Extraction of small river information based on object-oriented classification

Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery

Volumn 45, Issue 7, 2014, Pages 237-244

  Liu, Wei ^a   Wang, Conghua ^a   Zhao, Erping ^a   Du, Hejuan ^a  

^a XIZANG MINZU UNIVERSITY   (China)

Author keywords

Hierarchical extraction; Loess hilly and gully region; Multispectral remote sensing; Object oriented classification; Small waters

Indexed keywords

IMAGE SEGMENTATION; LANDFORMS; MAPS; MATHEMATICAL MORPHOLOGY; RIVERS; SEDIMENTS; WATER RESOURCES; WATER SUPPLY SYSTEMS;

HIERARCHICAL EXTRACTION; IDENTIFICATION ACCURACY; LOESS HILLY AND GULLY REGION; MULTISPECTRAL REMOTE SENSING; OBJECT ORIENTED CLASSIFICATION; OBJECT-ORIENTED SEGMENTATION; SPECTRAL INTERFERENCE; SUPERVISED CLASSIFICATION;

EXTRACTION;

EID: 84904397355     PISSN: 10001298     EISSN: None     Source Type: Journal    
DOI: 10.6041/j.issn.1000-1298.2014.07.037     Document Type: Article

References (28)

1. 2013.
2. 2012.
3. Shen Zhanfeng, Xia Liegang, Li Junli, et al. Automatic and high-precision extraction of rivers from remotely sensed images with Gaussian normalized water index[J]. Journal of Image and Graphics, 2013, 18(4): 421-428. (in Chinese)
4. Ouma Y O, Tateishi R. A water index for rapid mapping of shoreline changes of five east African rift valley lakes: an empirical analysis using LANDSAT TM and ETM+ data[J]. International Journal of Remote Sensing, 2006, 27(15): 3153-3181.
5. Shen Li, Tang Hong, Wang Shidong, et al. River extraction from the high resolution sensing image based on spatially correlated pixels template and adaboost algorithm[J]. Acta Geodaeticaet Cartographica Sinica, 2013, 42(3): 344-350. (in Chinese)
6. Yang Shuwen, Xue Chongsheng, Liu Tao, et al. A method of small water information automatic extraction from TM remote sensing images[J]. Acta Geodaeticaet Cartographica Sinica, 2010, 39(6): 611-617. (in Chinese)
7. Lira J. Segmentation and morphology of open water bodies from multispectral images[J]. International Journal of Remote Sensing, 2006, 27(18): 4015-4038.
8. Zhu Changming, Luo Jiancheng, Shen Zhanfeng, et al. River linear water adaptive auto-extraction on remote sensing image aided by DEM[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(2): 277-283. (in Chinese)
9. Luo Jiancheng, Sheng Yongwei, Shen Zhanfeng, et al. Automatic and high-precise extraction for water information from multispectral images with the step-by-step iterative transformation mechanism[J]. Journal of Remote Sensing, 2009, 13(4): 610-615. (in Chinese)
10. Liu H, Jezek K C. Automated extraction of coastline from satellite imagery by integrating canny edge detection and locally adaptive threshold methods[J]. International Journal of Remote Sensing, 2004, 25(5): 937-958.
11. 2004.
12. 2008.
13. Lacoste C, Descombes X, Zerubia J. Unsupervised line network extraction in remote sensing using a poly line process[J]. Patten Recognition, 2010, 43(4): 1631-1641.
14. Deng Ruru, He Yingqing, Qin Yan, et al. Measuring pure water absorption coefficient in the near-infrared spectrum (900-2 500 nm)[J]. Journal of Remote Sensing, 2012, 16(1): 192-206. (in Chinese)
15. Deng Ruru, He Yingqing, Qin Yan, et al. Pure water absorption coefficient measurement after eliminating the impact of suspended substance in spectrum from 400 nm to 900 nm[J]. Journal of Remote Sensing, 2012, 16(1): 174-191.(in Chinese)
16. Xu Hanqiu. A study on information extraction of water body with the modified normalized difference water index(MNDWI)[J]. 2005, 9(5): 589-595.(in Chinese)
17. Ri Pyongsop, Ma Zhangbao, Qi Qingwen, et al. Cloud and shadow removal from LANDSAT TM data[J]. Journal of Remote Sensing, 2012, 16(1): 192-206. (in Chinese)
18. Guo Jianhong, Tian Qingjiu, Wu Junzhao. Study on multispectral detecting shadow areas and a theoretical model of removing shadows from remote sensing images[J]. Journal of Remote Sensing, 2006, 10(2): 151-158. (in Chinese)
19. Zhu Gaolong, Liu Yibo, Ju Weimin, et al. Evaluation of topographic effects on four commonly used vegetation indices[J]. Journal of Remote Sensing, 2013, 17(1): 210-234. (in Chinese)
20. He Yajuan, Pan Xuebiao, Pei Zhiyuan, et al. Estimation of LAI and yield of sugarcane based on SPOT remote sensing data[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(5): 226-231. (in Chinese)
21. Mathieu R, Freeman C, Aryal J. Mapping private gardens in urban areas using object-oriented techniques and very high-resolution satellite imagery[J]. Landscape and Urban Planning, 2007, 81(3): 179-192.
22. Zhou W, Troy A, Grove M. Object-based land cover classification and change analysis in the Baltimore metropolitan area using multi temporal high resolution remote sensing data[J]. Sensors, 2008, 8(3): 1613-1636.
23. Xu Wenning, Mei Shuli, Wang Pengxin, et al. Improved Chan-Vese model and its application on high resolution remote sensing image segmentation[J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(3): 180-183.(in Chinese)
24. Guo Lin, Pei Zhiyuan, Wu Quan, et al. Application of method and process of object-oriented land use-cover classification using remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(7): 194-198. (in Chinese)
25. Benz U C, Peter H, Gregor W, et al. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J]. ISPRS Journal of Photogrammetry & Remote Sensing, 2004, 58(3-4): 239-258.
26. 2012.
27. Foody G M. Status of land cover classification accuracy assessment[J]. Remote Sensing of Environment, 2002, 80(1): 185-121.
28. Mai Kaile, Zhang Wenhui. Object-oriented classification approach for remote sensing imagery information extraction in loess hilly-gully region[J]. Transactions of the Chinese Society for Agricultural Machinery, 2011, 42(4): 153-158. (in Chinese)