Visualizing Scale-Domain Manifolds: A Multiscale Geo-Object-Based Approach

Scale Issues in Remote Sensing

Volumn 9781118305041, Issue , 2014, Pages 139-169

  Hay, Geoffrey J ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

Blob feature detection; Geographic object based hierarchies; Scale space (SS); Scale domain manifolds

Indexed keywords

FEATURE EXTRACTION; REMOTE SENSING; SPACE OPTICS;

BLOB FEATURE DETECTION; FEATURES DETECTIONS; GEOGRAPHIC OBJECT-BASED HIERARCHY; GEOGRAPHIC OBJECTS; OBJECT BASED; OBJECTS-BASED; SCALE DOMAINS; SCALE SPACE; SCALE SPACES; SCALE-DOMAIN MANIFOLD;

OBJECT DETECTION;

EID: 84926405452     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781118801628.ch08     Document Type: Chapter

References (92)

1. Ahl, V., and Allen, T. F. H. 1996. Hierarchy Theory: A Vision, Vocabulary, and Epistemology . New York: Columbia University Press.
2. Allen, T. F. H., and Starr, T. B. 1982. Hierarchy Perspective for Ecological Complexity . Chicago: University of Chicago Press.
3. Baatz, M., and Schäpe, A. 2000. Multiresolution segmentation: An optimization approach for high quality multiscale image segmentation. In J. Strobl and T. Blaschke (Eds.), Angewandte Geogr. Informationsverarbeitung XII. Heidelberg: Wichmann, pp. 12-23.
4. Beucher, S., and Lantuéjoul, C. 1979. Use of watersheds in contour detection. Int. Workshop on Image Processing, Real-time Edge and Motion Detection/Estimation, Rennes, France, pp. 17-21, September, CCETT/IRISA (Centre commun d'études de télédiffusion et télécommunications/ Institut de recherche en informatique et systèmes aléatoires), Report No. 132, 2.1 -2.12.
5. Biederman, I. 1987. Recognition-by-components: A theory of human image understanding. Psychological Review 94(2):115- 147.
6. Blaschke, T. 2010. Object based image analysis for remote sensing. ISPRS International Journal of Photogrammetry and Remote Sensing 65(1): 2-16.
7. Bogaert, J. 2003. Lack of agreement on fragmentation metrics blurs correspondence between fragmentation experiments and predicted effects. Conservation Ecology 7(1):r6; available at: http://www.consercol.org/vol7/iss1/resp6.
8. Bouchard, A., and Domon, G. 1997. The transformation of the natural landscapes of the Haut-Saint-Laurent (Québec) and its implication on future resources management. Landscape and Urban Planning 37(1- 2):99-107.
9. Burnett, C., and Blaschke, T. 2003. A multi-scale segmentation/object relationship modelling methodology for landscape analysis. Ecological Modelling 168(3):233 -249.
10. Canny, J. 1986. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6): 679-697.
11. Castilla, G. 2003. Object-oriented Analysis of Remote Sensing Images for Land Cover Mapping: Conceptual Foundations and a Segmentation Method to Derive a Baseline Partition for Classi fication. Ph.D. Dissertation, Polytechnic University of Madrid; http://www.montes.upm.es/Servicios/biblioteca/tesis/GCastillaTD_Montes.pdf.
12. Castilla, G., and Hay, G. J. 2008. Image-objects and geo-objects. In T. Blaschke, S. Lang, and G. J. Hay (Eds.), Object-Based Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Berlin: Springer, pp. 91-110.
13. Castilla, G., Hay, G. J., and Ruiz, J. R. 2008. Size-constrained Region Merging (SCRM): An automated delineation tool for assisted photointerpretation. Photogrammetric Engineering & Remote Sensing 74(4): 409-419.
14. Chen, G., Hay, G. J., Carvalho, L. M. T., and Wulder, M. 2012. Object Based Change Detection. International Journal of Remote Sensing 33(14): 4434-4457.
15. Chen, G., Hay, G. J., and St-Onge, B. 2011. A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada. International Journal of Applied Earth Observation and Geoinformation 15: 28-37.
16. Cousins, S. H. 1993. Hierarchy in ecology: Its relevance to landscape ecology and geographic information systems. In R. H. Young, D. R. Green, and S. H. Cousins (Eds.), Landscape Ecology and GIS. New York: Taylor & Francis, pp. 75-86.
17. Daubechies, I. 1988. Orthonormal bases of compactly supported wavelets. Communications on Pure and Applied Mathematics 41: 906-966.
18. Dey, V., Zhang, Y., and Zhong, M. 2010. A review on image segmentation techniques with remote sensing perspective. ISPRS TC VII Symposium Vienna, Austria, July 5, Vol. XXXVIII, Part 7A, pp. 31-42.
19. Doxani, G., Karantzalos, K., and Tsakiri-Strati, A. 2012. Monitoring urban changes based on scale space filtering and object-oriented classification. International Journal of Applied Earth Observations and Geoinformation 15: 38-48.
20. Drăguţ , L., Tiede, D., and Levick, S. R. 2010. ESP: A tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data. International Journal of Geographical Information Science 24(6): 859-871.
21. Foody, G. 1999. Image classification with a neural network: From completely-crisp to fullyfuzzy situations. In P. M. Atkinson and N. J. Tate (Eds.), Advances in Remote Sensing and GIS Analysis. Chichester: Wiley, pp. 17-37.
22. Forman, R. T. T. 1995. Land Mosaics: The Ecology of Landscapes and Regions. Cambridge, UK: Cambridge University Press.
23. Gibson, C. C., Ostrom, E., and Ahn, T. K. 2000. The concept of scale and the human dimensions of global change: A survey. Ecological Economics 32: 217-239.
24. Graham, I. 2001. Object-Oriented Methods. Principles and Practices, 3rd ed. Reading, MA: Addison-Wesley.
25. Hall, O., Hay, G. J., Bouchard, A., and Marceau, D. J. 2004. Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation. Landscape Ecology 19(1): 59-76.
26. Haralick, R. M., Sternberg, S. R., and Zhuang, X. 1987. Image analysis using mathematical morphology. IEEE Transactions on Pattern Analysis and Machine Intelligence 9(4): 532-550.
27. Haury, L. R., McGowan, J. A., and Wiebe, P. H. 1978. Patters and processes in the time-space scales of plankton distributons. In J. H. Steele (Ed.), Spatial Pattern in Plankton Communities. New York: Plenum, pp. 277-327.
28. Hay, G. J., and Blaschke, T. 2010. Forward: Special issue on geographic object-based image analysis (GEOBIA). Photogrammetric Engineering and Remote Sensing 76(2): 121-122.
29. Hay, G. J., Blaschke, T., Marceau, D. J., and Bouchard, A. 2003. A comparison of three imageobject methods for the multiscale analysis of landscape structure. ISPRS Journal of Photogrammetry and Remote Sensing 57(5-6):327-345.
30. Hay, G. J., and Castilla, G. 2008. Geographic Object-Based Image Analysis (GEOBIA): A new name for a new discipline. In T. Blaschke, S. Lang, and G. J. Hay (Eds.), Object-Based Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Berlin: Springer, pp. 75-89.
31. Hay, G. J., Castilla, G., Wulder, M. A., and Ruiz, J. R. 2005. An automated object-based approach for the multiscale image segmentation of forest scenes. International Journal of Applied Earth Observation and Geoinformation 7: 339-359.
32. Hay, G. J., Dube, P., Bouchard, A., and Marceau, D. J. 2002a.A scale-space primer for exploring and quantifying complex landscapes. Ecological Modelling 153(1-2):27-49.
33. Hay, G. J., and Marceau, D. J. 1998. Are image-objects the key for upscaling remotely sensed data? Proceedings of Modelling of Complex Systems, July 12-17, New Orleans, pp. 88-92.
34. Hay, G. J., and Marceau, D. J. 2004. Multiscale Object-Specific Analysis (MOSA): An integrative approach for multiscale landscape analysis. In S. M. de Jong and F. D. van der Meer (Eds.), Remote Sensing Image Analysis: Including the Spatial Domain. Book series: Remote Sensing and Digital Image Processing, Volume 5. Chapter 3. Dordrecht: Kluwer Academic.
35. Hay, G. J., Marceau, D. J., and Bouchard, A. 2002b. Modelling multiscale landscape structure within a hierarchical scale-space framework. International Archives of Photogrammetry and Remote Sensing 34(4): 532-536.
36. Hay, G. J.,Marceau, D. J.,Dubé, P., andBouchard,A. 2001.Amultiscale framework for landscape analysis: Object-specific analysis and upscaling. Landscape Ecology 16(6): 471-490.
37. Hay, G. J., and Niemann, K. O. 1994. Visualizing 3-D texture: A three dimensional structural approach to model forest texture. Canadian Journal of Remote Sensing 20(2): 90-101.
38. Hay, G. J., Niemann, K. O., and Goodenough, D. G. 1997. Spatial thresholds, image-objects and upscaling: A multi-scale evaluation. Remote Sensing of Environment 62(1): 1-19.
39. Hay, G. J., Niemann, K. O., and McLean, G. 1996. An object-specific image-texture analysis of H-resolution forest imagery. Remote Sensing of Environment 55(2): 108-122.
40. Holling, C. S. 1992. Cross-scale morphology, geometry, and dynamics of ecosystems. Ecological Monographs 62(4): 447-502.
41. Jähne, B. 1999. A multiresolution signal representation. In B. Jähne, H. Haußecker, and P. Geißler (Eds.), Handbook on Computer Vision and Applications. Boston: Academic, pp. 67-90.
42. Kay, J. 1991. A Non-equilibrium thermodynamic framework for discussing ecosystem integrity. Environmental Management 15(4): 483-495.
43. Kay, J. J., and Regier, H. 2000. Uncertainty, complexity, and ecological integrity: Insights from an ecosystem approach. In P. Crabbe, A. Holland, L. Ryszkowski, and L. Westra (Eds.), Implementing Ecological Integrity: Restoring Regional and Global Environmental and Human Health. Dordrecht: Kluwer, NATO Science Series, Environmental Security, pp. 121-156.
44. Klinger, A. 1972. Patterns and search statistics. In J. Rustagi (Ed.), Optimizing Methods in Statistics. New York: Academic Press, pp. 303-339.
45. Klinger, A., and Dyer, C. R. 1976. Experiments in picture representation using regular decomposition. Comp. Graphics Image Process 5:68.
46. Levin, S. A. 1999. Fragile Dominions: Complexity and the Commons. Reading, MA: Perseus Books.
47. Li, H., and Wu, J. 2004. Use and misuse of landscape indices. Landscape Ecology 19: 389-399.
48. Lindeberg, T. 1993. Detecting salient blob-like image structure and their scales with a scalespace primal sketch: A method for focus of attention. International Journal of Computer Vision 11(3):283-318
49. Lindeberg, T. 1994. Scale-Space Theory in Computer Vision. Dordrecht: Kluwer Academic.
50. Mandelbrot, B. 1967. The fractal geometry of nature. Science 156: 636-642.
51. Marceau, D. J. 1999. The scale issue in the social and natural sciences. Canadian Journal of Remote Sensing 25(4):347 -356.
52. Marceau, D. J., and Hay, G. J. 1999. Contributions of remote sensing to the scale issue. Canadian Journal of Remote Sensing 25(4):357 -366.
53. Marceau, D. J., Howarth, P. J., and Gratton, D. J. 1994. Remote sensing and the measurement of geographical entities in a forested environment. Part 1: The scale and spatial aggregation problem. Remote Sensing of Environment 49(2): 93-104.
54. Meentemeyer, V. 1989. Geographical perspectives of space, time, and scale. Landscape Ecology 3: 163-173.
55. Meilleur, A., Bouchard, A., and Bergeron, Y. 1994. The relation between geomorphology and forest community types of the Haut-Saint-Laurent, Quebec. Vegetatio 111:173- 192.
56. Nicolis, G., and Prigogine, I. 1989. Exploring Complexity: An Introduction . New York: W H Freeman.
57. O'Neill, R. V., and King, A. W. 1998. Homage to St. Michael; Or, why are there so many books on scale? In Ecological Scale Theory and Applications . New York: Columbia University Press, pp. 3- 15.
58. Peterson, G. 2000. Scaling ecological dynamics: Self-organization, hierarchical structure, and ecological resilience. Climate Change 44(3): 291-309.
59. Powers, R., Hay, G. J., and Chen, G. 2012. How wetland type and area differ through scale: A case study of Alberta 's Boreal Plains. Remote Sensing of Environment 117: 135-145.
60. Quattrochi, D. A., and Goodchild, M. F. (Eds.) 1996. Scale in Remote Sensing and GIS . Boca Raton, FL: Lewis Publishers.
61. Reynolds, J. R., and Wu, J. 1999. Do landscape structural and functional units exist? In J. D. Tenhunen and P. Kabat (Eds.), Integrating Hydrology, Ecosystem Dynamics and Biogeochemistry in Complex Landscapes. New York: Wiley, pp. 275-298.
62. Robert, C. P. 2001. The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation. New York: Springer.
63. Rosin, P. L. 1992. Representing curves at their natural scales. Pattern Recognition 25 (11):1315-1325.
64. Rowe, J. S. 2001. Transcending this poor Earth-á la Ken Wilber. Trumpeter 17:1; available at http://trumpeter.athabascau.ca/index.php/trumpet/article/view/138/161, last accessed October 20, 2013.
65. Settle, J. J., and Drake, N. A. 1993. Linear mixing and the estimation of ground cover proportions. International Journal of Remote Sensing 14(6): 1159-1177.
66. Simon, H. A. 1962. The architecture of complexity. Proceedings of the American Philosophical Society 106: 467-482.
67. Simon, H. A. 1973. The Organization of Complex Systems. In H. H. Pattee (Ed.), Hierarchy Theory: The Challenge of Complex Systems. New York: George Braziller, pp. 1-27.
68. Starck, J.-L., Murtagh, F., and Bijaoui, A. 1998. Image Processing and Data Analysis: The Multiscale Approach, Cambridge, UK: Cambridge University Press, 315 pp.
69. Steiniger, S., and Hay, G. J. 2009. Free and open source geographic information tools for landscape ecology: A review. Ecological Informatics 4(4): 183-195.
70. Swihart, R. K., DunningJr., G. B., and Waser, P. M. 2002. Grey matters in ecology: Dynamics of pattern, process, and scientific progress. Bulletin of the Ecological Society of America 83: 149-155.
71. Syed, A. H., Saber, E., and Messinger, D. 2011. Scale-space representation of remote sensing images using an object-oriented approach. SPIE 8053(1):805308.
72. Syed, A. H., Saber, E., and Messinger, D. 2012. Encoding of topological information in multiscale remotely sensed data: Applications to segmentation and object based image analysis. Proceedings of the 4th GEOBIA, May 7-9, Rio de Janeiro, Brazil, pp. 102-107.
73. Ter Haar Romeny, B. M., and Florack, L. M. J. 2000. Front-end vision, a multiscale geometry engine. Proc. First IEEE International Workshop on Biologically Motivated Computer Vision (BMCV2000), May 15-17, Seoul, Korea. In Lecture Notes in Computer Science, Vol. 1811. Heidelberg: Springer, pp. 297-307.
74. Tzotsos, A., Karantzalos, K., and Argialas, D. 2011. Object-based image analysis through nonlinear scale-space filtering. ISPRS Journal of Photogrammetry and Remote Sensing 66: 2-16.
75. Urban, D. L., O'Neill, R. V., and Shugart, Jr.H. H. 1987. Landscape ecology. A hierarchical perspective can help scientists understand spatial patterns. Bioscience 37(2): 119-127.
76. Waldrop, M. M. 1992. Complexity. The Emerging Science at the Edge of Order and Chaos. New York: Simon and Schuster.
77. Wang, F. 1990. Improving remote sensing image analysis through fuzzy information representation. Photogrammetric Engineering and Remote Sensing 56(8): 1163-1169.
78. Watt, A. S. 1947. Pattern and process in the plant community. Journal of Ecology 35: 1-22.
79. Weickert, J., Ishikawa, S., and Imiya, A. 1997. On the history of Gaussian scale-space axiomatics. In J. Sporring, M. Nielsen, L. Florack, and P. Johansen (Eds.), Gaussian Scale-Space Theory. Dordrecht: Kluwer, pp. 45-59.
80. Wessman, C. A. 1992. Spatial scales and global change: Bridging the gap from plots to GCM grid cells. Annual Review of Ecological Systems 23: 175-200.
81. Wheatley, M., and Johnson, C. 2009. Factors limiting our understanding of ecological scale. Ecological Complexity 6: 150-159.
82. Whittaker, R. H. 1953. A consideration of climax theory: The climax as a population and pattern. Ecol. Monogr. 23: 41-78.
83. Wiens, J. A. 1989. Spatial scaling in ecology. Functional Ecology 3(4): 385-397.
84. Woodcock, C. E., and Strahler, A. H. 1987. The factor of scale in remote sensing. Remote Sensing of Environment 21(3): 311-332.
85. Wu, J. 2007. Scale and scaling:Across-disciplinary perspective. In J.WuandR.Hobbs (Eds.), Key Topics in Landscape Ecology. Cambridge, UK: Cambridge University Press, pp. 115-142.
86. Wu, H., and Li, Z.-H. 2009. Scale issues in remote sensing: A review on analysis, processing and modeling. Sensors 9: 1768-1793.
87. Wu, J. 1999. Hierarchy and scaling: Extrapolating information along a scaling ladder. Canadian Journal of Remote Sensing 25: 367-380.
88. Wu, J., and Hobbs, R. 2002. Key issues and research priorities in landscape ecology: An idiosyncratic synthesis. Landscape Ecology 17: 355-365.
89. Wu, J., and Li, H. 2005. Concepts of scale and scaling. In J. Wu, K. B. Jones, H. Li, and O. L. Loucks (Eds.), Scaling and Uncertainty Analysis in Ecology. NewYork: Columbia University Press.
90. Wu, J., David, J. L., and Jenerette, G. D. 2003. Linking land use change with ecosystem processes: A hierarchical patch dynamics model. In S. Guhathakurta (Ed.), Integrated Land Use and Environmental Models. New York: Springer, pp. 99-119.
91. Wu, J., and Marceau, D. 2002. Modelling complex ecological systems: An introduction. Ecological Modelling 153(1-2):1-6.
92. Wu, J., and Loucks, O. L. 1995. From balance of nature to hierarchical patch dynamics: A paradigm shift in ecology. Quarterly Review of Biology 70: 439-466.