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全文摘要次数: 73 全文下载次数: 60
引用本文:

DOI:

10.11834/jrs.20243398

收稿日期:

2023-09-13

修改日期:

2024-05-02

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格陵兰北部冰前河网遥感观测与形态特征分析
刘金昱, 陈定华, 王裕涵, 易晓东, 朱雨欣, 杨康
南京大学地理与海洋科学学院
摘要:

每年消融期,冰前河网在格陵兰北部发育并汇流大量冰面融水进入海洋,是连接冰盖与海洋的重要通道。然而,目前格陵兰北部冰前河网的空间分布与形态特征尚不明晰。研究综合10 m空间分辨率Sentinel-2卫星遥感影像和Copernicus DEM等数据,采用汇流过程约束的水体遥感信息提取方法,精细化提取了2020年消融期格陵兰北部(~100,132 km2)冰前水体遥感信息,进一步顾及水体形态特征区分了冰前河网与孤立湖泊,再利用DEM排水网络连通冰前河网,生成了一套10 m空间分辨率的连通冰前河网与孤立湖泊(Continuous Proglacial River Networks and Isolated Lakes,CPRNs&ILs)遥感数据集。随后,选择5个验证区对比分析了CPRNs&ILs与4种水体遥感数据集(Dynamic World V1,CALC-2020,Esri Land Cover和ESA WorldCover)的河网提取精度,最后量化分析了冰前河网的空间分布与形态特征。结果表明:(1)顾及水体形态特征的划分方法准确提取并划分了冰前河网与孤立湖泊遥感信息,河网遥感信息提取的总体精度为93%±2%,优于上述4种对比数据集(总体精度为83%-89%),能够更为准确地反映研究区冰前河网,尤其是细小河流在消融期的空间分布;(2)格陵兰北部2020年消融期共发育995个冰前河网,总河长为26,605.6 km,水体总面积为1,832.6 km2,能够汇流90.5%的冰面融水进入海洋,剩余仅有9.5%的冰面融水通过入海冰川进入海洋,冰前河网主导着格陵兰北部冰面融水的汇流;(3)冰前河网等级差异明显,最高等级为5级,1-2级河网数量占比超84%,数量有限的40个(4.0%)4-5级高等级河网主导着河网长度(占比52.9%)、水体面积(63.9%)、汇水面积(54.1%)与汇流冰面融水径流量(69.3%)。总体来看,研究生产了一套10 m分辨率的格陵兰北部连通冰前河网与孤立湖泊遥感数据集,揭示了格陵兰北部冰前河网空间分布广泛、高等级河网呈主导作用、冰面融水汇流能力强等特征。研究综合遥感影像与DEM,提取并分析了整个格陵兰北部的连通冰前河网遥感信息,提升了对格陵兰融水从冰面到冰前汇流过程的理解,为分析入海融水对冰盖物质平衡和北极海洋环境的影响提供了数据支撑。

Remote sensing observation and analysis of proglacial river networks on the northern Greenland
Abstract:

Each summer, proglacial river networks develop on the northern Greenland and can route large volumes of surface meltwater into the ocean, acting as important meltwater connections between the ice sheet and the ocean. However, the spatial distribution and geomorphology of the proglacial river networks on the northern Greenland remain unclear. Based on 10 m resolution Sentinel-2 satellite images and 30 m resolution Copernicus DEM, this study maps proglacial water on the northern Greenland (with an area of 100,132 km2) in 2020 using an automatic water remote sensing information extraction algorithm constrained by routing process.First, river features are enhanced from the image background by using modified normalized difference water index (MNDWI), Gabor filter, and path opening operator. Second, the area of interest (AOI) for rivers is constructed to reduce the interference of bare ground and shadow features by combining height above the nearest drainage (HAND) AOI and topographic depressions. Third, the derived water mask is interested with DEM-modeled drainage networks to delete pseudo drainage channels, to generate continuous, realistic drainage networks and to classify proglacial river networks and isolated lakes based on their morphometric characteristics. Finally, proglacial river networks are connected by using continuous DEM-modeled drainage networks to produce the dataset of 10 m resolution continuous proglacial river networks and isolated lakes (CPRs&ILs).Our mapping results show the spatial distribution of proglacial river networks, compare with four water remote sensing datasets (Dynamic World V1, CALC-2020, Esri Land Cover and ESA WorldCover) and quantitatively analyze the length, width, area, drainage density and order of river networks. Our results indicate that: (1) this study accurately extracts and divides remote sensing information of the proglacial river networks and isolated lakes, and the overall accuracy of river network remote sensing information extraction is 93%±2%, which is better than the four comparison datasets (overall accuracy of 83%-89%). Our results can accurately reflect the spatial distribution of the proglacial river networks in the study area, especially small rivers during the melting period; (2) in 2020, a total of 995 proglacial river networks, covering a total water area of 1,832.6 km2, develop on the northern Greenland, and are able to route 90.5% of total surface meltwater runoff into the ocean; (3) proglacial river networks have significant network order difference ranging from 1 to 5. Order 1-2 river networks account for over 84% river networks, whereas the limited number of 40 (<5%) order 4-5 high-order river networks dominate the length of river networks (52.9%), water area (63.9%), catchment area (54.1%), and the routing of surface meltwater runoff (69.3%).Viewing collectively, this study produces a high-resolution proglacial water dataset with large spatial coverage, making up for the lack of precision of the existing datasets, and shows the overall distribution of the large-scale proglacial river networks. Our findings reveal that the widely-distributed proglacial river networks on the northern Greenland are dominated by high-order river networks, and substantially route surface meltwater, thereby improve our understanding of meltwater routing process from the supraglacial to proglacial regions on the northern Greenland.

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