A review of current issues in the integration of GIS and remote sensing data

International Journal of Geographical Information Systems

Volumn 10, Issue 1, 1996, Pages 85-101

  Wilkinson, G G ^a  

^a JOINT RESEARCH CENTRE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYSIS; DATA INTEGRATION; GIS; NEURAL NETWORK; REMOTE SENSING DATA; VISUALIZATION;

EID: 0029750124     PISSN: 02693798     EISSN: None     Source Type: Journal    
DOI: 10.1080/02693799608902068     Document Type: Article

References (90)

1. ANSELIN, L. 1994 Exploratory spatial data analysis and geographic information systems. Proceedings of EUROSTAT/DOSES Programme Workshop on New Tools for Spatial Data Analysis, held in Lisbon, 17-20 November 1993, (Luxembourg: Office for Official Publications of the European Communities), Eurostat Statistical Document, Theme 3, Series D, pp. 45-54.
2. ARDUINI, F., FIORAVANTI, S., and GIUSTO, D. D. 1991 Multifractals towards remote-sensing surface texture characterization. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '91), held in Espoo, Finland, 23-26 May. (Piscataway NJ: I.E.E.E. Press), pp. 317-320.
3. BAJCSY, R., and TAVAKOLI, M. 1976, Computer recognition of roads from satellite pictures. I.E.E.E. Transactions on Systems, Man, and Cybernetics, SMC-6, 623-637.
4. BARKER, J. 1993 Calibration and characterization of MODIS imagers on 15-year EOS mission. Proceedings of 12th Pecora Memorial Conference entitled: Land Information from Space Based Systems, held at Sioux Falls, 24-26 August (Bethesda, Maryland: American Society for Photogrammetry and Remote Sensing) pp. 326-335.
5. BEAULIEU, J. M., and GOLDBERG, M. 1989, Hierarchy in picture segmentation: a stepwise optimization approach. I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence, 11, 150-163.
6. BENEDIKTSSON, J. A., SWAIN, P. H., and ERSOY, O. K. 1990, Neural network approaches versus statistical methods in classification of multisource remote sensing data. I.E.E.E. Transactions on Geoscience and Remote Sensing, 28, 540-552.
7. BENEDIKTSSON, J. A., SWAIN, P. H., and ERSOY, O. K. 1993, Conjugate-gradient neural networks in classification of multisource and very-high-dimensional remote sensing data. International Journal of Remote Sensing, 14, 2883-2903.
8. BISCHOF, H., SCHNEIDER, W., and PINZ, A. J. 1992, Multispectral classification of Landsat images using neural networks. I.E.E.E. Transactions on Geoscience and Remote Sensing, 30, 482-490.
9. CEOS, 1992, The Relevance of Satellite Missions to the Study of the Global Environment, Committee on Earth Observation Satellites, Report to the UNCED Conference Rio de Janeiro 1992, (London: British National Space Centre).
10. CETIN, H., WARNER, T. A., and LEVANDOWSKI, D. W., 1993, Data classification, visualization, and enhancement using n-dimensional probability density functions (nPDF): AVIRIS, TIMS, TM and geophysical applications, Photogrammetric Engineering and Remote Sensing, 59, 1755-1764.
11. CIVCO, D. L. 1993, Artificial neural networks for land-cover classification and mapping, Int. J. Geographical Information Systems, 7, 2, 173-186.
12. CHEN, K. S., TZENG, Y. C., CHEN, C. F., and KAO, W. L. 1995, Land-cover classification of multispectral imagery using a dynamic learning neural network, Photogrammetric Engineering and Remote Sensing, 61, 403-408.
13. CHIOU, S. W. C. 1985, NASA image-based geological expert system development project for hyperspectral image analysis. Applied Optics, 24, 2085-2091.
14. CORR, D. G., TAILOR, A. M., CROSS, A., HOGG, D. C., LAWRENCE, D. H., MASON, D. C., and PETROU, M. 1989, Progress in automatic analysis of multi-temporal remotely-sensed data. International Journal of Remote Sensing, 10, 1175-1195.
15. CRIST, E. P., and CICONE, R. C. 1984, A physically-based transformation of Thematic Mapper data - the TM Tasseled Cap. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-22, 256-263.
16. CURRAN, P. J., 1988, The semivariogram in remote sensing: an introduction, Remote Sensing of Environment, 24, 493-507.
17. DAYHOFF, J., 1990, Neural Network Architectures. (New York: Van Nostrand Reinhold).
18. DE COLA, L. 1989, Fractal analysis of a classified Landsat scene. Photogrammetric Engineering and Remote Sensing, 55, 601-610.
19. DINER, D. J., BRUEGGE, C. J., MARTONCHIK, J. V., BOTHWELL, G. W., HOVLAND, L. E., and JONES, K. L., 1991, Global environmental monitoring with the EOS Multi-Angle Imaging Spectroradiometer (MISR). Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '91), held in Espoo, Finland, 23-26 May. (Piscataway NJ: I.E.E.E. Press), pp. 717-720.
20. DOWNEY, I. D., POWER, C. H., KANELLOPOULOS, I., and WILKINSON, G. G. 1992, A performance comparison of Landsat-TM land cover classification based on neural network techniques and traditional maximum likelihood and minimum distance algorithms. Proceedings of the 18th Annual Conference of the U.K. Remote Sensing Society entitled: Remote Sensing from Research to Operation, held in Dundee, Scotland, 15-17 September, edited by A. P. Cracknell and R. A. Vaughan, (Nottingham: Remote Sensing Society), pp. 518-528.
21. EDDY, C. A., and LOONEY, B. 1993, Three-dimensional digital imaging of environmental data: selection of gridding parameters. International Journal of Geographical Information Systems, 7, 165-172.
22. ELLIS, S. R. (editor), 1993, Pictorial Communication in Real and Virtual Environments (London: Taylor and Francis) 2nd. edition.
23. FISCHLER, M. A., TENENBAUM, J. M., and WOLF, H. C. 1981, Detection of roads and linear structures in low-resolution aerial imagery using a multisource knowledge integration technique. Computer Graphics and Image Processing, 15, 201-223.
24. FISHER, P. F. 1991, Modelling soil map-unit inclusions by Monte Carlo simulation. International Journal of Geographical Information Systems, 5, 193-208.
25. FOODY, G. M. 1995, Using prior knowledge in artificial neural network classification with a minimal training set. International Journal of Remote Sensing, 16, 301-312.
26. FRANKLIN, S. E., and PEDDLE, D. R. 1990, Classification of SPOT HRV imagery and texture features. International Journal of Remote Sensing, 11, 551-556.
27. GARVEY, T. D., 1987, Evidential reasoning for geographic evaluation for helicopter route planning. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 294-304.
28. GOLDBERG, M., GOODENOUGH, D., and SHLIEN, S. 1975, Classification methods and error estimation for multispectral scanner data. Proceedings of 3rd. Canadian Symposium on Remote Sensing, September pp. 125-143.
29. GOODENOUGH, D. G., GOLDBERG, M., PLUNKETT, G., and ZELEK, J. 1987, An expert system for remote sensing. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 349-359.
30. GUO, L. J., and MOORE, JMCM., 1991, Post-classification processing for thematic mapping based on remotely sensed image data. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '91), held in Espoo, Finland, 23-26 May. (Piscataway NJ: I.E.E.E. Press), pp. 2203-2206.
31. HARALICK, R. M., SHANMUGAM, K., and DINSTEIN, I., 1973, Textural features for image classification. I.E.E.E. Transactions on Systems, Man and Cybernetics, SMC-3, 610-621.
32. HARLOW, C. A., TRIVEDI, M. M., CONNERS, R. W., and PHILLIPS, D. 1986, Scene analysis of high resolution aerial scenes. Optical Engineering, 25, 347-355.
33. HEPNER, G. F., LOGAN, T., RITTER, N., and BRYANT, N. 1990, Artificial neural network classification using a minimal training set: comparison to conventional supervised classification. Photogrammetric Engineering and Remote Sensing, 56, 469-473.
34. HEUVELINK G. B. M., and BURROUGH, P. A., 1993, Error propagation in cartographic modelling using Boolean logic and continuous classification. International Journal of Geographical Information Systems, 7, 231-246.
35. HEUVELINK, G. B. M., BURROUGH, P. A., and STEIN, A. 1989, Propagation of errors in spatial modelling with GIS. International Journal of Geographical Information Systems, 3, 303-322.
36. HILL, J., and MÉGIER, J., 1988, Regional land cover and agricultural area statistics and mapping in the Département Ardèche, France, by use of Thematic Mapper data. International Journal of Remote Sensing, 9, 1573-1595.
37. IRONS, J. R., MARKHAM, B. L., NELSON, R. F., TOLL, D. L., WILLIAMS, D. L., LATTY, R. S., and STAUFFER, M. L., 1985, The effects of spatial resolution on the classification of Thematic Mapper data. International Journal of Remote Sensing, 6, 1385-1403.
38. JIMENEZ, L., and LANDGREBE, D., 1994, High dimensional feature reduction via projection pursuit. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '94), held at Pasadena, 8-12 August 1994, (Piscataway NJ: I.E.E.E. Press) 2, pp. 1145-1147.
39. JONES, M. C., and SIBSON, R., 1987, What is projection pursuit?, Journal of Royal Statistical Society A., 150, part 1, pp. 1-36.
40. JRC. 1991, Annual Report 1991, Institute for Remote Sensing Applications, Joint Research Centre, Commission of the European Communities. (Luxembourg: Office for Official Publications of the European Communities), Publication No. EUR 14833, pp. 46-48.
41. KANELLOPOULOS, I., VARFIS, A., WILKINSON, G. G., and MÉGIER, J., 1992, Land cover discrimination in SPOT imagery by artificial neural network - a twenty class experiment. International Journal of Remote Sensing, 13, pp. 917-924.
42. KANELLOPOULOS, I., WILKINSON, G. G., and MÉGIER, J. 1993, Integration of neural network and statistical image classification for land cover mapping. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '93), held in Tokyo 18-21 August. (Piscataway, NJ: I.E.E.E. Press), 2, pp. 511-513.
43. KEIM, D. A., and KRIEGEL, H.-P., 1994, VisDB: Database exploration using multidimensional visualization. I.E.E.E. Computer Graphics and Applications, 14, 75-78.
44. KEY, J., MASLANIC, A., and SCHWEIGER, A. J. 1989, Classification of merged AVHRR and SMMR arctic data with neural networks. Photogrammetric Engineering and Remote Sensing, 55, 1331-1338.
45. KIM, H., and SWAIN, P. H. 1989, Multisource data analysis in remote sensing and geographic information systems based on Shafer's theory of evidence. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '89), held in Vancouver, 10-14 July. (Piscataway NJ: I.E.E.E. Press), pp. 829-832.
46. KIMES, D. S., HARRISON, P. A., and HARRISON, P. R., 1992, New developments of a knowledge based system (VEG) for inferring vegetation characteristics. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '92), held in Houston, 26-29 May. (Piscataway NJ: I.E.E.E. Press), pp. 763-765.
47. KIMES, D. S., HARRISON, P. R., AND RATCLIFFE, P. A. 1991, A knowledge-based system for inferring vegetation characteristics. International Journal of Remote Sensing, 12, 1987-2020.
48. KOHONEN T. 1984, Self Organization and Associative Memory. Springer series in Information Sciences, Vol. 8. (Berlin: Springer-Verlag) - also in 2nd edition 1988.
49. KONTOES, C., WILKINSON, G. G., BURRILL, A., GOFFREDO, S., and MÉGIER, J. 1993, An experimental system for the integration of GIS data in knowledge-based image analysis for remote sensing of agriculture. International Journal of Geographical Information Systems, 7, 247-262.
50. LEE, J., WEGER, R. C., SENGUPTA, S. K., and WELCH, R. M. 1990, A neural network approach to cloud classification. I.E.E.E. Transactions on Geoscience and Remote Sensing, 28, 846-855.
51. LEE, T., RICHARDS, J. A., and SWAIN, P. H., 1987, Probabilistic and evidential approaches for multisource data analysis. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 283-293.
52. LOGUERCIO-POLOSA, R. M., PICCINNI, C. G., and SCIACOVELLI, N., 1992, Knowledge based detection of waste disposal sites using Landsat-TM imagery and context information. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '92), held in Houston, 26-29 May. (Piscataway, NJ: I.E.E.E. Press), pp. 1619-1621.
53. MATSUYAMA, T., 1987, Knowledge-based aerial image understanding systems and expert systems for image processing. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 305-316.
54. MCKEOWN, D. M., 1987, The role of artificial intelligence in the integration of remotely sensed data with geographic information systems. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 330-348.
55. MÉGIER, J., HILL, J., and KOHL, H., 1991, Land-use inventory and mapping in a mountainous area: the Ardèche experiment. International Journal of Remote Sensing, 12, 445-462.
56. MOLENAAR, M., and JANSSEN, L. L. F., 1992, Integrated processing of remotely sensed and geographic data for land inventory purposes. EARSeL Advances in Remote Sensing, 1, 113-121.
57. MOON, W. M., 1989, Integration of remote sensing and geophysical/geological data using Dempster-Shafer approach. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '89), held in Vancouver, 10-14 July. (Piscataway NJ: I.E.E.E. Press), pp. 838-841.
58. MOON, W. M., 1990, Integration of geophysical and geological data using evidential belief function. I.E.E.E. Transactions on Geoscience and Remote Sensing, 28, 711-720.
59. NAGAO, M., and MATSUYAMA, T., 1979, Edge preserving smoothing. Computer Graphics and Image Processing, 9, 394-407.
60. NICOLIN, B., and GABLER, R. 1987, A knowledge-based system for the analysis of aerial images. I.E.E.E. Transactions on Geoscience and Remote Sensing, GE-25, 317-329.
61. NOVAJOSKY, W., 1993, Present and future capabilities of SPOT satellite systems. Proceedings of 12th. Pecora Memorial Conference entitled: Land Information from Space Based Systems, held at Sioux Falls, 24-26 August, (Bethesda, Maryland: American Society for Photogrammetry and Remote Sensing) pp. 319-321.
62. PAO, Y.-H., 1989, Adaptive Pattern Recognition and Neural Networks (Reading MA: Addison-Wesley).
63. PAVLIDIS, T., and LIOW, Y.-T., 1990, Integrating region growing and edge detection. I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence, 12, 225-233.
64. PEDDLE, D. R., 1995, Knowledge formulation for supervised evidential classification. Photogrammetric Engineering and Remote Sensing, 61, 409-417.
65. PEDDLE, D. R., and FRANKLIN, S. E., 1992, Multisource evidential classification of surface cover and frozen ground. International Journal of Remote Sensing, 13, 3375-3380.
66. PENTLAND, A. P., 1984, Fractal-based description of natural scenes. I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence, 6, 518-523.
67. PENTLAND, A. P., 1985, On describing complex surface shapes. Image and Vision Computing, 3, 153-162.
68. PERKINS, W. A., LAFFEY, T. J., and NGUYEN, T. A., 1986, Rule-based interpreting of aerial photographs using the Lockheed expert system. Optical Engineering, 25, 356-362.
69. PRIEBE, C. E., SOLKA, J. L., ROGERS, G. W., and HAYES, H. I., 1993, Discriminant analysis in aerial images using fractal-based features. Proceedings of SPIE Conference No. 1962 entitled Adaptive and Learning Systems II, held in Orlando, 12-16 April. (Bellingham, WA: SPIE - The Society for Photo-Optical Instrumentation Engineering).
70. RAFFY, M., (editor), 1994, Special Issue: Scaling in Remote Sensing, International Journal of Remote Sensing, 15, 12.
71. RUMELHART, D. E., HINTON, G. E., and WILLIAMS, R. J. 1986, Learning internal representations by error propagation. In: Parallel Distributed Processing - Explorations in the Microstructure of Cognition, Volume 1: Foundations, edited D. E. Rumelhart, J. L. McClelland and the PDP Research Group editors. (Cambridge MA: MIT Press), pp. 318-362.
72. SCHOENMAKERS, R. P. H. M., and STAKENBORG, J. H. T. 1992, Adaptive filtering using gradient morphology. Proceedings 11th. IAPR International Conference on Pattern Recognition, held in The Hague, 30 August-3 Septeber.
73. SHAFER, G., 1976, A Mathematical Theory of Evidence (Princeton: Princeton University Press).
74. SHU-QUIANG, W., and UNWIN, D. J., 1992, Modelling landslide distribution on loess soils in China: an investigation. International Journal Geographical Information Systems, 6, 391-405.
75. SRINIVASAN, A., and RICHARDS, J. A., 1990, Knowledge based techniques for multi-source classification. International Journal Remote Sensing, 11, 505-525.
76. TILTON, J. C., 1989, Image segmentation by iterative parallel region growing and splitting. Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS '89), held in Vancouver, 10-14 July. (Piscataway, NJ: I.E.E.E. Press), pp. 2235-2238.
77. TILTON, J. C., and COX, S. C., 1983, Segmentation of remotely sensed data using parallel region growing, Digest of the International Geoscience and Remote Sensing Symposium (IGARSS '83), held in San Francisco, 31 August-2 September, pp. 9.1-9.6.
78. TROTTER, C. M., 1991, Remotely-sensed data as an information source for geographical information systems in natural resource management: a review. International Journal Geographical Information Systems, 5, 225-239.
79. VAN CLEYNENBREUGEL, J., FIERENS, F., SUETENS, P., and OOSTERLINCK, A. 1990, Delineating road structures on satellite imagery by a GIS-guided technique, Photogrammetric Engineering and Remote Sensing, 56, 893-898.
80. WANG, F., and NEWKIRK, R., 1988, A knowledge-based system for highway network extraction. I.E.E.E. Transactions on Geoscience and Remote Sensing, 26, 525-531.
81. WILKINSON, G. G., 1993 a, The generalization of satellite derived raster thematic maps for GIS input, Geo-Informations-Systeme, 6, 5, pp. 24-29.
82. WILKINSON, G. G., 1993 b, Neural networks: a new analysis tool for GIS and remote sensing. GIS Europe, 2, (October), 38-40.
83. WILKINSON, G. G., FEERENS, F., and KANELLOPOULOS, I., 1995 a, Integration of neural and statistical approaches in spatial data classification. Geographical Systems, 2, 1-20.
84. WILKINSON, G. G., FOLVING, S., KANELLOPOULOS, I., MCCORMICK, N., FULLERTON, K., and MÉGIER, J., 1995b. Forest mapping from multi-source satellite data using neural network classifiers -an experiment in Portugal, Remote Sensing Reviews, 12, pp. 83-106.
85. WILKINSON, G. G., KANELLOPOULOS, I., and MÉGIER, J., (EDITORS), 1995 c, Fractals in Geoscience and Remote Sensing (Luxembourg: Office for Official Publications of the European Communities, Report EUR 16092 EN, 348pp., Image Understanding Research Series Vol. 1).
86. WILKINSON, G. G., KANELLOPOULOS, I., MEHL, W., and HILL, J. 1993, Land cover mapping using combined Landsat Thematic Mapper imagery and ERS-1 Synthetic Aperture Radar imagery. Proceedings of the 12th. Pecora Memorial Conference entitled: Land Information from Space Based Systems, held at Sioux Falls, 24-26 August (Bethesda, Maryland: American Society for Photogrammetry and Remote Sensing), pp. 151-158.
87. WILKINSON, G. G., and MÉGIER, J. 1990, Evidential reasoning in a pixel classification hierarchy - a potential method for integrating image classifiers and expert system rules based on geographic context. International Journal of Remote Sensing, 11, 1963-1968.
88. WORBOYS, M. F., 1994, A unified model for spatial and temporal information. The Computer Journal, 37, 26-34.
89. WU, J.-K., CHENG, D.-S., WANG, W.-T., and CAI, D.-L. 1988. Model-based remotely-sensed imagery interpretation. International Journal Remote Sensing, 9, 1347-1356.
90. YOSHIDA, T., and OMATU, S., 1994, Neural network approach to land cover mapping. I.E.E.E. Transactions on Geoscience and Remote Sensing, 32, 1103-1109.