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DOI | 10.3390/rs12040692 |
Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques | |
Gagarin, Leonid; Wu, Qingbai; Melnikov, Andrey; Volgusheva, Nataliya; Tananaev, Nikita; Jin, Huijun; Zhang, Ze; Zhizhin, Vladimir | |
发表日期 | 2020 |
EISSN | 2072-4292 |
卷号 | 12期号:4 |
英文摘要 | Groundwater icings, typical features of permafrost hydrology, are indicative of hydrothermal interactions between surface and ground waters, and permafrost. Their main morphological parameters, i.e., icing area and volume, are generally estimated with low accuracy. Only scarce field observational data on icing volume and seasonal development exist to date. Our study evaluates and compares performance of several widely used techniques of icing morphometric estimation, based on field data, collected on a giant Icing #2 in the Samokit River basin, southern Yakutia. Groundwater icing area was estimated by: (a) staking, (b) unmanned aerial vehicle (UAV) surveys, and (c) satellite imagery analysis. Icing #2 area in late February was between 1.3810(6) m(2) and 1.6810(6) m(2), icing volume, between 1.7310(6) m(3) and 4.2010(6) m(3), depending on the technique used. Staking is the least accurate, but also the only direct technique, which is hence used as a baseline tool in our study. Staking-based assessment of icing morphometry is the most conservative, while UAV-based estimates of icing area are higher by 14% to 17%, and of icing volume, by 74% to 142%, compared to staking. The latter appears, in our case, to be the least accurate method, although a direct one. It requires a sufficient number of staking points and transects, which should be set up to represent all icing zones, i.e., channel branches and alluvial islands. Photogrammetry based on UAV surveys has numerous advantages, i.e., higher precision of a per pixel icing volume calculation, based on an ice-free valley bottom digital surface model (DSM), and potential reusability of a resulting DSM. However, positioning precision suffers from the overlay of multiple flyovers required because of battery replacements, and, in our case, an insufficient number of ground control points. Satellite imagery along with B.L. Sokolov's empirical approach were used to estimate the annual maximum icing area and volume, and the empirical estimates tend to converge to satellite-based values. Finally, all thing being equal, UAV-based photogrammetry shows higher precision in estimating the icing morphometrical parameters. |
英文关键词 | groundwater icing; sub-permafrost groundwater; supra-permafrost groundwater; remote sensing; UAV-based photogrammetry; Sokolov equations of icing morphometry; Southern Yakutia |
语种 | 英语 |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS关键词 | AUFEIS ; RIVER ; ALASKA ; INSAR ; SNOW |
WOS记录号 | WOS:000519564600103 |
来源期刊 | REMOTE SENSING |
来源机构 | 中国科学院西北生态环境资源研究院 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/240285 |
作者单位 | [Gagarin, Leonid; Wu, Qingbai; Jin, Huijun; Zhang, Ze] Northwest Inst Ecoenvironm & Resources, State Key Lab Frozen Soil Engn, Lanzhou 730000, Peoples R China; [Gagarin, Leonid; Melnikov, Andrey; Tananaev, Nikita; Zhizhin, Vladimir] RAS, Siberian Branch, Melnikov Permafrost Inst, Yakutsk 677010, Russia; [Volgusheva, Nataliya] Geoscan Ltd, 26 Shatelena St, St Petersburg 194021, Russia; [Jin, Huijun] HIT, Sch Civil Engn, Harbin 150090, Peoples R China |
推荐引用方式 GB/T 7714 | Gagarin, Leonid,Wu, Qingbai,Melnikov, Andrey,et al. Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques[J]. 中国科学院西北生态环境资源研究院,2020,12(4). |
APA | Gagarin, Leonid.,Wu, Qingbai.,Melnikov, Andrey.,Volgusheva, Nataliya.,Tananaev, Nikita.,...&Zhizhin, Vladimir.(2020).Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques.REMOTE SENSING,12(4). |
MLA | Gagarin, Leonid,et al."Morphometric Analysis of Groundwater Icings: Intercomparison of Estimation Techniques".REMOTE SENSING 12.4(2020). |
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