Object-based image analysis and treaty verification: New approaches in remote sensing - Applied to nuclear facilities in Iran

Object-Based Image Analysis and Treaty Verification: New Approaches in Remote Sensing - Applied to Nuclear Facilities in Iran

Volumn , Issue , 2008, Pages 1-170

  Nussbaum, Sven ^a   Menz, Gunter ^b  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

^b UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84892314871     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-4020-6961-1     Document Type: Book

References (152)

1. Abmayer, W. (1994). Einfuhrung in die digitale Bildverarbeitung. Teubner, Stuttgart.
2. Aiazzi, B., Alparone, L., Baronti, S., and Garzelli, A. (2002). Context-driven fusion of high spatial and spectral resolution data based on oversampling multiresolution analysis. IEEE Transactions on Geoscience and Remote Sensing, 40(10), 2300-2312.
3. Albertz, J. (2001). Einfuhrung in die Fernerkundung. Grundlagen der Interpretation von Luft-und Satellitenbildern. Wissenschaftliche Buchgesellschaft, Darmstalt.
4. Avenhaus, R., Kyriakopoulos, N., Richard, M., and Stein, G. (2006). Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions. Springer, New York.
5. Baatz, M. and Schape, A. (1999). Object-oriented and multi-scale image analysis in semantic networks. Proceedings of the 2nd International Symposium on Operationalization of Remote Sensing, 16-20 August, Enschede, The Netherlands. Enschede, CD-Rom.
6. Baatz, M. and Schape, A. (2000). Multiresolution segmentation-An optimization approach for high quality multi-scale image segmentation. In: J. Strobl, and T. Blaschke (Eds.): Angewandte Geographische Informationsverarbeitung XII. Beitrage zum AGIT-Symposium Salzburg. Heidelberg, New York.
7. Baatz, M., Heyen, M., and Hofman, P. (2004). eCognition-Object oriented image analysis. User Guide. Definiens AG. Abrufbar unter: http://www.definiens- imaging.com.
8. Banko, G. (1998). A review of assessing the accuracy of classifications of remotely sensed data and methods including remote sensing data in forest inventory. Interim Report IR-98-081. IIASA, Laxanburg, Austria.
9. Baute, J. G. (2006). A concrete experience: The Iraq Case. In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Ed.), Springer, New York.
10. Benz, U., Hofmann, P., Willhauck, G., Lingenfelder, I., and Heynen, M. (2004). Multi-resolution, object-oriented fuzzy analysis of remote sensing data for gis-ready information. ISPRS Journal of Photogrammetry & Remote Sensing 58 (2004), 239-258.
11. Berk, A., Bernstein, L., and Robertson, D. C. (1989). Modtran: A moderate resolution model for lowtran. afgl-tr-89-0122. Air Force Geophysics Laboratory, Hanscom AFB MA 01731.
12. Bhattacharyya, A. (1943). On a measure of divergence between two statistical populations defined by their probability distributions. Bulletin of the Calcutta Mathematical Society, (35), 99-110.
13. Bitelli, G., Camassi, R., Gusella, R., andMongol, A. (2004). Image change detection on urban area: The earthquake case. Proceedings of the ISRPS 2004 Annual Conference, Istanbul, Turkey. July 19-23.
14. Blaschke, T. (2000). Objektextraktion und regelbasierte Klassifikation von Fernerkundungsdaten: Neue Moglichkeiten fur GIS-Anwender und Planer. In: M. Schrenk, (Ed.): CORP'2000. Technical University of Vienna.
15. Blaschke, T. (2004). Towards a framework for change detection based on image objects. 1st GGRS, Gottingen, 7-8 October.
16. Blaschke, T. (2005). A framework for change detection based on image objects. In: Gottinger Geographische Abhandlungen, S., Erasmi, B., Cyffka, M. Kappas, (Eds.) 113, 1-9. Goltze, Goettingen.
17. Bruzzone, L. and Prieto, D. F. (1999). A bayesin appraoch to automatic change detection. Proceedings of the IEEE 1999 International Geoscience and Remote Sensing Symposium, Hamburg.
18. Byrne, G. F., Crapper, P. F., and Mayo, K. K. (1980). Monitoring land-cover changes by principal component analysis of multitemporal landsat data. Remote Sensing of Environment, 10, 175-184.
19. Cabral, P., Gilg, J., and Painho, M. (2005). Monitoring urban growth using remote sensing, gis and spatial metrics, remote sensing and modeling of ecosystems for sustainability. Proceedings of SPIE-Optics & Photonics, San Diego, USA, 29 July-4 August.
20. Campbell, J. B. (1996). Introduction to Remote Sensing, 2nd Edition, Taylor & Francis, New York.
21. Canty, M. J. (1999). Fernerkundung mit Neuronalen Netzen. Expert-Verlag, Germany.
22. Canty, M. J. and Schlittenhardt, J. (2001). Satellite data used to locate site of 1998 indian nuclear test. Eos, Transactions, American Geophysical Union, 82(3), 25-29.
23. Canty, M. J., Nielsen, A. A., and Schmidt, M. (2004). Automatic radiometric normalization of multispectral imagery. Remote Sensing of Environment, 91(3, 4), 441-451.
24. Carlson, J. (2006). Experience and challenges inWMD treaty verification: A comparative view. In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Eds.), Springer, New York.
25. Centeno, J. S. (1998). Integrierte Verarbeitung von Satellitenbild-und gerasteter Karteninformation. In: Digitale Bildverarbeitung. H.-P.Bahr and T. Vogtle (Eds.): Anwendung in Photogrammetrie, Kartographie und Fernerkundung, Heidelberg.
26. Chandra, M., Moreira, A., and Keydel, W. (2005). Amper: Network on applied multiparameter environmental remote sensing. An eu sponsored resaerch and training network. Proceedings of the IGARSS 2005 Symposium. Seoul, Korea.
27. Chavez, P. and MacKinnon, D. J. (1994). Automatic detection of vegetation changes in the southwestern united states using remotely sensed images. Photogrammetric Engineering and Remote Sensing, 60(5), 571-583.
28. Chen, Y., Fung, T., Lin, W., and Wang, J. (2005). An image fusion method based on object-oriented image classification. Proceedings of the IGARSS 2005 Symposium. Seoul, Korea, 25-29 July.
29. Chunyang, H., Li, J., Zhang, J., Pan, Y., and Chen, Y. H. (2005). Dynamic monitor on urban expansion based on a object-oriented approach. Proceedings of the IGARSS 2005 Symposium. Seoul, Korea, 25-29 July.
30. Clayton, D. G. (1971). The gram-schmidt othogonalization. Applied Statistics, 20, 335-338.
31. Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing Environment, 37, 35-46.
32. Cooley (2006). Nuclear nonproliferation treaty NPT. in: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Eds.), Springer, New York.
33. Crase, B. and Hempel, C. (2005). Object based land cover mapping for groote eylandt: A tool for reconnaissance and land based surveys. Proceedings of NARGIS 2005-APPLICATIONS IN TROPICAL SPATIAL SCIENCE. 4th-7th July Charles Darwin University, Darwin, NT, Australia.
34. Dai, X. and Khorram, S. (1997). Development of a feature-based approach to automated image registration for multitemporal and multisensor remotely sensed imagery. Proceedings of the IEEE 1997 Internatinal Geoscience and Remote Sensing Symposium, Singapore.
35. Dai, X., Khorram, S., and Cheshire, H. (1996). Automated image registration for change detection from landsat thematic mapper imagery. Proceedings of the IEEE 1996 Internatinal Geoscience and Remote Sensing Symposium, Lincoln, USA.
36. Du, Y., Teillet, P., and Cihlar, J. (2002). Radiometric normalization of multitemporal highresolution images with quality control for land cover change detection. Remote Sensing Environment, 82, 123-134.
37. Eklundh, L. and Singh, A. (1993). A comparative analysis of standardised and unstandardised principal components analysis in remote sensing. International Journal of Remote Sensing, 14(7), 1359-1370.
38. Farebrother, R. W. (1974). The gram-schmidt regression. Applied Statistics, 23, 470-476.
39. Feitosa, R., Costa, G., and Cazes, T. (2006). A genetic approach for the automatic adaptation of segmentation parameters. Proceedings of the AGIT-Obia, Salzburg, 4-5 July.
40. Fischer, W. and Stein, G. (1998). Das gestarkte safeguards-system der iaeo. Energiewirtschaftliche Tagesfragen, 48(8), 524-530.
41. Frauman, E. and Wolf, E. (2005). Segmentation of very high spatial resolution satellite images in urban areas for segments-based classification. Proceedings of the ISPRS WG 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.
42. Freund, J. (2003). Mathematical statistics with Applications. Prentice-Hall International.
43. Förstner, W. and Gulch, E. (1987). A fast operator for detection and precise location of distinct points, corners and centers of circular features. ISPRS Intercommission Workshop, Interlaken.
44. Förstner, W., Liedtke, C.-E., and Buckner, J. (Eds.) (1999). SMATI 99. Proceedings of the Semantic Modelling for the Acquisition of Topographic Information from Images and Maps. Munich, Germany.
45. Fukunaga, K. (1990). Introduction to Statistical Pattern Recognition, 2nd Edition. Academic Press Inc, Burlington, MA, USA.
46. Fung, T. (1990). An assessment of tm imagery for land-cover change detection. IEEE Transactions on Geoscience and Remote Sensing, 28(4), 681-684.
47. Fung, T. and LeDrew, E. (1987). Application of principal components analysis to change detection. Photogrammetric Engineering & Remote Sensing, 53(12), 1649-1658.
48. Fung, T. and LeDrew, E. (1988). The determination of optimal threshold levels for change detection using various accuracy indices. Photogrammetric Engineering & Remote Sensing, 54(10), 1449-1454.
49. Furby, S. and Campell, N. (2001). Calibrating images from different dates to like-value counts. Remote Sensing Environment, 82, 123-134.
50. Gong, P. (1993). Change detection using principal components analysis and fuzzy set theory. Canadian Journal of Remote Sensing, 19(1), 22-29.
51. Greiwe, A. (2004). Feature-based fusion of multisensor data-inclusion of hyperspectral data into classification of high resolution orthophotos. 1st GGRS, Gvttingen, 7-8 October.
52. Grenzdoerfer, G. (2005). Land use change in rostock, germany since the reunification-A combined approach with satellite data and high resolution aerial images. Proceedings of the ISPRS WG 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.
53. Growe, S. and Tonjes, R. (1997). A knowledge based approach to automatic image registration. Proceedings of the International Conference on Image Processing 97 (ICIP 97), Santa Barbara, USA.
54. Hall, F., Strebel, D., Nickeson, J., and Goetz, S. (1991). Radiometric rectification: Toward a common radiometric response among multidate, multisensor images. Remote Sensing Environment, 82, 123-134.
55. Haralick, R. and Shapiro, L. (1992). Computer and Robot Vision. Volume 1. Addison-Wesley, Reading.
56. Haralick, R. and Shapiro, L. (1993). Computer and Robot Vision. Volume 2. Addison-Wesley, Reading.
57. Heremans, R., Willekens, A., Borghys, D., Verbeeck, B., Valckenborgh, J., and 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. June 20-24, St. Petersburg, Russian Federation.
58. Hofmann, T. and Buhmann, J. M. (1997). Pairwise data clustering by deterministic annealung. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(1), 1-4.
59. Hofmann, T., Puzicha, J., and Buhmann, J. M. (1996). Unsupervised segmentation of textured images by pairwise data clustering. Proceedings of the IEEE Conference on Image Processing, 1996, Lausanne, Switzerland, III, 137-140.
60. Hudson, W. D. and Ramm, C. W. (1987). Correct formulation of the kappa coefficient of agreement. Photogrammetric Engineering and Remote Sensing, 53(4), 421-422.
61. IAEA/Hg. (1968). The agency's safeguards system. Information Circular 66, Rev. 2, Wien.
62. IAEA/Hg. (1970). Treaty on the non-proliferation of Nuclear Weapons. Information Circular 140, Wien.
63. IAEA/Hg. (1972). The structure and content of agreements between the agency and states required in connection with the treaty on the non-proliferation of Nuclear Weapons. Information Circular 153, Wien.
64. IAEA/Hg. (1998). Model protocol additional to the agreement(s) between state(s) and the international atomic energy agency for the application of safeguards. Information Circular 540 (Corrected), Wien.
65. Ingebritsen, S. E. and Lyon, R. J. P. (1985). Principal components analysis of multitemporal image pairs. International Journal of Remote Sensing, 6(5), 687-696.
66. Jasani, B. (2004). Identification of key features of nuclear reactors for interpretation of imageries from remote sensing satellites. Journal of Nuclear Materials Management, 32(3), 28-37.
67. Jasani, B. (2006). Civil reconnaissance satellites-opportunities and challenges, In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Eds.). Springer, New York.
68. Jensen, J. R. (2004). Introductory Digital Image Processing-A Remote Sensing Perspective, 3rd Edition, Prentice Hall, Upper Saddle River, NJ, USA.
69. Jiaju, L. (1988). Development of principal component analysis applied to multitemporal landsat tm data. International Journal of Remote Sensing, 9(12), 1895-1907.
70. Kneizys, F., Shettel, E., Abreu, L., Chetwynd, J., Anderson, G., Gallery, W., Selby, J., and Clough, S. A. (1988). Users guide to lowtran 7. afgltr-88-0177. Air Force Geophysics Laboratory, NTIS No. AD-A206773.
71. Koch, B., Jochum, M., Ivitis, E., and Dees, M. (2003). Pixelbasierte Klassifizierung im Vergleich and zur Erganzung zum objektbasierten Verfahren. Photogrammetrie Fernerkundung Geoinformation, 3, 195-204.
72. Kosugi, Y. and Kosaka, N. (2005). Development of agricultural gis on shonai area in northeast japan using satellite data. Proceedings of the 26th Asian Conference on Remote Sensing. Hanoi, Vietnam, 7-11 November.
73. Kouchi, K. and Yamazaki, F. (2005). Damage detection based on object-based segmentation and classification from high-resolution satellite images for the 2003 boumerdes, algeria earthquake. Proceedings of the 26th Asian Conference on Remote Sensing. Hanoi, Vietnam, 7-11 November.
74. Kraus, K. (1990). Fernerkundung Band 2, Auswertung photographischer und digitaler Bilder. F. Bonn: Ferd. Dummlers Verlag.
75. Kraus, K. and Schneider, W. (2001). Fernerkundung. Physikalische Grundlagen. Band 1. Dummler Verlag, Bonn.
76. Kronfeld, U., Baus, W., Ebbesen, B., and Jathe, M. (Eds.), (1993). Abrustung, Konversion, Verifkation, Technikfolgen, O kologische Sicherheit. Naturwissenschaftliche Forschungsprojekte an deutschen Hochschulen. Kieler Schriften zur Friedenswirtschaft, Band 2, LIT, Hamburg.
77. Kunz, D., Vogtle, T., and Schilling, K.-J. (1998). Integrierte verarbeitung von satellitenbild und vektorieller karteninformation. in: H.-P. Bahr und T. Vogtle (Ed.): Digitale Bildverarbeitung. Anwendung in Photogrammetrie, Kartographie und Fernerkundung, Heidelberg, New York.
78. Laben, C. A. and Brower, B. V. (2000). Process for enhancing the spatial Resolution of multispectral Imagery using Pan-sharpening. United States Patent.
79. Laliberte, A., Rango, A. and Fredrickson, E. (2005). Classification of arid rangelands using an object-oriented and multi-scale approach with quickbird imagery. Proceedings of the ASRPS 2005 Annual Conference, Baltimore, MD, USA, 7-11 March.
80. Langanke, T., Blaschke, T., and Lang, S. (2004). An object-based gis/remote sensing approach supporting monitoring tasks in european-wide nature conservation. Proceedings of the Mediterranean conference on Earth Observation. First Mediterranean Conference on Earth Observation (Remote Sensing), 21-23, April Belgrade, 245-252.
81. Lee, A. J., Carender, N. H., Knowlton, D. J., Bell, D.M., and Bryan, J. K. (1993). Autonomous registration of landsat, spot, and digital map imagery. Proceedings of the SPIE 1944: Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision, April, Orlando, USA, 68-79.
82. Lehner, M. (1986). Triple stereoscopic imagery simulation and digital image correlation for meoss project. Proceedings of the ISPRS Commision I Symposium, Stuttgart, 477-484.
83. Lehner, M. and Gill, R. (1989). Photogrammetric Adjustment of Triple Stereoscopic Imagery of an Airbone CCD Scanner. Proceedings of the Optical 3-D Measurment Techniques, Wichman Verlag, Karlsruhe.
84. Lehner, M. and Gill, R. (1992). Semi-automatic derivation of digital elevation models from stereoscopic 3-line scanner data. Proceedings of Satellite Symposia 1 & 2: Navigation & Mobile Communications, and Image Processing, GIS & Space-assisted Mapping, International Space Year Conference, Munich, Germany.
85. LeMoigne, J. (1998). First evaluation of automatic image registration methods. Proceedings of the IEEE 1998 International Geoscience and Remote Sensing Symposium, Seattle, USA, 6-10 July.
86. Li, H., Manjunath, B. S., and Mitra, S. K. (1995). A contour-based approach to multisensor image registration. IEEE Transactions on Image Processing, 4(3), 320-334.
87. Lillesand, T. M., Kiefer, R. W., and Chipman, J. W. (2003). Remote Sensing and Image Interpretation. John Wiley & Sons, Hoboken.
88. Liu, Z., Wang, J., and Liu, W. (2005). Building extraction from high resolution imagery based on multi-scale object oriented classification and probabilistic hough transform. Proceedings of the IGARSS 2005 Symposium. Seoul, Korea, 25-29 July.
89. Macleod, R. D. and Congalton, R. G. (1998). A quantitative comparison of change detection algorithms for monitoring eelgrass from remotely sensed data. Photogrammetric Engineering & Remote Sensing, 64(3), 207-216.
90. Mallat, S. G. (1989). A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), 674-693.
91. Mas, J.-F. (1999). Monitoring land-cover changes-A comparison of change detection techniques. International Journal of Remote Sensing, 20(1), 139-152.
92. Mather, P. M. (2004). Computer Processing of Remotely Sensed Images. An Introduction. John Wiley & Sons, Chichester.
93. Metternicht, G. (1999). Change detection assessment using fuzzy sets and remotely sensed data: An application of topographic map revison. ISPRS Journal of Photogrammetry & Remote Sensing, 54(4), 221-233.
94. Moeller, M. (2005). Remote sensing for the monitoring of urban growth patterns. Proceedings of the ISPRS WG 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.
95. Moran, M., Jackson, R., Slater, P., and Teillet, P. (1992). Evaluation of simplified procedures for retrival of land surface reflectance factors from satellite sensor output. Remote Sensing Environment, 41, 160-184.
96. Muchoney, D. M. and Haack, B. N. (1994). Change detection for monitoring forest defoliation. Photogrammetric Engineering & Remote Sensing, 60(10), 1243-1251.
97. Nauck, D., Klawonn, F., and Kruse, R. (1994). Neuronale Netze und Fuzzy-Systeme. Vieweg, Braunschweig.
98. Neubert, M. and Meinel, G. (2003). Vergleich von Segmentierungsprogrammen fur Fernerkundungsdaten. Angewandte Geographische Informationsverarbeitung XV, Beitrage zum AGITSymposium Salzburg, Strobl/Blaschke/Griesebner (Eds.), 323-329.
99. Nielsen, A., Conradson, K., and Andersen, O. (2002). A change oriented extension of eof analysis applied to the 1996-1997 avhrr sea surface temperature data. Physics and Chemistry of Earth, 27(32-34), 1379-1386.
100. Nielsen, A. A. (1996). Change detection in multispectral, bi-temporal spatial data using othogonal transformations. Proceedings of the 8th Australien Remote Sensing Conference, Canberra, Australia, March.
101. Nielsen, A. A. and Conradsen, K. (1997). Multivariate alteration detection (mad) in multispectral, bi-temporal data: A new approach to change detection studies. Technical Report IMM-REP-1997.Technical University of Denmark Lyngby, 11.
102. Nielsen, A. A., Conradsen, K., and Simpson, J. J. (1998). Multivariate alteration detection (mad) and maf postprocessing in multispectral, bitemporal image data: A new approach to change detection studies. Remote Sensing of Environment, 64, 1-19.
103. Niemeyer, I. (2001). Satelliten und nukleare Kontrolle. Anderungsdetektion und wissensbasierte, objektorientierte Klassifikation zur Unterstutzung der nuklearen Verifikation. Schriftenreihe des Forschungszentrum Julich, Reihe Umwelt/Environment, Band 28, Julich.
104. Niemeyer, I. (2005). Use of thermal infrared image data for nuclear safeguards purposes. Proceedings of the 27th Symposium on Safeguards and Nuclear Material Management, 10-12 May (CD-Rom).
105. Niemeyer, I. and Canty, M. (2003). Pixel-based and object-oriented change detection analysis using high-resolution imagery. Proceedings of the 25th Symposium on Safeguards and Nuclear Material Managment, Stockholm, Sweden, 13-15 May (CD-Rom).
106. Niemeyer, I. and Nussbaum, S. (2005). Automation of change detection procedures for nuclear safeguards-related monitoring purposes. Proceedings of the 31st International Symposium of Remote Sensing of Environment, Global Monitoring for Sustainability and Security, Saint Petersburg.
107. Niemeyer, I., Nussbaum, S., and Lingenfelder, I. (2005a). Automated analysis of remote sensing data for extensive monitoring tasks in the context of nuclear safeguards. Proceedings of the IEEE International Geo-science and Remote Sensing Symposium, IGARSS'05, Seoul.
108. Niemeyer, I., Nussbaum, S., and Canty, M. (2005b). Automation of change detection procedures for nuclear safeguards-related monitoring purposes. Proceedings of the IEEE International Geo-science and Remote Sensing Symposium, IGARSS'05, Seoul.
109. Nussbaum, S., Niemeyer, I., and Canty, M. (2005). Feature recognition in the context of automated object-oriented analysis of remote sensing data monitoring the iranian nuclear sites. Proceedings of the SPIE Europe Symposium on Optics/Photonics in Security & Defence, Bruges, Belgium, September 26-28, 5988.
110. Pappas, T. N. and Safranek, R. (2000). Perceptual criteria for image quality evaluation. Handbook of image and Video Processing. In: A. C. Bovik, (Ed.), p. 939-959, Academic Press.
111. Poucet, A. (2006). Arms control and non-proliferation treaties: An ontology of concepts and characteristics. In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Eds.), Springer, New York.
112. Quint, F. (1998). Objekterfassung aus Karte und Bild. In H.-P. Bahr and T. Vogtle (Ed.): Digitale Bildverarbeitung Anwendung in Photogrammetrie, Kartographie und Fernerkundung. Heidelberg, Germany.
113. Ranchin, T. and Wald, L. (2000). Fusion of high spatial and spectral resolution images: The arsis concept and its implementation. Photogrammetric Engineering and Remote Sensing, 66(1), 49-61.
114. Ranchin, T., Aiazzi, B., Alparone, L., Baronti, S., and Wald, L. (2003). Image fusion-The arsis concept and some successful implementation schemes. ISPRS Journal of Photogrammetry & Remote Sensing, 58, 4-18.
115. Richard, M. (2006). Beyond Iraq: The new challenges to the nuclear nonproliferation regime). In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Eds.), Springer, New York.
116. Richards, J. A. and Jia, X. (1999). Remote Sensing Digital Image Analysis. An Introduction. Springer Verlag, New york.
117. Richter, R. (1990). A fast atmospheric correction algorithm applied to landsat tm images. International Journal of Remote Sensing, 11(1), 159-166.
118. Ridd, M. K. and Liu, J. (1998). A copmarison of four algorithms for change detection in urban environment. Remote Sensing of Environment, 63, 95-100.
119. Rosenfield, G. H., Fitzpatrick-Lins, K., and Ling, H. (1982). Sampling for thematic map accuracy testing. Photogrammetric Engineering and Remote Sensing, 48(1), 131-137.
120. Sagerer, G. and Niemann, H. (1997). Semantic Networks for Understanding Scenes. Advanes in Computer Vision and Machine Intellegence. Plenum Press, New York.
121. Sandmeier, S. (1997). Radiometrische korrektur des topographieeffektes in optischen satellitenbilddaten-vergleich eines semi-empirischen verfahrens mit einem physikalischbasierten modell. Photogrammetrie, Fernerkundung, Geoinformation, 1, 23-32.
122. Schenkel, R. (2006). Improving verification:Trends and perspectives for research. In: Verifying Treaty Compliance-Limiting Weapons of Mass Destruction and Monitoring Kyoto Protocol Provisions, R. Avenhaus, N. Kyriakopoulos, M. Richard and G. Stein (Ed.), Springer, New York.
123. Schiewe, J. (2002). Segmentation of High-Resolution remotely sensed Data-Concepts, Applications and Problems. Symposium on Geospatial Theory, Processing Applications. Ottawa.
124. Schiewe, J. and Tufte, L. (2001). Potenzial regionen-basierter Verfahren fur die intergrative Auswertung von GIS-und Fernerkundungsdaten. In Fernerkundung and GIS. T. Blascke (Eds.). Wichmann.
125. Schott, J., Salvaggio, C., and Volchok, W. (1988). Radiometric scene normalization using pseudoinvariant features. Remote Sensing Environment, 26, 1-16.
126. Schott, J. R. (1997). Remote Sensing. The Image Chain Approach. Oxford University Press, New York.
127. Schowengerdt, R. A. (1997). Remote Sensing-Models and Methods for Image Processing. 2nd Edition, San Diego. Academic Press.
128. Sim, S. (2005). A proposed method for disaggregating census data using object-oriented image classification and gis. Proceedings of the ISPRS WG 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.
129. Singh, A. (1989). Digital change detection techniques using remotly-sensed data. International Journal of Remote Sensing, 10(6), 989-1003.
130. Slink, T. A. (1996). Satellitenfernerkundung zur Verifkation von Rustungskontrollen und Abrustungsvertragen. Europaische Hochschulschriften 1957, Reihe II, Rechtswissenschaft. Verlag Peter Lang, Frankfurt/Main.
131. Sohl, T. L. (1999). Change analysis in the united arab emirates: An investigation of techniques. Photogrammetric Engineering & Remote Sensing, 65(4), 475-484.
132. Sonka, M., Hlavac, V., and Boyle, R. (1998). Image processing, Analyses and Machine Vision, 2. Auflage. PWS Publishing, Pacific Grove.
133. Sunar, F. (1998). An analysis of change in a multi-date data set: A case study in the ikitelli area, istanbul, turkey. International Journal of Remote Sensing, 19(2), 225-235.
134. Thepaut, O., Kpalma, K., and Ronsin, J. (1998). Erssar and spot images automatic registration in a multichannel consensual segmentation scheme. Proceedings of the IEEE 1998 International Geoscience and Remote Sensing Symposium, Seattle, USA, 6-10 July II, 1040-1042.
135. Tizhoosh, H. R. (1998). Fuzzy-Bildverarbeitung. Einfuhrung in Theorie und Praxis. Springer, Berlin.
136. Tonjes, R. (1999). Wissensbasierte Interpretation und 3D-Rekonstruktion von Landschaftsszenen aus Luftbildern. Fortschritt-Berichte VDI, VDI-Verlag. Dusseldorf, 10(575).
137. Tönjes, R., Growe, S., Buckner, J., and Liedtke, C.-E. (1999). Knowledge-based interpretation of remote sensing images using semantic nets. Photogrammetric Engineering & Remote Sensing, 65(7), 811-821.
138. Truong, O., Keeffe, R., Baines, P., and Paquette, J.-P. (1999). Potential application of commercial satellite imagery in international safeguards. Journal of Nuclear Materials Management (JNMM), 25(2), 13-18.
139. USGS (Januar, 1990). The spatial data transfer standard. United States gelogical Survey, Draft.
140. van Genderen, J., Lock, B., and Vass, P. (1978). Remote sensing: Statistical testing of thematic map accuracy. Remote Sensing of Environment, 7, 3-14.
141. Vermote, E. F., Tanre', D., Deuze', J. J., Herman, M., and Mocrette, J.-J. (1997). Second simulation of the satellite signal in the solar spectrum, 6s: An overview. Geoscience and Remote Sensing, 35(3), 675-686.
142. Wang, Z. and Bovik, A. C. (2002). A universal image quality index. IEEE Signal Processing Letters.
143. Wiemker, R. (1997). An iterative spectral-spatial bayesian labeling approach for unsupervised robust change detection on remotely sensed multispectral imagery. Proceedings of the 7th International Conference on Computer Analysis of Images and Patterns, CAIP'97, 10-12, 263-270.
144. Wiemker, R., Speck, A., Kulbach, D., Spitzer, H., and Bienlein, J. (1997). Unsupervised robust change detection on multispectral imagery using spectral and spatial features. Proceedings of the Third International Airborne Remote Sensing Conference and Exhibition, 7-10 July, Copenhagen, Denmark, I, 640-647.
145. Wilkinson, G. G. (1999). Recent developments in remote sensing technology and the importance of computer vision analysis techniques. I., Kanellopoulos, G. G.Wilkinson, and Moons T. (Eds.): Machine Vision and Advanced Image Processing in Remote Sensing. Berlin, I, 5-11. Springer.
146. Witheside, T. (2005). A multi-scale object-oriented approach to the classification of multi-sensor imagery for mapping land cover in the top end. Proceedings of NARGIS 2005-APPLICATIONS IN TROPICAL SPATIAL SCIENCE. 4th-7th July 2005 Charles Darwin University, Darwin, NT, Australia.
147. Xu, L. and Yuille, A. L. (1995). Robust principal component analysis by self-organizing rules based on statistical physics approach. ITTT Transactions on Neural Networks, 6(1), 131-143.
148. Yang, L., Albregtsen, F., Lønnestad, T., and Grøtum, P. (1995). A supervised approach to the evaluation of image segmentation methods. Proceedings CAIP 1995, Lecture Notes in Computer Science, 970, 759-765.
149. Yang, T.-N. and Wang, S.-D. (1999). Robust algorithms for principal component analysis. Pattern Recognition Letters 20, 927-933.
150. Yang, X. and Lo, C. (2000). Relative radiometric normalization performance for change detection from multi-date satellite images. Photogrammetric Engineering and Remote Sensing, 66, 967-980.
151. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.
152. Zhang, Y. (1996). A survey on evaluation methods for image segmentation. Pattern Recognition, 29(8), 1335-1346.