着DEM在湖泊水文动态的研究中4个主要方向:湖泊水域变化、湖泊水位变化、湖泊水量变化、湖泊水文灾害情势,重点总结:DEM与其他遥感观测平台、实地观测及模型模拟等多源数据的融合策略,数字地形分析与水文学分析、遥感影像分析等方法的集成策略,以及DEM数据不确定性等对湖泊水文变化研究的影响。最后,本文论述了目前DEM在湖泊水文研究中存在的关键问题,并结合技术发展趋势和研究热点问题,提出了可能的解决路径和未来的研究前景。
罗竹, 刘凯, 张春亢, 邓心远, 马荣华, 宋春桥. DEM在湖泊水文变化研究中的应用进展[J]. 地球信息科学学报, 2020, 22(7): 1510-1521.DOI:10.12082/dqxxkx.2020.190538
LUO Zhu, LIU Kai, ZHANG Chunkang, DENG Xinyuan, MA Ronghua, SONG Chunqiao. Progress of the DEM Application for Studying Lake Hydrologic Dynamics[J]. Journal of Geo-information Science, 2020, 22(7): 1510-1521.DOI:10.12082/dqxxkx.2020.190538
表1
全球常用的开放DEM数据集"
数据名称 | 覆盖 | 获取原理 | 测量时间 | 主要数据版本 | 数据处理 | 发布机构 | 下载地址 | 发布时间 | 分辨率/m |
---|---|---|---|---|---|---|---|---|---|
SRTM DEM | 56°S~60° N | SAR-C 波段 | 2000.02 | SRTM V.1 | 未编辑 | USGS | http://earthexplorer.usgs.gov | 2003 | 90 |
SRTM V4.1 | 填补空洞,对水体进行了处理 | CGIAR | http://srtm.csi.cgiar.org/srtmdata/ | 2008 | 90 | ||||
SRTM V.3 | 采用ASTER DEMs、GMTED2010、NED作为辅助数据源填补空洞、提高分辨率和精度,对水体进行了处理 | NASA、USGS | https://dwtkns.com/srtm30m/ | 2015 | 30 | ||||
SRTM X-SAR DEM | 56°S~60° N | SAR-X 波段 | 2000.02 | SRTM X-SAR DEM | 未编辑 | DLR | https://download.geoservice.dlr.de/SRTM_XSAR/#download | 2010 | 30 |
ASTER DEM | 83°S~83° N | 光学传感器 | 2000—2011 | ASTER GDEM V.1 | 230万张影像立体测图自动化处理 | METI、NASA | https://gdemdl.aster.jspacesystems.or.jp/ | 2009 | 90 |
2000—2013 | ASTER GDEM V.2 | 提高精度、分辨率及水体的准确性,减少人工误差 | METI、NASA | 2011 | 30 | ||||
2000—2013 | ASTER GDEM V.3 | 填补空洞,使用新的全球水体数据处理水体,减少水域异常 | METI、NASA | 2019 | 30 | ||||
AW3D DEM | 60°S~60° N | 光学传感器 | 2006—2011 | ALOS AW3D 30 V.1.0 | 300万张影像立体测图自动化处理 | JAXAEORC | https://www.eorc.jaxa.jp/ALOS/en/aw3d30/ | 2016 | 30 |
2006—2011 | ALOS AW3D 30 V.2.2 | 填补空洞,对数据质量差的区域进行修补,对海岸线进行了更新 | JAXAEORC | 2019 | 30 | ||||
TanDEM-X | 全球 | SAR-X 波段 | 2010—2015 | TanDEM-X 90 | 未编辑 | DLR | https://download.geoservice.dlr.de/TDM90 | 2018 | 90 |
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