Object-based image analysis of remote sensing data;objektno usmerjena analiza podatkov daljinskega zaznavanja

Geodetski Vestnik

Volumn 55, Issue 4, 2011, Pages 665-688

  Veljanovski, Tatjana ^a,b   Kanjir, Urša ^a   Oštir, Krištof ^a,b  

^a ANTON MELIK GEOGRAPHICAL INSTITUTE   (Slovenia)

^b Center of Excellence SPACE SI   (Slovenia)

Author keywords

Object based classification; Object based image analysis; Remote sensing; Segmentation; Semantic classification

Indexed keywords

IMAGE ANALYSIS; IMAGE CLASSIFICATION; IMAGE RESOLUTION; PIXEL; REMOTE SENSING; SATELLITE DATA; SEGMENTATION; SPATIAL RESOLUTION;

EID: 84455174849     PISSN: 03510271     EISSN: None     Source Type: Journal    
DOI: 10.15292/geodetski-vestnik.2011.04.665-688     Document Type: Article

References (75)

1. Addink, E.A., Van Coillie, F.M.B. (eds.) (2010). GEOBIA2010: Geographic object-based image analysis, Ghent, Belgium, 29. June - 2. July 2010. ISPRS Vol. No. XXXVIII-4/C7, Archives ISSN No 1682-1777. http://geobia.ugent.be/proceedings/html/papers.html (April 2011).
2. Albertz, J. (2001). Einführung in die Fernerkundung. Grundlagen der Interpretation von Luft- und Satellitenbildern.WissenschaftlicheBuchgesellschat, Darmstalt.
3. Baatz, M., Schäpe, A. (2000). Multi-resolution segmentation - an optimization approach for high quality multi-scale segmentation. In: Strobl, J., et al. (eds.), Angewandte Geographische Informations verarbeitung XII, Beiträgezum AGIT Symposium Salsburg 2000, Karlruhe, Herbert Wichmann Verlag, 12-23.
4. Beaudoin, A., Le Toan, T., Lopes, A., Laur, H. (1990). Forest and land use segmentation of SAR images using backscatter and textural information. In:10th Annual International Geoscience and Remote Sensing Symposium, College Park, MD, IEEE 90 CH2825-50, IEEE, Piscataway, NJ, 871-874.
5. Bitelli, G., Camassi, R., Gusella, R., Mongol, A. (2004). Image change detection on urban area: The earthquake case. In: Proceedings of the ISPRS2004 annual conference, Istanbul, Turkey, 19.-23. July 2004.
6. Blaschke, T. (2005). A framework for change detection based on image object. In: Erasmi, S., Cyffka, B., Kappas, M. (eds.) Göttinger Geographische Abhandlungen 113, 1-9.
7. Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 2-16.
8. Blaschke, T., Lang, S., Hay G.J. (eds.) (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications (Lecture notes in geo-information and cartography). Springer.
9. Blaschke, T., Strobl, J. (2001). What's wrong with pixels? Some recent developments interfacing remote sensing and GIS. GIS-Zeitschrift für Geoinformations systeme 14 (6), 12-17.
10. Campbell, J.B. (1996). Introduction to remote sensing. 2. edition. New York, Guilford Press.
11. Castilla, G., Hay, G.J. (2008). Geographic object-based image analysis (GEOBIA). In: Blaschke, T., Lang, S., Hay, G.J. (eds.), Object-based image analysis - spatial concepts for knowledge-driven remote sensing applications. Springer-Verlag, Berlin, 91-111.
12. Chandra, M., Moreira, A., Keydel, W. (2005). Amper: Network on applied multi-parameter environmental remote sensing. An EU sponsored research and training network. In: Proceedings of the IGARSS 2005 Symposium. Seul, Korea. 25.-29. July 2005.
13. Chunyang, H., Li, J., Zhang, J., Pan, Y., Chen, Y.H. (2005). Dynamic monitor on urban expansion based on an object-oriented approach. In: Proceedings of the IGARSS 2005 Symposium. Seul, Korea. 25.-29. July 2005.
14. Congalton, R.G., Green, K. (1999). Assessing the accuracy of remotely sensed data: principles and practices. Lewis Publisher.
15. Cracknell, A.P. (1998). Synergy in remote sensing - What's in a pixel? International Journal of Remote Sensing 19 (11), 2025-2047.
16. Crase, B., Hempel, C. (2005). Object based land cover mapping for groote eylandt: a tool for reconnaissance and land based surveys. In: Proceedings of NARGIS 2005 - Applications in Tropical Spatial Science. Charles Darwin University, Darwin, NT, Australia. 4.-7. July 2005.
17. Definiens (2011). Definiens Solutions. http://www.definiens.com/, http://community.definiens.com/home.html, http://www.ecognition.com/learn/resource-center/show-more?type=Scientific%20Paper (April 2011).
18. Durić, N. (in press). Object-based classification for extracting tree species and detection of japanese knotweed. Graduation thesis. Ljubljana: Faculty of Civil and Geodetic Engineering, Department of Geodetic Engineering.
19. ENVI (2004). ENVI User's guide.http://aviris.gl.fcen.uba.ar/Curso_SR/biblio_sr/ENVI_userguid.pdf (April 2011).
20. Gao, Y., Kerle, N., Mas, J. F., Navarrete, A., Niemeyer, I. (2007). Optimized image segmentation and its effect on classification accuracy. Poster session on 5th international Symposium on Spatial Data Quality, Enschede, The Netherlands.
21. GEOBIA Wiki (2011). GEO Object Based Image Analysis Wikipedia. University of Calgary. http://wiki.ucalgary.ca/page/GEOBIA (April 2011).
22. Gonzales, R.C, Woods, R.E. (2002). Digital image processing, 2nd edition. Prentice Hall, Inc.
23. Grenzdoerfer, G. (2005). Land use change in Rostock, Germany since the reunification - a combined approach with satellite data and high resolution aerial images. In: Proceedings of the ISPRSWG VII/1 Human Settlements and Impact Analysis, 3rd International Symposium Remote Sensing and Data Fusion Over Urban Areas (URBAN 2005) and 5th International Symposium Remote Sensing of Urban Areas (URS 2005). Tempe, AZ, USA. 14.-16. March 2005.
24. Grigillo, D., Kosmatin Fras, M. (2011). Classification based building detection from GeoEye-1 images. In: Stilla, U. (ed.), JURSE 2011: Proceedings of IEEE-GRSS/ISPRS Joint Urban Remote Sensing Event, TUM, Munich, Germany, 11.-13. April 2011, 381-384. http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=05764799 (April 2011).
25. Grigillo, D., Kosmatin Fras, M., Petrovič, D. (2011). Automatic extraction and building change detection from digital surface model and multispectral orthophoto. Geodetski vestnik 55-1, 28-45.
26. GTS (2005). Geografski terminološki slovar. Ljubljana: Založba ZRC, ZRC SAZU.
27. Hall, F.G., Townshend, J.R., Engman, E.T. (1995). Status of remote sensing algorithms for estimation of land surface state parameters. Remote Sensing of Environment. 51, 138-156.
28. Haralick, R.M., Shapiro, L. (1985). Survey: image segmentation techniques. Comput. Vis. Graph. Image Process. 1985, 29, 100-132.
29. Hay, G.J., Blaschke, T., Marceau, D.J., Bouchard, A. (2003). A comparison of three image-object methods for the multi-scale analysis of landscape structure. ISPRS Journal of Photogrammetry & Remote Sensing, 57, 327-345.
30. Hay, G.J., Castilla, G. (2006). Object-based image analysis: strengths, weaknesses, opportunities and threats (SWOT). In: International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. No. XXXVI-4/C42, Salzburg.
31. Hay, G.J., Castilla, G., Wulder, M.A., Ruiz, J.R. (2005). An automated object-based approach for the multi-scale image segmentation of forest scenes. International Journal of Applied Earth Observation and Geoinformation, 7, 339-359.
32. Heremans, R., Willekens, A., Borghys, D., Verbeeck, B., Valckenborgh, J., Perneel, C. (2005). Automatic detection of flooded areas on ENVISAT/ASAR images using an object-oriented classification technique and an active contour algorithm. Proceedings of the 31th International Symposium on Remote Sensing of the Environment. St. Petersburg, Russia. 20.-24. June 2005.
33. Horowitz, H.M., Lewis, J.T., Pentland, A.P. (1975). Estimating proportions of objects from multispectral scanner data, Final Report, NAS9 Contract NAS9-14123, NASA CR 141826.
34. Johansen, K., Tiede, D., Blaschke, T., Arroyo, L.A., Phinn, S. (2011). Automatic geographic object based mapping of streambed and riparian zone extent from LiDAR data in a temperate rural urban environment, Australia. Remote Sens. 2011, 3, 1139-1156.
35. Kamagata, N., Akamatsu, Y., Mori, M., Qing Li, Y., Hoshinoy, Y., Hara, K. (2005). Comparison of pixel-based and object-based classifications of high resolution satellite data in urban fringe areas. In: Proceedings of the 26th Asian Conference on Remote Sensing. Hanoi, Vietnam. 7.-11. November 2005.
36. Kanjir, U. (2009). Object oriented land use classification from remote sensing data. Graduation thesis. Ljubljana: Faculty of Civil and Geodetic Engineering, Department of Geodetic Engineering.
37. Kanjir, U., Veljanovski, T., Marsetič, A., Oštir, K. (2010). Application of object based approach to heterogeneous land cover/use. In: Addink, E.A., Van Coillie, F.M.B. (eds.) GEOBIA 2010: Geographic Object-Based Image Analysis, Ghent, Belgium, 29.6.-2.7. 2010. http://geobia.ugent.be/proceedings/html/papers.html (April 2011).
38. Kanjir, U., Veljanovski, T., Oštir, K. (2011a). Change detection of urban areas - the Ljubljana, Slovenia case study. In: JURSE 2011: Proceedings of IEEE-GRSS/ISPRS Joint Urban Remote Sensing Event, TUM, Munich, Germany. 11.-13. April 2011.
39. Kanjir, U., Veljanovski, T., Oštir, K. (2011b). Multi level segmentation of soil sealing in urban areas. The 32nd Asian Conference on Remote Sensing, Taipei, Taiwan, 3.-7.10.2011.
40. Ketting, R.L., Landgrebe, D.A. (1976). Classification of spectral image data by extraction and classification of homogeneous objects, IEEE Transactions Geosci. Electronics 14, 19-25.
41. Kobler, A., Džeroski, S., Kermatisoglou, I. (2006). Habitat mapping using machine learning-extended kernel-based reclassification of an Ikonos satellite image. Ecol. model., 2006, Vol. 191, No. 1, 83-95.
42. Kokalj, Z ̌.,Os ̌tir, K. (2006). Ugotavljanje pokrovnosti Slovenije iz satelitskih posnetkov Landsat. Geografski vestnik, 2006, Vol. 78, No. 2.
43. Kokalj, Ž.,Os ̌tir, K. (2007). Land cover mapping using Landsat satellite image classification in the classical Karst - Kras region. Acta carsologica 36-3, 433-440.
44. Kouchi, K., Yamazaki, F. (2005). Damage detection based on object-based segmentation and classification from high-resolution satellite images for the 2003 Boumerdes, Algeria earthquake. In: Proceedings of the 26th Asian Conference on Remote Sensing. Hanoi, Vietnam. 7.-11. November 2005.
45. Laliberte, A., Rango, A., Fredrickson, E. (2005). Classification of arid rangelands using an object-oriented and multi-scale approach with QuickBird imagery. In: Proceedings of the ASPRS 2005 Annual Conference. Baltimore, MD, USA. 7.-11. March 2005.
46. Lang, S., Blaschke, T. (2003). Hierarchical object representation - comparative multi-scale mapping of anthropogenic and natural features. ISPRS Archives 34, Part 3/W8: 17-19.
47. Lang, S., Blaschke, T., Schöpfer, E. (2006). 1st International Conference on Object-based Image Analysis. http://www.isprs.org/proceedings/XXXVI/4-C42/papers.htm (April 2011).
48. Liang, S. (2004). Quantitative remote sensing of landsurfaces. New York: Willey-Interscience.
49. Lillesand, T.M., Kiefer, R.W., Chipman, J.W. (2004). Remote sensing and image interpretation. 5th edition.New York, John Wiley and Sons, Inc.
50. Manakos, I., Schneider, T., Ammer, U. (2000). A comparison between the ISODATA and the eCognition classification methods on basis of field data. In: ISPRS, Vol. XXXIII, Amsterdam, 2000.
51. Mason, D.C., Corr, D.G., Cross, A., Hogg, D.C., Lawrence, M., Petrou, D.H., Tailor, A.M. (1988). The use of digital map data in the segmentation and classification of remotely sensed images, Int. J. Geographic Inf. Systems 2, 195-215.
52. Moeller, M. (2005). Remote sensing for the monitoring of urban growth patterns. In: Proceedings of the ISPRSWG VII/1 Human Settlements and Impact Analysis, 3rd International Symposium Remote Sensing and Data Fusion Over Urban Areas (URBAN 2005) and 5th International Symposium Remote Sensing of Urban Areas (URS 2005). Tempe, AZ, USA. 14.-16. March 2005.
53. Navulur, K. (2007). Multi-spectral image analysis using the object oriented paradigm. CRC Press, Taylor & Francis Group.
54. Neubert, M, Herold, H., Meinel, G. (2008). Assessing image segmentation quality - concepts, methods and application. In: Blaschke, T., Lang, S., Hay G.J (Eds.): Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications (Lecture notes in geoinformation and cartography): 785-803.
55. Niemeyer, I., Canty, M.J. (2001). Knowledge-based interpretation of satellite data by object-based and multi-scale image analysis in the context of nuclear verification. http://www.geomonitoring.tu-freiberg.de/publications/igarss01nie.pdf (April 2011).
56. Nussbaum, S., Menz, G. (2008). Object-based image analysis and treaty verification: new approaches in remote sensing - applied to nuclear facilities in Iran. Springer.
57. Oštir, K. (2006). Daljinsko zaznavanje (Remote Sensing). Ljubljana: Založba ZRC.
58. Pal, R., Pal, K. (1993). A review on image segmentation techniques. Pattern Recogn. 1993, 26, 1277-1294.
59. Pena-Barragán, J.M., Ngugi, M.K., Plant, R.E., Six, J. (2011). Object-based crop identification using multiple vegetation indices, textural features and crop phenology. Remote Sensing of Environment, 155-6: 1301-1316.
60. Quegan, S., Caves, R.G., Grover, K.D., White, R.G. (1992). Segmentation and change detection in ERS-1 images over East Anglia, In: First ERS-1 Symposium: Early Results, ESA, Cannes, France, 617-622.
61. Radoux, J., Defourny, P. (2008). Quality assessment of segmentation results devoted to object-based classification. In: Blaschke, T., Lang, S., Hay G.J. (eds.): Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications (Lecture notes in geoinformation and cartography): 257-273.
62. Richards, J.A., Jia, X. (1999). Remote sensing digital image analysis. An introduction. Springer Verlag, NY.
63. Schiewe, J. (2002). Segmentation of high-resolution remotely sensed data: concepts, applications and problems. In: Joint ISPRS Commission IV Symposium: Geospatial Theory, Processing and Applications. 9.-12. July 2002.
64. Schiewe, J., Gähler, M. (2008). Modelling uncertainty in high resolution remotely sensed scenes using a fuzzy logic approach. In: Blaschke, T., Lang, S., Hay G.J (Eds.): Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications (Lecture notes in geoinformation and cartography), 769-785.
65. Schiewe, J., Tufte, L., Ehlers, M. (2001). Potential and problems of multi-scale segmentation methods in remote sensing.Geographische Informations systeme 6, 34-39.
66. Schowengerdt, R.A. (2007). Remote sensing. Models and methods for image processing. 3rd edition. Academic Press, Elsevier Inc.
67. Šabić, D., Lojović, E.H., Tretjak, A. (2000).Ocenjena sprememba pokrovnosti tal v statističnem GISu pokrovnosti in rabe tal Slovenije: junij 1993 - junij 1997. In: Hladnik, D. et al., GIS v Sloveniji 1999-2000, Ljubljana 2000, Založba ZRC, 201-207.
68. Šumrada, R. (2005). Strukture podatkov in prostorske analize. Ljubljana, Faculty of Civil and Geodetic Engineering.
69. Veljanovski, T. (2008). The problem of false (non-intrinsic) changes in pixel-based change detection on Landsat imagery. Geodetski vestnik 2008, Vol. 52, No. 3, 457-474.
70. Veljanovski, T., Lamovec, P., Pehani, P., Oštir, K. (2011a). Comparison of three techniques for detection of flooded areas on ENVISAT and RADARSAT-2 satellite images. In: Geoinformation for disaster management: Gi4DM 2011, 3.-8. May 2011, Antalya, Turkey.
71. Veljanovski, T., Pehani, P., Kokalj, Ž., Oš;tir, K. (2011b). Zaznavanje poplav s časovno vrsto radarskih satelitskih posnetkov ENVISAT in RADARSAT-2. In: Zorn, M., Komac, B., Ciglič, R., Pavšek, M. (Eds.): Neodgovorna odgovornost, (Naravne nesreče, 2). Ljubljana: ZaložbaZRC, 2011, pp. 81-89. http://giam.zrc-sazu.si/sites/default/files/Naravne-nesrece-02.pdf (April 2011).
72. Whiteside, T. (2005). A multi-scale object-oriented approach to the classification of multi-sensor imagery for mapping land cover in the top end. In: Proceedings of NARGIS 2005 - Applications in Tropical Spatial Science. Charles Darwin University, Darwin, NT, Australia. 4.-7. July 2005.
73. Whiteside, T., Ahmad, W. (2005). A comparison of object-oriented and pixel-based classification methods for mapping land cover in northern Australia. Proceedings 2005. Melbourne: Spatial Sciences Institute.
74. Willhauck, G., Schneider, T., De Kok, R., Ammer, U. (2000). Comparison of object oriented classification techniques and standard image analysis for the use ofchange detection between SPOT multispectral satellite images and aerial photos. In: ISPRS, Vol. XXXIII, Amsterdam, 2000.
75. Yan, G., Mas, J.F., Maathuis, B.H.P., Xiangmin, Z., Van Dijk, P.M. (2006). Comparison of pixel-based and object-oriented image classification approaches-a case study in a coal fire area, Wuda, Inner Mongolia, China. International Journal of Remote Sensing. Vol.27, No.18., 4039-4055.