Settlement extraction in the North China Plain using Landsat and Beijing-1 multispectral data with an improved watershed segmentation algorithm

International Journal of Remote Sensing

Volumn 31, Issue 6, 2010, Pages 1411-1426

  Wang, Lei ^a   Gong, Peng ^a,b   Ying, Qing ^a   Yang, Zhenzhong ^a   Cheng, Xiao ^a   Ran, Qiong ^c  

^a BEIJING NORMAL UNIVERSITY   (China)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c Beijing Landview Mapping Information Technology Co Ltd   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY; EXTRACTION; IMAGE ENHANCEMENT; INFRARED DEVICES;

HIGH QUALITY IMAGES; LANDSAT ENHANCED THEMATIC MAPPER PLUS (ETM+) IMAGE; LANDSAT THEMATIC MAPPER IMAGES; MULTI-SPECTRAL DATA; NEAR INFRARED BAND; SEGMENTATION RESULTS; SPATIAL RESOLUTION; WATERSHED SEGMENTATION ALGORITHM;

IMAGE SEGMENTATION;

ALGORITHM; DATA INTERPRETATION; LANDSAT THEMATIC MAPPER; MULTISPECTRAL IMAGE; NEAR INFRARED; SATELLITE DATA; SATELLITE IMAGERY; SEGMENTATION; SPATIAL RESOLUTION;

BEIJING [CHINA]; CHINA; HEBEI;

EID: 77951111555     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160903475332     Document Type: Article

References (27)

1. AL-KHUDHAIRY, D.H.A., CARAVAGGI, I. and GLADA, S., 2005, Structural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques. Photogrammetric Engineering and Remote Sensing, 71, pp. 825-837.
2. BENZ, U.C., 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 and Remote Sensing, 58, pp. 239-258.
3. BIENIEK, A. and MOGA, A., 2000, An efficient watershed algorithm based on connected components. Pattern Recognition, 33, pp. 907-916.
4. FORSTER, B.C., 1985, An examination of some problems and solutions in monitoring urban areas from satellite platforms. International Journal of Remote Sensing, 6, pp. 139-151.
5. GAO, H., LIN, W., XUE, P. and SIU, W.C., 2006, Marker-based image segmentation relying on disjoint set union. Signal Processing: Image Communication, 21, pp. 100-112.
6. GONG, P., 2006, Information extraction. In Manual of Remote Sensing: Remote Sensing of Human Settlements, 3rd edn, M. Ridd and A. Renz (Eds), pp. 275-334 (Bethesda, MD: American Society for Photogrammetry and Remote Sensing).
7. GONG, P. and HOWARTH, P.J., 1990, The use of structural information for improving land-cover classification accuracies at the rural-urban fringe. Photogrammetric Engineering and Remote Sensing, 56, pp. 67-73
8. GONG, P. and HOWARTH, P.J., 1992, Frequency-based contextual classification and grey-level vector reduction for land-use identification. Photogrammetric Engineering and Remote Sensing, 58, pp. 423-437.
9. GONG, P., MARCEAU, D. and HOWARTH, P.J., 1992, A comparison of spatial feature extraction algorithms for land-use mapping with SPOT HRV data. Remote Sensing of Environment, 40, pp. 137-151.
10. HARIS, K., EFSTRATIADIS, S.N., MAGLAVERAS, N. and KATSAGGELOS, A.K., 1998, Hybrid image segmentation using watersheds and fast region merging. IEEE Transactions on Image Processing, 7, pp. 1684-1699.
11. JENSEN, J.R. and TOLL, D.L., 1982, Detecting residential land-use development at the urban fringe. Photogrammetric Engineering and Remote Sensing, 48, pp. 629-643.
12. MALPICA, N., ORTUNO, J.E., and SANTOS, A., 2003, A multichannel watershed-based algorithm for supervised texture segmentation. Pattern Recognition Letters, 24, pp. 1545-1554.
13. OAPOS-CALLAGHAN, R.J. and BULL, D.R., 2005, Combined morphological-spectral unsupervised image segmentation. IEEE Transactions on Image Processing, 14, pp. 49-62.
14. OSMA-RUIZ, V., GODINO-LLORENTE, J.I., SANCHEZ-LECHÓN, N. and GÓMEZ-VILDA, P., 2007, An improved watershed algorithm based on efficient computation of shortest paths. Pattern Recognition, 40, pp. 1078-1090.
15. RIDD, M. (Ed.), 2006, Manual of Remote Sensing: Remote Sensing of Human Settlements, 3rd edn, A. Renz (Ed.) (Bethesda, MD: American Society for Photogrammetry and Remote Sensing).
16. SETO, K.C. and FRAGKIAS, M., 2005, Quantifying spatiotemporal patterns of urban land use changes with four cities of China with time series landscape metrics. Landscape Ecology, 20, pp. 871-888.
17. SETO, K.C., KAUFIMANN, R.K. and WOODCOCK, C.E., 2000, Landsat reveals China's farmland reserves, but they're vanishing fast. Nature, 406, pp. 121.
18. SHACKELFORD, A.K. and DAVIS, C.H., 2003, A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas. IEEE Transactions on Geoscience and Remote Sensing, 41, pp. 2354-2363.
19. SHAFARENKO, L., PETROU, M., and KITTLER, J., 1997, Automatic watershed segmentation of randomly textured color images. IEEE transactions on Image Processing, 6, pp. 1530-1544.
20. STUCKENS, J., COPPIN, P.R. and BAUER, M.E., 2000, Integrating contextual information with per-pixel classification for improved land cover classification. Remote Sensing of Environment, 71, pp. 282-296.
21. SUN, H., YANG, J. and REN, M., 2005, A fast watershed algorithm based on chain code and its application in image segmentation. Pattern Recognition Letters, 26, pp. 1266-1274.
22. VINCENT, L. and SOILLE, P., 1991, Watersheds in digital spaces: an efficient algorithm based onimmersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13, pp. 583-598.
23. WALKER, J.S. and BRIGGS, J.M., 2007, An object-oriented approach to urban forest mapping in Phoenix. Photogrammetric Engineering and Remote Sensing, 73, pp. 577-583.
24. WANG, D., 1997, A multiscale gradient algorithm for image segmentation using watershelds. Pattern Recognition, 30, pp. 2043-2052.
25. WANG, L., GONG, P. and BIGING, G.S., 2004, Individual tree crown delineation and treetop detection in high spatial resolution aerial imagery. Photogrammetric Engineering and Remote Sensing, 70, pp. 351-367.
26. YU, Q., GONG, P., CLINTON, N., BIGING, G. and SCHIROKAUER, S., 2006, Object-based detailed vegetation mapping using high spatial resolution imagery. Photogrammetric Engineering and Remote Sensing, 72, pp. 799-811.
27. ZHA, Y., GAO, J. and NI, S., 2003, Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, pp. 583-594.