Difference between revisions of "Marine geo-information system for the North Sea seafloor"

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===Introduction===
 
===Introduction===
 
Geo-Information Systems (GIS) are designed for the management, visualisation and analysis of geodata. Geodata refers to all measurements and information which are intrinsically tied to their location (latitude, longitude, depth) of observation. It includes data obtained during scientific marine and landside research as well as geodata compiled for economic and socioeconomic needs.  
 
Geo-Information Systems (GIS) are designed for the management, visualisation and analysis of geodata. Geodata refers to all measurements and information which are intrinsically tied to their location (latitude, longitude, depth) of observation. It includes data obtained during scientific marine and landside research as well as geodata compiled for economic and socioeconomic needs.  
[[Image:Schlueter_2.jpg|thumb|300px|right|'''Figure 2''': The compilation of different types of measurements and thematic maps which describe the environmental conditions of the sediment-water-transition zone allows the identification of provinces at the seafloor. Depending on the specific scientific objective, natural conservation issues or economic interests, these provinces might be habitats according to the European Nature Information System (EUNIS), regions suitable for sand and gravel mining, or geochemical provinces characterised by e.g. methane concentrations and morphological features at the seafloor.]]Data measured at distinct locations, thematic maps, georeferenced photographs, videos as well as other types of spatial information can be integrated and analysed by GIS. To facilitate such analysis, the geodata are structured in the form of information layers compiling one parameter set in one map (Fig. 1). *By overlaying information layers, including the attributes, frame, legend etc., the overall map is composed. This allows complex spatial analysis for research objectives such as identification of provinces of the seafloor (Jerosche et al., 2007<ref name="J07eA">Jerosch, K., Schlüter, M., Foucher, J.P., Allais, A.G., Klages, M. & Edy, C. (2007). Spatial distribution of benthic communities affecting the methane concentration at Håkon Mosby Mud Volcano. Marine Geology, 243, 1-17. doi:10.1016/j.margeo. 2007.03.010.</ref>) or calculation of geochemical budgets (Schlüter et al., 2000<ref name="SeA00">Schlüter, M., Sauter, E. J., Schäfer, A. & Ritzau, W. (2000). Spatial budget of organic carbon flux to the seafloor of the northern North Atlantic (60°N - 80°N). Global Biogeochemical Cycles, 14 (1), 329- 340.</ref>), as well as for applications like determination of location factors for the construction of e.g. offshore wind farms or areas suitable for sand and gravel recovery.  
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Data measured at distinct locations, thematic maps, georeferenced photographs, videos as well as other types of spatial information can be integrated and analysed by GIS. To facilitate such analysis, the geodata are structured in the form of information layers compiling one parameter set in one map (Fig. 1). *By overlaying information layers, including the attributes, frame, legend etc., the overall map is composed. This allows complex spatial analysis for research objectives such as identification of provinces of the seafloor (Jerosche et al., 2007<ref name="J07eA">Jerosch, K., Schlüter, M., Foucher, J.P., Allais, A.G., Klages, M. & Edy, C. (2007). Spatial distribution of benthic communities affecting the methane concentration at Håkon Mosby Mud Volcano. Marine Geology, 243, 1-17. doi:10.1016/j.margeo. 2007.03.010.</ref>) or calculation of geochemical budgets (Schlüter et al., 2000<ref name="SeA00">Schlüter, M., Sauter, E. J., Schäfer, A. & Ritzau, W. (2000). Spatial budget of organic carbon flux to the seafloor of the northern North Atlantic (60°N - 80°N). Global Biogeochemical Cycles, 14 (1), 329- 340.</ref>), as well as for applications like determination of location factors for the construction of e.g. offshore wind farms or areas suitable for sand and gravel recovery.  
  
[[Image:Schlueter_3.jpg|thumb|left|'''Figure 3''': This sketch visualises the formation of methane (CH4) in surface sediments. Under anoxic conditions CH4 is formed by the microbial turnover of organic matter. At sites where the methane concentration exceeds saturation, formation of gas bubbles occurs. These bubbles ascend to the sediment water interface and possibly into the water column.]]
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[[Image:Schlueter_2.jpg|thumb|300px|right|'''Figure 2''': The compilation of different types of measurements and thematic maps which describe the environmental conditions of the sediment-water-transition zone allows the identification of provinces at the seafloor. Depending on the specific scientific objective, natural conservation issues or economic interests, these provinces might be habitats according to the European Nature Information System (EUNIS), regions suitable for sand and gravel mining, or geochemical provinces characterised by e.g. methane concentrations and morphological features at the seafloor.]][[Image:Schlueter_3.jpg|thumb|left|'''Figure 3''': This sketch visualises the formation of methane (CH4) in surface sediments. Under anoxic conditions CH4 is formed by the microbial turnover of organic matter. At sites where the methane concentration exceeds saturation, formation of gas bubbles occurs. These bubbles ascend to the sediment water interface and possibly into the water column.]]
  
 
===Motivation===
 
===Motivation===

Revision as of 19:46, 22 April 2009

Figure 1: Within a GIS, spatial information is organised in the form of information layers and archived in a geo database. This supports data mining, geostatistical analysis as well as specific GIS techniques supporting multicriteria decision analysis.

Introduction

Geo-Information Systems (GIS) are designed for the management, visualisation and analysis of geodata. Geodata refers to all measurements and information which are intrinsically tied to their location (latitude, longitude, depth) of observation. It includes data obtained during scientific marine and landside research as well as geodata compiled for economic and socioeconomic needs. Data measured at distinct locations, thematic maps, georeferenced photographs, videos as well as other types of spatial information can be integrated and analysed by GIS. To facilitate such analysis, the geodata are structured in the form of information layers compiling one parameter set in one map (Fig. 1). *By overlaying information layers, including the attributes, frame, legend etc., the overall map is composed. This allows complex spatial analysis for research objectives such as identification of provinces of the seafloor (Jerosche et al., 2007[1]) or calculation of geochemical budgets (Schlüter et al., 2000[2]), as well as for applications like determination of location factors for the construction of e.g. offshore wind farms or areas suitable for sand and gravel recovery.

Figure 2: The compilation of different types of measurements and thematic maps which describe the environmental conditions of the sediment-water-transition zone allows the identification of provinces at the seafloor. Depending on the specific scientific objective, natural conservation issues or economic interests, these provinces might be habitats according to the European Nature Information System (EUNIS), regions suitable for sand and gravel mining, or geochemical provinces characterised by e.g. methane concentrations and morphological features at the seafloor.
Figure 3: This sketch visualises the formation of methane (CH4) in surface sediments. Under anoxic conditions CH4 is formed by the microbial turnover of organic matter. At sites where the methane concentration exceeds saturation, formation of gas bubbles occurs. These bubbles ascend to the sediment water interface and possibly into the water column.

Motivation

Worldwide, the coastal zone has a dense population and coastal waters are often subject to different economic demands. Such activities as well as research objectives or issues like identification of natural conservation areas require detailed information and maps about the marine environment. Unfortunately, such maps are often unavailable, due to the lack or low accessibility of environmental data.

Figure 4: This seismic transect shows the seafloor and sediment strata in the subsurface (to a depth of ~50 m below seafloor). In the right section of this transect a pockmark (a morphological depression at the seafloor) was detected. High concentrations of methane and the occurrence of gas bubbles (below the blue or yellow line) are indicated by the seismic records.

This is often a limiting factor, for example for identification of benthic habitats, e.g. according to the European Nature Information System (EUNIS) as well as for studies on submarine groundwater discharge, occurrence of methane in sediments or the release of nutrients from the seafloor. As a step towards the development of a digital information system we compiled an extensive dataset of bathymetric data, sediment maps, benthos biology, geochemical data, (e.g. concentrations of oxygen or nutrients in bottom waters and sediments), as well as about the use of the seafloor. The data compilation and analysis was part of the EC Project METROL and the BMBF/DFG funded project MarGIS.

Figure 5: High resolution mapping of a pockmark.

Application of a spatial database

For the compilation of a large data set covering a multitude of parameters for the purpose of comparing geo information the careful description of meta- information is essential (Fig. 2). Regarding maps, such meta-information includes the geographic projection, the geodetic datum (e.g. WGS84), the source or the publication date. To cope with the large number of data sets, maps, and meta-information we developed a spatial database scheme. This scheme was implemented as a spatial database which is directly linked to the GIS and, in turn, supports the spatial analysis processes as well as visualisation of results. Combined with the Internet Map Server (IMS), it allows the interactive dissemination of geodata and maps to scientists and the general public.

Figure 6: Spatial distribution of major pockmark fields and occurrence of shallow gas in the North Sea and Skagerrak. The data were compiled from different sources, projected to a common basis and analysed within the geo-information system.

Methane in sediments of the North Sea and Baltic Sea

Methane is an important energy resource and greenhouse gas. Due to its relevance we are interested in identifying regions at the seafloor which are characterised by high methane (CH4) concentrations and locations where methane is transferred into the water column or atmosphere (Fig. 3).

Figure 7: High resolution bathymetric information, survey data about the location of pockmark fields, geochemical data, and geological profiles were combined and visualised in 3D. This allows a virtual flight over the seafloor. By this means the coincidence of structures can be identified. For example the alignment and orientation of pockmarks along the southern part of Norwegian Trench was studied.
For these objectives we compiled geodata about the occurrence of natural gas reservoirs in deeper geological strata, about fault structures which are possible conduits for the migration of fluids and gases, about the spatial distribution of gas-rich surface sediments as well as about morphological features at the seafloor. The later include so called pockmarks and seeps which are indicative of the occurrence of high concentrations of gas (Fig. 4).

For the data management, visualisation of geodata and spatial analysis we applied a geo-information system. This allows computation of the areas at the sea- floor where high gas concentration in surface sediments is observed (Fig. 6, 7). Furthermore, GIS techniques allow to identify intersections of gas rich surface sedi- ments with pockmark fields or fault zones. This provides information about pathways for fluids or gases. The spatial distribution, size and area of a pockmark field in the Eckernförde Bay were investigated by a survey with an Autonomous Underwater Vehicle (Schlüter et al., 2004[3]). Integration of the survey data and previously measured geochemical data into the geo- information system enabled a characterisation of sediment types within pockmarks as well as the distribution of free gas in the subsurface.

References

  1. Jerosch, K., Schlüter, M., Foucher, J.P., Allais, A.G., Klages, M. & Edy, C. (2007). Spatial distribution of benthic communities affecting the methane concentration at Håkon Mosby Mud Volcano. Marine Geology, 243, 1-17. doi:10.1016/j.margeo. 2007.03.010.
  2. Schlüter, M., Sauter, E. J., Schäfer, A. & Ritzau, W. (2000). Spatial budget of organic carbon flux to the seafloor of the northern North Atlantic (60°N - 80°N). Global Biogeochemical Cycles, 14 (1), 329- 340.
  3. Schlüter, M., Sauter, E. J., Andersen, C. E., Dahlgaard, H. & Dando, P. (2004). Spatial Distribution and Budget for Submarine Groundwater Discharge in Eckernförde Bay (W-Baltic Sea). Limnology and Oceanography, 49 (1), 157-167.



The main author of this article is Schlüter, Michael
Please note that others may also have edited the contents of this article.

Citation: Schlüter, Michael (2009): Marine geo-information system for the North Sea seafloor. Available from http://www.coastalwiki.org/wiki/Marine_geo-information_system_for_the_North_Sea_seafloor [accessed on 28-03-2024]


The main author of this article is Jerosch, Kerstin
Please note that others may also have edited the contents of this article.

Citation: Jerosch, Kerstin (2009): Marine geo-information system for the North Sea seafloor. Available from http://www.coastalwiki.org/wiki/Marine_geo-information_system_for_the_North_Sea_seafloor [accessed on 28-03-2024]