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Remotely sensing the German Wadden Sea—a new approach to address national and international environmental legislation

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Abstract

The Wadden Sea along the North Sea coasts of Denmark, Germany, and the Netherlands is the largest unbroken system of intertidal sand and mud flats in the world. Its habitats are highly productive and harbour high standing stocks and densities of benthic species, well adapted to the demanding environmental conditions. Therefore, the Wadden Sea is one of the most important areas for migratory birds in the world and thus protected by national and international legislation, which amongst others requires extensive monitoring. Due to the inaccessibility of major areas of the Wadden Sea, a classification approach based on optical and radar remote sensing has been developed to support environmental monitoring programmes. In this study, the general classification framework as well as two specific monitoring cases, mussel beds and seagrass meadows, are presented. The classification of mussel beds profits highly from inclusion of radar data due to their rough surface and achieves agreements of up to 79 % with areal data from the regular monitoring programme. Classification of seagrass meadows reaches even higher agreements with monitoring data (up to 100 %) and furthermore captures seagrass densities as low as 10 %. The main classification results are information on area and location of individual habitats. These are needed to fulfil environmental legislation requirements. One of the major advantages of this approach is the large areal coverage with individual satellite images, allowing simultaneous assessment of both accessible and inaccessible areas and thus providing a more complete overall picture.

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References

  • Adam, S., De Backer, A., De Wever, A., Sabbe, K., Toorman, E. A., Vincx, M., et al. (2011). Bio-physical characterization of sediment stability in mudflats using remote sensing: a laboratory experiment. Continental Shelf Research, 31(10, Supplement), S26–S35.

    Article  Google Scholar 

  • Alexandridis, T. K., Lazaridou, E., Tsirika, A., & Zalidis, G. C. (2009). Using Earth Observation to update a Natura 2000 habitat map for a wetland in Greece. Journal of Environmental Management, 90(7), 2243–2251.

    Article  Google Scholar 

  • Allewijn, R. (1992). Applications of remote sensing for tidal waters, coastal areas and inland waters. In European ‘International Space Year’ Conference 1992—remote sensing for environmental monitoring and resource management, Munich, Germany, 30 March - 4 April 1992 (Vol. 2, pp. 651–654). European Space Agency.

  • Bartholdy, J., & Folving, S. (1986). Sediment classification and surface type mapping in the Danish Wadden Sea by remote sensing. Netherlands Journal of Sea Research, 20(4), 337–345.

    Article  Google Scholar 

  • Bortels, L., Chan, J. C. W., Merken, R., & Koedam, N. (2011). Long-term monitoring of wetlands along the Western-Greek bird migration route using Landsat and ASTER satellite images: Amvrakikos Gulf (Greece). Journal for Nature Conservation, 19(4), 215–223.

    Article  Google Scholar 

  • Brockmann, C., & Stelzer, K. (2008). Optical remote sensing of intertidal flats. In V. Barale, & M. Gade (Eds.), Remote sensing of the european seas (pp. 117–128). Springer Science + Business Media B. V.

  • Choe, B.-H., Kim, D.-J., Hwang, J.-H., Oh, Y., & Moon, W. M. (2012). Detection of oyster habitat in tidal flats using multi-frequency polarimetric SAR data. Estuarine, Coastal and Shelf Science, 97, 28–37.

    Article  Google Scholar 

  • Dame, R., Dankers, N., Prins, T., Jongsma, H., & Smaal, A. (1991). The influence of mussel beds on nutrients in the western Wadden Sea and eastern Scheldt estuaries. Estuaries, 14(2), 130–138.

    Article  CAS  Google Scholar 

  • Dankers, N., & Zuidema, D. R. (1995). The role of the mussel (Mytilus edulis L.) and mussel culture in the Dutch Wadden Sea. Estuaries, 18(1A), 71–80.

    Article  Google Scholar 

  • Dennert-Möller, E. (1982). Erstellung einer Sedimentkarte der nordfriesischen Wattgebiete aus Landsat-Bilddaten. Bildmessung und Luftbildwesen, 50, 204–206.

    Google Scholar 

  • Deronde, B., Kempeneers, P., & Forster, R. M. (2006). Imaging spectroscopy as a tool to study sediment characteristics on a tidal sandbank in the Westerschelde. Estuarine, Coastal and Shelf Science, 69(3–4), 580–590.

    Article  Google Scholar 

  • Doerffer, R., & Murphy, D. (1989). Factor analysis and classification of remotely sensed data for monitoring tidal flats. Helgoländer Meeresuntersuchungen, 43(3–4), 275–293.

    Article  Google Scholar 

  • Folving, S. (1984). The Danish Wadden Sea, thematic mapping by means of remote sensing. Folia geografica danica, 5, 1–56.

  • Fraser, R. H., Olthof, I., & Pouliot, D. (2009). Monitoring land cover change and ecological integrity in Canada’s national parks. Remote Sensing of Environment, 113(7), 1397–1409.

    Article  Google Scholar 

  • Gade, M., & Melchionna, S. (2016). Joint use of multiple synthetic aperture radar imagery for the detection of bivalve beds and morphological changes on intertidal flats. Estuarine, Coastal and Shelf Science, 171, 1–10. doi:10.1016/j.ecss.2016.01.025.

    Article  Google Scholar 

  • Gade, M., & Stelzer, K. (2010). Multi-sensor remote sensing of the Wadden Sea ecosystem on the North Sea coast. Ocean from Space 2010 Symposium, Venice, Italy, 26–30 April 2010.

  • Gade, M., Alpers, W., Melsheimer, C., & Tanck, G. (2008). Classification of sediments on exposed tidal flats in the German Bight using multi-frequency radar data. Remote Sensing of Environment, 112(4), 1603–1613.

    Article  Google Scholar 

  • Gade, M., Melchionna, S., Stelzer, K., & Kohlus, J. (2014). Multi-frequency SAR data help improving the monitoring of intertidal flats on the German North Sea coast. Estuarine, Coastal and Shelf Science, 140, 32–42.

    Article  Google Scholar 

  • Hearn, S. M., Healey, J. R., McDonald, M. A., Turner, A. J., Wong, J. L. G., & Stewart, G. B. (2011). The repeatability of vegetation classification and mapping. Journal of Environmental Management, 92(4), 1174–1184.

    Article  CAS  Google Scholar 

  • HIMOM (2005). Final Report EU Contract EVK3-CT-2001-00052.

  • Ibrahim, E., & Monbaliu, J. (2011). The suitability of spaceborne multispectral data for sediment characterization: a case study. Coastal, Estuarine & Shelf Science, 92, 437–445.

    Article  CAS  Google Scholar 

  • Jung, R., & Ehlers, M. (2014). A hierarchical classification of the German tidal flats using a multi-sensor and multi-temporal remote sensing approach. 34th EaRSEL Symposium, Warsaw, Poland, 16.-20.06.2014.

  • Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., et al. (2009). Remote sensing change detection tools for natural resource managers: understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment, 113(7), 1382–1396.

    Article  Google Scholar 

  • Kleeberg, U. (1990). Kartierung der Sedimentverteilung im Wattenmeer durch integrierte Auswertung von Satellitendaten und Daten der Wattenmeerdatenbank (WADABA) der GKSS. Thesis, Universität Trier, Trier.

  • Kokke, J. M. M. (1995). Mapping of intertidal surface sediments using high resolution remote sensing (a study in the Westerscheldt area, the Netherlands). EARSeL Advances in Remote Sensing, 4(1), 35–44.

    Google Scholar 

  • Lee, K.-S., Park, S. R., & Kim, Y. K. (2007). Effects of irradiance, temperature, and nutrients on growth dynamics of seagrasses: a review. Journal of Experimental Marine Biology and Ecology, 350, 144–175.

    Article  Google Scholar 

  • MLUR - Ministerium für Landwirtschaft, Umwelt und ländliche Räume des Landes Schleswig-Holstein (2010). Bewirtschaftungsplan nach Artikel 13 der Richtlinie 2000/60/EG für die Flussgebietseinheit Eider. Kiel, 247 pp.

  • Nehls, G., Witte, S., Büttger, H., Dankers, N., Jansen, J., Millat, G., et al. (2009). Beds of blue mussels and Pacific oysters. Thematic Report No. 11. In H. Marencic & J. de Vlas (Eds.), Quality Status Report 2009. Wadden Sea Ecosystem No. 25. Common Wadden Sea Secretariat, Trilateral Monitoring and Assessment Group, Wilhelmshaven, Germany.

  • Pröber, C. (1981). Die Möglichkeiten der Fernerkundung in der Küstengeologie: eine Untersuchung am Beispiel der nordfriesischen Wattsedimente und der Schwebfracht in der Nordsee. Dissertation, Universität Kiel, Kiel.

  • Rainey, M. P., Tyler, A. N., Bryant, R. G., Gilvear, D. J., & McDonald, P. (2000). The influence of surface and interstitial moisture on the spectral characteristics of intertidal sediments: implications for airborne image acquisition and processing. International Journal of Remote Sensing, 21(16), 3025–3038.

    Article  Google Scholar 

  • Rainey, M. P., Tyler, A. N., Gilvear, D. J., Bryant, R. G., & McDonald, P. (2003). Mapping intertidal estuarine sediment grain size distributions through airborne remote sensing. Remote Sensing of Environment, 86(4), 480–490.

    Article  Google Scholar 

  • Smith, G. M., & Fuller, R. M. (2001). An integrated approach to land cover classification: an example in the island of Jersey. International Journal of Remote Sensing, 22(16), 3123–3142.

  • Stelzer, K., & Brockmann, C. (2006). Optische Fernerkundung für die Küstenzone. In K. P. Traub & J. Kohlus (Eds.), GIS im Küstenzonen Management – Grundlagen und Anwendungen. Heidelberg.

  • Stevens, J. P., Blackstock, T. H., Howe, E. A., & Stevens, D. P. (2004). Repeatability of phase 1 habitat survey. Journal of Environmental Management, 73(1), 53–59.

    Article  CAS  Google Scholar 

  • TMAG – Trilateral Monitoring and Assessment Group (2009). TMAP manual. The Trilateral Monitoring and Assessment Program (TMAP) Wilhelmshaven, http://www.waddensea-secretariat.org/monitoring-tmap/manual-guidelines.

  • van der Graf, S., Jonker, I., Herlyn, M., Kohlus, J., Fogh Winter, H., Reise, K., et al. (2009). Seagrass. Thematic Report No. 12. In H. Marencic & J. de Vlas (Eds.), Quality Status Report 2009. Wa dden Sea Ecosystem No. 25. Common Wadden Sea Secretariat, Trilateral Monitoring and Assessment Group, Wilhelmshaven, Germany.

  • van der Wal, D., & Herman, P. M. J. (2007). Regression-based synergy of optical, shortwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments. Remote Sensing of Environment, 111(1), 89–106.

    Article  Google Scholar 

  • Wang, Y., & Koopmanns, B. N. (1995). Monitoring tidal flat changes using ERS-1 SAR images and GIS in the western Wadden Sea area, the Netherlands. EARSeL Advances in Remote Sensing, 4(1), 45–52.

    Google Scholar 

  • Yates, M. G., Jones, A. R., McGrorty, S., & Goss-Custard, J. D. (1993). The use of satellite imagery to determine the distribution of intertidal surface sediments of the Wash, England. Estuarine, Coastal and Shelf Science, 36(4), 333–344.

    Article  Google Scholar 

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Acknowledgments

We thank H. Büttger and H. Farke as well as all colleagues and volunteers who assisted with the data collection during field campaigns. F. Leverenz and F. Werner helped in the processing of TSX data. Furthermore, we like to thank M. Nyenhuis and colleagues from the German Aerospace Center (DLR) for constructive support during the SAMOWatt project. We also thank the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research on Sylt, BioConsult SH in Husum, and Syltair on Sylt, as well the National Park Authorities in Lower Saxony and Schleswig-Holstein for providing monitoring data and/or logistical support during data collection. TerraSAR-X data were provided by DLR under contract OCE0994. Data from Landsat-7 and Landsat-8, RapidEye, and SPOT-4 were obtained from the USGS, RESA, and the ESA Third Party Mission.

Funding was received from the German Ministry of Economy (BMWi) for the projects DeMarine SAMOWatt (contract numbers 50EE1112, 50EE1115, 50EE1117) and DeMarine-Environment TP4 (contract numbers 50EE0830, 50EE0816, 50EE0817).

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Authors and Affiliations

  1. Schleswig-Holstein Agency for Coastal Defence, National Park and Marine Conservation, National Park Authority, Schlossgarten 1, 25832, Tönning, Germany

    Gabriele Müller, Jasmin Geißler, Jörn Kohlus & Kai Eskildsen

  2. Brockmann Consult GmbH, Max-Planck-Straße 2, 21502, Geesthacht, Germany

    Kerstin Stelzer & Susan Smollich

  3. Institute of Oceanography, University of Hamburg, Bundesstraße 53, 20146, Hamburg, Germany

    Martin Gade, Sabrina Melchionna & Linnea Kemme

  4. National Park Authority Wadden Sea of Lower Saxony, Virchowstr. 1, 26382, Wilhelmshaven, Germany

    Winny Adolph & Gerald Millat

  5. State Agency for Agriculture, Environment and Rural Areas, Hamburger Chaussee 25, 24220, Flintbek, Germany

    Hans-Christian Reimers

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  1. Gabriele Müller
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  2. Kerstin Stelzer
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  3. Susan Smollich
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  4. Martin Gade
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  5. Winny Adolph
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  6. Sabrina Melchionna
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  7. Linnea Kemme
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  8. Jasmin Geißler
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  9. Gerald Millat
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  10. Hans-Christian Reimers
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  11. Jörn Kohlus
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  12. Kai Eskildsen
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Correspondence to Martin Gade.

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Müller, G., Stelzer, K., Smollich, S. et al. Remotely sensing the German Wadden Sea—a new approach to address national and international environmental legislation. Environ Monit Assess 188, 595 (2016). https://doi.org/10.1007/s10661-016-5591-x

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  • DOI: https://doi.org/10.1007/s10661-016-5591-x

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