Geological map of the Arctic

Harrison, J C; St-Onge, M R; Петров, О. В.; Strelnikov, S I; Lopatin, B. G.; Wilson, Frederic H. Digital Files Preparation:; Tella, S; Paul, D; Lynds, T; Shokalsky, SP; Hults, Chad; Bergman, Stefan; Jepsen, H.F; Solli, Arne

doi:10.4095/225705

Cited by 27 publications

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“…7). The transition to a smoother seafloor morphology on the outer continental shelf occurs rather abruptly across a near straight southwest-to-northeast trending line that fits well with geological maps showing change across a thrust fault from igneous rocks to a seafloor composed of sedimentary rocks further offshore 34 (Fig. 7).…”

Section: Technical Validationsupporting

confidence: 79%

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The International Bathymetric Chart of the Arctic Ocean Version 4.0

et al. 2020

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Bathymetry (seafloor depth), is a critical parameter providing the geospatial context for a multitude of marine scientific studies. Since 1997, the International Bathymetric Chart of the Arctic Ocean (IBCAO) has been the authoritative source of bathymetry for the Arctic Ocean. IBCAO has merged its efforts with the Nippon Foundation-GEBCO-Seabed 2030 Project, with the goal of mapping all of the oceans by 2030. Here we present the latest version (IBCAO Ver. 4.0), with more than twice the resolution (200 × 200 m versus 500 × 500 m) and with individual depth soundings constraining three times more area of the Arctic Ocean (∼19.8% versus 6.7%), than the previous IBCAO Ver. 3.0 released in 2012. Modern multibeam bathymetry comprises ∼14.3% in Ver. 4.0 compared to ∼5.4% in Ver. 3.0. Thus, the new IBCAO Ver. 4.0 has substantially more seafloor morphological information that offers new insights into a range of submarine features and processes; for example, the improved portrayal of Greenland fjords better serves predictive modelling of the fate of the Greenland Ice Sheet. Background & Summary A broad range of Arctic climate and environmental research, including questions on the declining cryosphere and the geological history of the Arctic Basin, require knowledge of the depth and shape of the seafloor 1-3. Bathymetry provides the geospatial framework for these and other studies 4 and has impact on many processes, including the pathways of ocean currents and, thus, the distribution of heat 5,6 , sea-ice decline 7 , the effect of inflowing warm waters on tidewater glaciers 8 , and the stability of marine-based ice streams and outlet glaciers grounded on the seabed 9-11. Bathymetric data from large parts of the Arctic Ocean are, however, not available or extremely sparse due to difficulties, both logistical and political, in accessing the region 12. The International Bathymetric Chart of the Arctic Ocean (IBCAO) project, was initiated in 1997 in St Petersburg, Russia, to address the need for up-to-date digital portrayals of the Arctic Ocean seafloor 13. Since 1997, three Digital Bathymetric Models (DBMs) have ingested new data sets compiled by the IBCAO project team and have been released for public use 14-16. These DBMs comprised grids with a regular cell size of 2.5 × 2.5 km (Ver. 1.0), 2 × 2 km (Ver. 2.0) and 500 × 500 m (Ver. 3.0) on a Polar Stereographic projection. Depth estimates for grid cells between constraining depth observations were interpolated by the continuous curvature spline in a tension gridding algorithm 17. All depth data available at the time of the compilations were used, including multi-and single-beam bathymetry, and contours and soundings digitized from depth charts, with direct depth observations having the highest priority and digitized contours the lowest 18. Recognizing the importance of complete global bathymetry, the General Bathymetric Chart of the Ocean (GEBCO), a project under the auspices of the International Hydrographic Organization (IHO) and the Intergovernmental Oceanographic Commissio...

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Section: Technical Validationsupporting

confidence: 79%

“…4.0 (a), Ver. 3.0 (b) and the geological map by Harrison, et al34 (c). The thrust fault marked X-X' on the geological map is shown as a reference on the bathymetric maps in (a,b).…”

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confidence: 99%

The International Bathymetric Chart of the Arctic Ocean Version 4.0

et al. 2020

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“…The inset is a simplified geologic map color-coded by dominant facies within geologic units (C* = dominant carbonate/evaporite, C = major carbonate, Cm = minor carbonate, S = sedimentary, SV = sedimentary and volcanic, SM = sedimentary and metamorphic, Ip = plutonic igneous, Iv = volcanic igneous, M = metamorphic, G = unknown due to glacial coverage). Geologic units are simplified from Wheeler et al [1996] and Harrison et al [2011] (see Text S1 for details).…”

Section: Regional Analysesmentioning

confidence: 99%

On the geochemical heterogeneity of rivers draining into the straits and channels of the Canadian Arctic Archipelago

et al. 2017

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Ten rivers across northern Canada and the Canadian Arctic Archipelago (CAA) were sampled during spring 2014 and summer 2015 to investigate their geochemical heterogeneity for comparison against larger North American (i.e., Mackenzie and Yukon Rivers) and Siberian rivers. In general, rivers draining the western and/or northern regions of the study area have higher solute concentrations and lower 87Sr/86Sr ratios compared to rivers draining the eastern and/or southern regions. The inorganic geochemical signatures largely reflect the bedrock geology, which is predominately carbonate in the western and/or northern regions and silicate in the eastern and/or southern regions. Riverine δ18O values primarily correlate with latitude, with only a few exceptions. Measurements of total alkalinity (TA) were combined with a regional analysis of bedrock geology and extrapolated to produce a range for the mean characteristic TA of rivers draining into the straits and channels of the CAA (628–819 µeq kg−1). Combining this estimate with contributions from the Mackenzie River yields a revised North American river runoff TA of 935–1182 µeq kg−1, which is much lower than that of the Mackenzie River (1540 µeq kg−1). This lower concentration suggests that TA may not be used to distinguish between North American and Siberian river contributions in regions such as Davis Strait.

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“…The 809 gossans used in this study are grouped into six clusters as can be seen in Figure 2. The geological map of the Arctic bedrock compiled by [35] was selected to provide context for our study. This map shows that the gossans from our study can be found on 35 different lithologies.…”

Section: Region Of Studymentioning

confidence: 99%

“…Most of the gossans from the cluster 1 are in metamorphosed siliciclastic rocks dated from the Paleoproterozoic. For more detailed geological settings, please read the description of the geological map from [35]. each Landsat 8 image.…”

Section: Region Of Studymentioning

confidence: 99%

A Deep Learning Approach to the Detection of Gossans in the Canadian Arctic

et al. 2020

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Gossans are surficial deposits that form in host bedrock by the alteration of sulphides by acidic and oxidizing fluids. These deposits are typically a few meters to kilometers in size and they constitute important vectors to buried ore deposits. Hundreds of gossans have been mapped by field geologists in sparsely vegetated areas of the Canadian Arctic. However, due to Canada’s vast northern landmass, it is highly probable that many existing occurrences have been missed. In contrast, a variety of remote sensing data has been acquired in recent years, allowing for a broader survey of gossans from orbit. These include band ratioing or methods based on principal component analysis. Spectrally, the 809 gossans used in this study show no significant difference from randomly placed points on the Landsat 8 imageries. To overcome this major issue, we propose a deep learning method based on convolutional neural networks and relying on geo big data (Landsat-8, Arctic digital elevation model lithological maps) that can be used for the detection of gossans. Its application in different regions in the Canadian Arctic shows great promise, with precisions reaching 77%. This first order approach could provide a useful precursor tool to identify gossans prior to more detailed surveys using hyperspectral imaging.

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Geological map of the Arctic

Cited by 27 publications

References 0 publications

The International Bathymetric Chart of the Arctic Ocean Version 4.0

The International Bathymetric Chart of the Arctic Ocean Version 4.0

On the geochemical heterogeneity of rivers draining into the straits and channels of the Canadian Arctic Archipelago

A Deep Learning Approach to the Detection of Gossans in the Canadian Arctic

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