Object-oriented classification of QuickBird data for mapping seagrass spatial structure

• Autorzy: Urbański J.A. , Mazur A. , Janas U.
• Języki publikacji: EN

Abstrakty

EN

QuickBird satellite images were processed using object-based analysis to map the spatial structure of seagrass in sandy shoal habitat in the southern Baltic Sea. A three-level ecological model of seagrass landscape, composed of meadows, beds and patches/gaps, was implemented in the multi-scale object domain. Image segmentation was performed at different spatial scales. In order to determine representative scales for bed level and patch/gap level objects, histograms of delineated objects were analyzed. Using object-oriented classification methods, two hierarchically nested maps of seagrass spatial structure were created. The map of patches/gaps was created using the nearest neighbor classification method in the feature space defined by the mean value of band 2 and the value of the proposed seagrass index. Overall map accuracy was 83%. The second map, which depicted the cover density of seagrass beds, was created on the basis of hierarchical relationships between objects at two chosen spatial scale levels. Both maps were exported as vector objects to GIS. Vector-based mapping of seagrass landscape structures at two scales simultaneously provides new possibilities for using landscape metrics and time change detection methods.

Słowa kluczowe

EN

QuickBird; Baltic Sea; GIS; seagrass; seagrass spatial structure

• Wydawca: Institute of Oceanography University of Gdańsk
• Czasopismo: Oceanological and Hydrobiological Studies
• Rocznik: 2009
• Tom: Vol. 38, No.1
• Strony: 27--43
• Opis fizyczny: bibliogr. 34 poz., wykr.

Twórcy

autor

Urbański J.A.

autor

Mazur A.

autor

Janas U.

• University of Gdansk, Institute of Oceanography Al. Pilsudskiego 46, 81-378 Gdynia, Poland,

Bibliografia

• Andréfouët S., Kramer P., Torres-Pulliza D., Joyce K., Hochberg E., et al., 2003, Multi-site evaluation of IKONOS data for classification of tropical coral reef environment, Remote Sensing of Environment, 88, 128-143
• Blaschke T., Burnett C., Pekkarinen A., 2004, New contextual approaches using image segmentation for object-based classification, (in:) S. de Jong & F., van der Meer (Ed.), Remote Sensing Image Analysis: Including the spatial domain, Dordrecht, Boston, London: Kluwer Academic Publishers
• Boström C., Bonsdorff E., 1997, Community structure and spatial variation of benthic invertebrates associated with Zostera marina (L.) beds in the northern Baltic Sea, Journal of Sea Research, 37, 153-166
• Boström C., Jackson E.L., Simenstand C.A., 2006, Seagrass landscapes and their effects on associated fauna: A review, Estuarine, Coastal and Shelf Science, 68, 383-403
• Congalton R., 1991, A review of assessing the accuracy of classification of remotely sensed data, Remote Sensing of Environment, 37, 35-46
• Constanza R., d'Arge R., deGroot R., Farber S., Grasso M., et al., 1997, The value of the world's ecosystem services and natural capital, Nature, 387, 253-260
• Cuevas-Jiménez A., Ardisson P., Condal A., 2002, Mapping of shallow coral reefs by colour aerial photography, International Journal of Remote Sensing, 23(18): 3697-3712
• Definiens Developer, 2007, User Guide (Munich: Definiens Imaging GmbH). Available online at: www.definiens.com (accessed 18 March 2008)
• Dekker A., Brando V., Anstee J., 2005, Retrospective seagrass change detection in a shallow coastal tidal Australian lake, Remote Sensing of Environment, 97, 415-433
• Water Frame Directive, 2000, Directive 2000/60/EC of The European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy, Official Journal of the European Communities, 327, 1-72
• eCognition, 2005, User Guide (Munich: Definiens Imaging GmbH). Available online at: www.definiens.com (accessed 15 March 2006)
• Elvidge C., Dietz J., Berkelmans R., Andréfouët S., Skirving W., Strong A., Tuttle B., 2004, Satellite observation of Kappel Islands (Great Barrier Reef) 2002 coral bleaching using IKONOS data, Coral Reefs, 23, 123-13
• Foden J., Brazier D.P., 2007, Angiosperms (seagrass) within the EU water framework directive: A UK perspective, Marine Pollution Bulletin, 55, 181-195
• Fornes A., Basterretxea G., Orfila A., Jordi A., Alvarez A., Tintore J., 2006, Mapping Posidonia oceanica from IKONOSISPRS, Journal of Photogrammetry & Remote Sensing, 60, 315-322
• Green K., Lopez C., 2007, Using object-oriented classification of ADS40 data to map the benthic habitats of the state of Texas, Photogrammetric Engineering & Remote Sensing, 72(6): 665-675
• Jackson E.L., Attrill M.J., Rowden A.A., Jones M.B., 2006, Seagrass complexity hierarchies: Influence on fish groups around the coast of Jersey (English Channel). Journal of Experimental Marine Biology and Ecology, 330, 38-54
• Kim M., Madden M., 2006, Determination of optimal scale parameters for alliance-level forest classification of multispectral IKONOS images. Proceedings of the 1st International Conference on Object-based Image Analysis (OBIA 2006)
• Krause-Jensen D., Greve T.M., Nielsen K., 2005, Eelgrass as a Bioindicator under the European Water Framework Directive, Water Resources Management, 19, 63-75
• Kruk-Dowgiałło L., Szaniawska A., 2008, Gulf of Gdansk and Puck Bay (in:) Schiewer U. (Ed.), Ecology of Baltic Coastal Waters, Ecological Studies, 197, 139-165
• Kutser T., Miller I., Jupp D., 2006, Mapping coral reef benthic substrates using hyperspectral space-borne images and spectral libraries, Estuarine, Coastal and Shelf Science, 70, 449-460
• Lathrop R., Montesano P., Haag S., 2006, A multi-scale segmentation approach to mapping seagrass habitats using airborne digital camera imagery, Photogrammetric Engineering &Remote Sensing, 72(6): 665-675
• Lucieer V.L., 2008, Object-oriented classification on sidescan sonar data for mapping benthic marine habitats, International Journal of Remote Sensing, 29(3): 905-921
• Lyzenga D.R., 1981, Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and Landsat data, International Journal of Remote Sensing, 2, 71-82
• Mumby P., Edwards A., 2002, Mapping marine environments with IKONOS imagery: enhanced spatial resolution can deliver greater thematic accuracy, Remote Sensing of Environment, 82, 248-25
• Pasqualini V., Pergent-Martini C., Pergent G., Agreil M., Skoufas G. et al., 2005, Use of SPOT 5 for mapping seagrasses: An application to Posidonia oceanica, Remote Sensing of Environment, 94, 39-45
• Pihl L., Baden S., Kautsky N., Rönnbäck P., Söderqvist T., et al., 2006, Shift in fish assemblage structure due to loss of seagrass Zostera marina habitats in Sweden, Estuarine, Coastal and Shelf Science, 67, 123-132
• Pihl L., Wennhage H., 2002, Structure and diversity of fish assemblages on rocky and soft bottom shores on the Swedish west coast, Journal of Fish Biology, 61, 148-166
• Pliński M., Jóźwiak T., 2004, The distribution of the vegetation on the Polish coast of the Baltic Sea in 1996-2000, Oceanological and Hydrobiological Studies, 33(2): 29-40
• Robbins B.D., Bell S.S., 1994, Seagrass landscapes: A terrestrial approach to the marine subtidal environment, Trends Ecology and Evolution, 9, 301-304
• Sagert S., Krause-Jensen D., Henriksen P., Rieling T., Shubert H., 2005, Integrated ecological assessment of Danish Baltic Sea coastal areas by means of phytoplankton and macrophytobenthos, Estuarine, Coastal and Shelf Science, 63(1-2): 109-118
• Sleeman J.C., Kendrick G.A., Boggs G.S., Hegge J.J., 2005, Measuring fragmentation of seagrass landscape: which indices are most appropriate for detecting change?, Marine and Freshwater Research, 56, 851-864
• Urbański J., Grusza G., Chlebus N., Kryla L., 2008, A GIS-based WFD oriented typology of shallow micro-tidal soft bottom using wave exposure and turbidity mapping, Estuarine, Coastal and Shelf Science, 78, 27-37
• VirtualDub Editor 1.7.6 software. Available online at: http://www.esoft.web.id/audio-video/freedownload-virtualdub-1.7.6.html (accessed 18 March 2008)
• Ward L., Kemp W., Boynton W., 1984, Influence of waves and seagrass communities on suspended particulates in an estuarine embayment, Marine Geology, 59(1-4): 85-103