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GIS for planning, navigation acquisition and visualization of results for the study of chemical munition dumpsites in the Baltic Sea

NATALIA GONCHAROVA

Atlantic Branch of P. P. Shirshov Institute of Oceanology, Russian Academy of Sciences, 236000 Kaliningrad, Russia, e-mail: natte@inbox.ru

PAVEL BORODIN, ALEXANDER GRESS

Institute of Computer Science II, University of Bonn, 53117 Bonn, Germany, e-mail: {borodin,gress}@cs.uni-bonn.de

Abstract: The MERCW project focuses on the study of chemical munition dumpsites in the Baltic Sea. To analyse the ecological risks related to sea-dumped weapons, data and analyses generated by a variety of disciplines need to be integrated. The most suitable solution to store, visualize and analyse the data, which is spatial by its nature, is to use the functionality of a geographic information system (GIS). We are developing a system, which combines the capabilities and flexibility of a 3D GIS application with the latest advances in various fields of scientific visualization, aiming to integrate the data gathered during more than 30 years of research as well as newly acquired data. Furthermore, for acquisition of new data with high quality, software for marine navigation and cartography should be used with maximum efficiency. The results of data integration will allow better analysis of the available information and efficient planning of the future field investigations. Our goal is to deliver a complex system of useful and easy-to-use tools for collection, storage, analysis and visualization of a wide range of data types. Keywords: GIS, software for marine navigation and nautical cartography, high quality data acquisition, scientific visualization, chemical munition dumpsites.

Figure 1. Preparation for the measurements (left) and use of the navigation software in the laboratory (middle) on board R/V “Professor Shtokman”;

visualization of hydrodynamics using the project visualization system (right). 1 INTRODUCTION Large quantities of warfare were dumped after WW1 and WW2 in the European and Russian seas, forming а potential threat to the marine environment and population of the coastal zones. The MERCW (Modelling of Ecological Risks Related to Sea-Dumped Chemical Weapons) project, started in 2005 and funded by the European Commission under the Sixth Framework Programme, is carried out by 10 European and Russian research institutions and focuses on the study of chemical munition dumpsites in the Baltic Sea. Through site investigations and

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modelling an assessment should be made of the ecological risks related to the dumped warfare for the marine ecosystem and people. To properly analyse the ecological risks related to sea-dumped chemical weapons, data and analyses generated by a variety of independent disciplines are integrated. The project comprises a team of experts in marine geology, geophysics, oceanography, toxicology, modelling, scientific visualisation and data management, enabling skilled use of front-line technologies. The research in the project includes collection and analysis of existing data of various types, acquisition of new data, modelling of various processes (migration of released toxic compounds etc.), visualization and, finally, assessment of ecological risks. Since most of the data to be used in the project is spatial by its nature, the most suitable solution to store, visualize and analyse it is to use the functionality of a geographic information system. As none of the existing software fully meets our requirements, our aim was to develop a unique system, which combines the capabilities and flexibility of a 3D GIS application with the latest advances in various fields of scientific visualization. Furthermore, since new data should be gathered with highest spatial precision, available software for marine navigation and nautical cartography should be involved in the workflow as efficiently as possible. In the following sections we will consider some areas of research in the MERCW project, which deal with the data used in the project, its acquisition, presentation and analysis. 2 DATA FLOW IN THE PROJECT This section provides an overview of the most important uses of data within the project. 2.1 Data collection To properly organise the collection of data, we analysed all data types and corresponding formats that will be used during the project. We considered the data already collected and owned by the project participants, the data that will be collected during the project and the publicly available data stored at various archives over the Internet. 2.1.1 Archival data A considerable amount of data from the areas relevant to the MERCW project (Bornholm area, Gotland deep and Skagerrak area) was gathered by the participating parties during more than 30 years of research and was now provided for the use within the project. The obtained data comes from many types of measurements: hydrochemical and geochemical samples, lithological samples, hydrophysical samples, microbiological samples, geophysical profiles, hydrophysical profiles and seismic profiles. Measured values were obtained for a variety of parameters, including concentration of various contaminants: petroleum hydrocarbons, heavy metals, arsenic, chemical warfare components, phenol, chlorophenols, chloroorganic pesticides, cyclooctasulfur. The data also includes such information as moisture of the samples, type of sediments, macro- and microelements and their compounds. 2.1.2 New data acquisition In the course of the whole project new data will be acquired by most participating institutions during research cruises in the Baltic Sea. These measurements should be performed for all parameters listed above as well as some additional parameters and will be planned based on

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the availability of the respective archival data, where visualization of existing data will play a very important role. The necessity to perform high quality measurements with highest spatial precision makes high demands on the use of navigation facilities of the research vessel. In Section 3 we will discuss how this issue was addressed in our research. 2.1.3 Publicly available data Among the publicly available data, especially the digital elevation models and bathymetric maps of the Baltic Sea are an important basis for the visualization in the project. This includes the SRTM30-Plus dataset [Becker and Sandwell 2004], which combines digital topographic and bathymetric data from the whole Earth in a moderate resolution and the IOWTOPO dataset [Seifert et al. 2001], which contains bathymetric data from the Baltic Sea region in a slightly higher resolution, as well as the Blue Marble: Next Generation Earth imagery dataset [Stöckli et al. 2005]. Additional cartographic data for the Baltic Sea region were obtained from various public archives, such as the Baltic GIS Portal (http://www.ekoi.lt/gis). This includes site names and vector maps containing coastlines, depth contours, sea ice areas etc.

Figure 2. : Visualization of the collected data in the project visualization system.

2.2 Data analysis and processing A lot of information was extracted from cruise reports. Since data provided by different organisations often used different abbreviation rules, units of measurement etc., unification was required and performed. After analysis and manual pre-processing, all information was processed using specifically developed software tools and stored in a relational database, which is used as a common project database and allows export to different required formats. For all types of measurements, metadata was extracted. In case of sampling stations, this includes coordinates of the station, sampling instruments, type of sampling (water, interstitial

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water or bottom sediments) and types of analyses. Metadata on profiles includes coordinates of the profile’s start and end points and the profiling instruments used. 2.3 Data presentation For visualization purposes, all information about the measurements, including their spatial locations and the aforementioned metadata, as well as relevant measurement results were converted into ESRI Shapefiles. The Shapefile format [ESRI 1998] is a de facto standard for storing geospatial vector maps including georeferences and metadata, especially in the GIS community. Many resources in this format are available, and many tools support it. One important application of the Shapefiles generated from the database was the creation of a map of existing measurements, which is used in the planning of future cruises. In addition, the generated Shapefiles can be used directly in the project visualization system (see Figure 2). Section 4 will provide more details on the project visualization system and the techniques used for visualizing the collected data. 3 SPECIALIZED NAVIGATION-ORIENTED GIS SYSTEM Since the use of GIS-based applications in the marine context has special requirements [Gagarsky 2003], there is a well-established practice of using specialized navigation-oriented GIS systems. Among these, the dKart products developed by Morintech Navigation AS have shown to be very reliable tools for marine navigation and nautical cartography and are very well suited for the requirements of the project. To provide highest spatial precision during data acquisition, the navigation software should be installed not only on the navigation bridge, where access to it is very limited because of cruise safety regulations, but also in the laboratory of the research vessel. This scheme of navigation acquisition was developed during the recent cruises of R/V “Professor Shtokman”, a medium-sized research vessel build in 1979 and operated by the P. P. Shirshov Institute of Oceanology of the Russian Academy of Sciences.

Figure 3. The scheme of navigation acquisition on board R/V “Professor Shtokman”.

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All regular navigation facilities were connected to an NMEA-0183 compatible hub used in the local network of the vessel. A dKart Navigator workstation at the navigation bridge was connected to the hub. The use of a local network consisting of a main workstation at the navigation bridge and a PC at the laboratory, which receives navigation and bathymetric information from the main workstation in the form of NMEA messages, provides simplified interaction between independent PCs running the navigation software (see Figure 3). This allows efficient route planning, automatic route monitoring on chart, determining positions of additional boats, recording of the navigational situation in the electronic logbook and export of information to other systems. The dKart Navigator software also allows construction of digital elevation models of the sea bottom, including 3D models and cross-sections, visualization of sampling stations and detected objects, overlaying of thematic maps and import of graphical and attribute information. The use of the software in the laboratory allows control of the manoeuvre at the research area (see Figure 4), on-the-fly planning of the field research, especially the measurements concerned with weather conditions and unforeseen circumstances, event log maintenance as well as preparation of the cruise reports. In addition, the printing capabilities allow to produce high-quality navigation maps with various user-defined layers and generalization of contents depending on the scale of the map.

Figure 4. Navigation acquisition for work in a delimited

research area (left) and precise sampling (right). The precise sampling following the exact scheme of sampling points makes higher demands on on-line navigation. To address this issue, during the last cruise in the summer 2007 some modifications were applied to the above system: the dKart Navigator workstation in the laboratory was connected to an independent GPS receiver with its antenna installed in line with the ship’s DGPS (differential GPS) antenna at the navigation bridge. The principal dimensions of the ship and positions of both antennas were put into the software. This allows to restore the position of the vessel not as a point, but as a linear object based on the automatic entries in the ship’s log. This is especially important during the work at a station, since the constant ship position results in a zero course value and, therefore, the impossibility to restore its orientation. 4 USE OF VISUALIZATION IN THE PROJECT The use of visualization within the MERCW project has two main targets. First, it provides a quick and intuitive overview over the data acquired during the project as well as the relevant

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data collected previously. Second, it is an important instrument to present the results of the project such as potential risk scenarios resulting from the analyses and modelling in the project. Since these interactive visualizations are to be used by scientists with different background, the data should be presented in an easily understandable way. In this section we will give a short overview of the four main components, which are currently included in the project visualization system: visualization of topographic and bathymetric data, visualization of scattered measurements and 2D vector maps, visualization of multi-dimensional gridded data and visualization of hydrodynamics. 4.1 Visualization of topographic and bathymetric data We generated a digital terrain model of the Baltic Sea region based on the IOWTOPO bathymetric dataset and the Blue Marble: Next Generation Earth imagery dataset mentioned above. Since the ability to view the whole Baltic Sea region is required as well as the ability to zoom into any area of interest showing more details of the inspected data, suitable multi-resolution visualization techniques have been used. The visualization of bathymetric and topographic data in our visualization system is realized based on the scalable compression and rendering approach by Wahl et al. [2004], which is very well suited for the project-specific requirement of efficiently reproducing a real terrain dataset at different scales with guaranteed precision. To improve the depth perception of the viewer when looking at the relatively shallow Baltic Sea bathymetry, we implemented the following techniques. First, the user has the ability to adjust the vertical scaling of the bathymetric data for visualization. We found that an exaggerated vertical scaling, using a scaling factor of 10 to 100 times, provides a good impression of the Baltic Sea bathymetry. Furthermore, we incorporated dynamic lighting of the terrain, which also improves the depth perception heavily. Finally, the visualization system also allows overlaying isolines onto the terrain, similar to the traditional visualization of these data in 2D visualization systems. 4.2 Visualization of scattered measurements and 2D vector maps One type of data acquired during surveys is scattered, i.e. measured only at irregularly distributed locations, e.g. samples, positions of shipwrecks, etc. The visualization system has the ability to provide an overview over the locations of these measurements and can also show other information associated with these locations (the metadata). Another type of data to be included into the visualization is 2D shape data, e.g. the ship tracks or other data that can be represented by 2D vector maps. Our visualization system shows scattered data as points on the 3D terrain. The associated metadata can either be directly embedded into the 3D visualization or shown separately on user request, as shown in Figure 2. 2D shapes are visualized as lines or polygonal areas on the 3D terrain. While a 2D shape might have a certain depth value, e.g. for data measured at sea surface level or at a fixed depth, 2D shapes of unspecified depth are visualized by projecting them onto the surface of the terrain model, i.e. onto the sea bottom (see Figure 2). For the visualization of such projected shapes we use the efficient projective visualization technique proposed by Schneider and Klein [2007]. 4.3 Visualization of multi-dimensional gridded data Most types of processed data, especially data created by techniques of data interpolation, as well as many types of modelled data can be characterized as multi-dimensional gridded data.

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In most cases rectilinear or uniform grids are used. Data grids can be scalar-valued (i.e. they store a single scalar value, such as temperature or salinity, at each grid cell) or vector-valued (e.g. grids that store current vectors at each grid cell). Our visualization system uses different techniques for visualizing such 2- or 3-dimensional data grids. The most important one with respect to the project is the use of so-called curtain plots [Ware et al. 2001] to show seismic or other profiles at the spatial locations where they have been acquired. For this purpose, the profile data, given as 2D data grids perpendicular to the water surface, is visualized by coloured, vertically extruded curves on top of the 3D terrain. Inclusion of the profile data in the 3D visualization system provides a more intuitive understanding of the measurements and their spatial relation (see Figure 5).

Figure 5. Visualization of 2D seismic profiles as curtain plots.

4.4 Visualization of hydrodynamics Besides the visualization of gathered data, also the visualization of modelled data is important in the project, especially of data from hydrodynamic simulations. For this purpose, we applied suitable techniques of flow visualization based on particle tracing. This method seems to be specifically suited for the visualization requirements of the project since it is also a very convenient technique to visualize the movement of sediment and the spreading of toxic compounds. For the purposes of the project, the flow visualization has to be as flexible as possible such that it can be applied to any kind of hydrodynamics model developed in the project. At the same time, it should be as efficient as possible to allow real-time visualization and interaction with complex particle systems, which require very large numbers of particles to make the underlying hydrodynamics visually understandable. To account for both aspects in an optimum way, we integrated two alternative approaches in the visualization system: (1) visualization of pre-computed particle simulations and (2) concurrent simulation and visualization of particle systems using recent graphics hardware. The second approach allows to visualize a much higher number of particles in real-time than the first one (see Figure 1, right). 5 CONCLUSIONS Using the methods of data acquisition, processing, storage and visualization described in this paper we achieved the following results.

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We have built a system consisting of two dKart Navigator workstations, which allows to plan and control various tasks performed during the cruise more efficiently and to increase the quality of data collection during work in the research area and precise sampling. The development of a unique visualization system, which combines the capabilities and flexibility of a 3D GIS application with the latest advances in various fields of scientific visualization, allows us to efficiently integrate data gathered during more than 30 years of research as well as newly acquired data and perform its visual spatial analysis. Due to the common data formats, the developed visualization system is capable of data interchange with the navigation software, which reduces the efforts necessary for data integration and allows to use the integrated visualization for the planning of the future field research. ACKNOWLEDGEMENTS The IOWTOPO dataset was produced by the Baltic Sea Research Institute of Warnemünde. The Blue Marble: Next Generation dataset was produced by NASA’s Earth Observatory. We thank the project partners for providing various archival data and our colleagues for helping with implementation and data preparation. Special thanks go to Vadim Paka for his valuable comments. This work was funded by the European Commission under the Sixth Framework Programme (INCO-CT2005-013408). REFERENCES Joseph J. Becker and David T. Sandwell. SRTM30_Plus: data fusion of SRTM land

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Reto Stöckli, Eric Vermote, Nazmi Saleous, Robert Simmon and David Herring. The Blue Marble Next Generation – A true color earth dataset including seasonal dynamics from MODIS. Technical Report, NASA Earth Observatory, October 2005.

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