Mapping of settlements in high-resolution satellite imagery using high performance computing

GeoJournal

Volumn 69, Issue 1-2, 2007, Pages 119-129

  Cheriyadat, Anil ^a   Bright, Eddie ^a   Potere, David ^a   Bhaduri, Budhendra ^a  

^a OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

Classification; Edge; High performance computation; Land cover; Remote sensing; Texture; Urban

Indexed keywords

EDGE DETECTION; IMAGE CLASSIFICATION; REMOTE SENSING; URBAN PLANNING;

HIGH PERFORMANCE COMPUTATION; LAND COVER;

SATELLITE IMAGERY;

ALGORITHM; DATABASE; LAND COVER; POPULATION DISTRIBUTION; POPULATION MODELING; SATELLITE IMAGERY; SETTLEMENT PATTERN; URBAN REGION;

EID: 35648929458     PISSN: 03432521     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10708-007-9101-0     Document Type: Conference Paper

References (27)

1. Augusteijn, M. F., Clemens, L. E., & Shaw, K. A. (1995). Performance evaluation of texture measures for ground cover identification in satellite images by means of neural network classifier. IEEE Transactions on Geoscience and Remote Sensing, 33, 616-626.
2. Bhaduri, B., Bright, E., Coleman, P., & Dobson, J. (2002). LandScan: Locating people is what matters. Geoinfomatics, 5, 34-37.
3. Burns, G., Daoud, R., & Vaigl, J. (1994). LAM: An open cluster environment for MPI. Proceedings of Supercomputing Symposium (pp. 379-386). University of Toronto.
4. Chaudhuri, B. B., & Sarkar, N. (1995). Texture segmentation using fractal dimension. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(1), 72-77.
5. Chen, C. H., Pau, L. F., & Wang, P. S. P. (1998). The handbook of pattern recognition and computer vision (2nd ed., pp. 207-248). World Scientific Publishing Co.
6. Chellappa, R., & Chatterjee, S. (1985). Classification of textures using Gaussian Markov random fields. IEEE Transactions on Acoustics, Speech, and Signal Processing, 33(4), 959-963.
7. Clausi, D. A., & Zhao, Y. (2002). An advanced computational method to determine co-occurrence probability texture features. IEEE Proceedings of Geoscience and Remote Sensing Symposium, 4, 2453-2455.
8. Dekker, R. J. (2003). Texture analysis and classification of ERS SAR images for map updating of urban areas in The Netherlands. IEEE Transactions on Geoscience and Remote Sensing, 41(9, Part 1), 1950-1958.
9. De Martinao, M., Causa, F., & Serpico, S. B. (2003). Classification of optical high resolution images in urban environment using spectral and textural information. IEEE Proceedings of Geoscience and Remote Sensing Symposium, 1, 467-469.
10. Dobson, J., Bright, E., Coleman, P., Durfee, R., & Worley, B. (2000). LandScan: A global population database for estimating populations at risk. Photogrammetric Engineering & Remote Sensing, 66(7), 849-857.
11. Friedl, M., McIver, D., Hodges, J., Zhang, X., Muchoney, D., Strahler, A., Woodcock, A., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., & Schaaf, C. (2002). Global land cover mapping from MODIS: Algorithms and early results. Remote Sensing of Environment, 83, 287-302.
12. Gropp, W., Lusk, E., Doss, N., & Skjellum, A. (1996). A high performance, portable implementation of the MPI Message-passing interface standard. Parallel computing, 22(6), 789-828.
13. Haralick, R. M., Shanmugam, K., & Dinstein, I., (1973). Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3, 610-621.
14. Haralick, R. M. (1979). Statistical and structural approaches to texture. Proceedings of IEEE, 67(5), 786-803.
15. Haas, P. W., & Resch, M. M., (2005). High performance computing in science and engineering. International Symposium on Computer Architecture and High Performance Computing, 10-17.
16. Jain, A. K., Farrokhnia, F., & Alman, D. H., 1990. Texture Analysis of Automotive Finishes. In Proceedings of SME Machine Vision Applications Conference (pp. 1-16). Detroit, MI.
17. Loveland, T. R., Reed, B. C., Brown, J. F., Ohlen, D. O., Zhu, J, Yang, L., & Merchant, J. W. (2000). Development of a Global Land Cover Characteristics Database and IGBP DISCover from 1-km AVHRR Data. International Journal of Remote Sensing, 21(6/7), 1303-1330.
18. Mugler, J., Naughton, T., & Scott, S. L. (2005). OSCAR meta-package system. International Symposium on High Performance Computing Systems and Applications, 353-360.
19. National Academies Press (2006). Priorities for GEOINT research at the national geospatial-intelligence agency, http://www.nap.edu
20. Quinlan, R. (1996). Introduction of decision trees. Machine Learning, 1(1), 81-106.
21. Rellier, G., Descombes, X., Falzon, F., & Zerubia, J. (2004). Texture feature analysis using a Guass-Markov model in hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 42(7), 1543-1551.
22. Simard, M., Saatchi, S. S., & De Grandi, G. (2000). The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest. IEEE Transactions on Geoscience and Remote Sensing, 38(5, Part 1), 2310-2321.
23. Tahir, M. A., Bouridane, A., Kurugollu, F., & Amira, A. (2004). Accelerating the computation of GLCM and Haralick texture features on reconfigurable hardware. International Conference on Image Processing, 5, 2857-2860.
24. Tobin, K. W., Bhaduri, B. L., Bright, E. A., Cheriyadat, A., Karnowski, T. P., Palathingal, P. J., Potok, T. E., & Price, J. R. (2006). Automated feature generation in large-scale geospatial libraries for content-based indexing. Journal of Photogrammetric Engineering and Remote Sensing, 72(5).
25. Tucker, C. J., Denelle, M. G., & Jon, D. D. (2004). NASA's Global Orthorectified Landsat Data Set. Photogrammetric Engineering & Remote Sensing, 70(3), 313-322.
26. Vogelmann, J., Sohl, T., & Howard. S. (1998). Regional characterization of land cover using multiple sources of data. Photogrammetric Engineering and Remote Sensing, 64(1), 45-57.
27. Woods, B., Clymer, B., Saltz, J., & Kurc, T. (2004). A parallel implementation of 4-dimensional haralick texture analysis for disk-resident image datasets. Proceedings of the ACM/IEEE SC2004 (pp. 48-48).