References
- 1.Castleman K R. 1998. Digital Image Processing. Beijing: Tsinghua University Press
- 2.Davies E R. 1990. Machine Vision: Theory, Algorithms, Practicalities. London, San Diego: Academic Press
- 3.Dey A and Bhattacharya R K. 2014. Monitoring of River Center Line and Width—a Study on River Brahmaputra. Journal of the Indian Society of Remote Sensing, 42(2): 475–482
- 4.Feyisa G L, Meilby H, Fensholt R and Proud S R. 2014. Automated Water Extraction Index: a New Technique for Surface Water Mapping using Landsat Imagery. Remote Sensing of Environment, 140: 23–35
- 5.Fu G, Zhao H R, Li C and Shi L M. 2014. A Method by Improved Circular Projection Matching of Tracking Twisty Road from Remote Sensing Imagery. Acta Geodaetica et Cartographica Sinica, 43(7): 724–730
- 6.Jasiewicz J and Metz M. 2011. A New GRASS GIS Toolkit for Hortonian Analysis of Drainage Networks. Computers and Geosciences, 37(8): 1162–1173
- 7.Jiang H, Feng M, Xiao T and Wang C Z. 2014. A Narrow River Extraction Method based on Linear Feature Enhancement in TM Image. Acta Geodaetica et Cartographica Sinica, 43(7): 705–710
- 8.Li H, Dai Z Y, Zhang L H and Jiang Z Y. 2011. Mathematical Morphology based Drainage Line Extraction from Remote Sensing Image. Geomatics and Information Science of Wuhan University, 36(8): 956–959
- 9.Liu R Y, Miao Q G, Huang B, Song J F and Debayle J. 2016. Improved Road Centerlines Extraction in High-resolution Remote Sensing Images using Shear Transform, Directional Morphological Filtering and Enhanced Broken Lines Connection. Journal of Visual Communication and Image Representation, 40: 300–311
- 10.Maboudi M, Amini J, Hahn M and Saati M. 2016. Road Network Extraction from VHR Satellite Images using Context Aware Object Feature Integration and Tensor Voting. Remote Sensing, 8(8): 637
- 11.McFeeters S K. 1996. The Use of the Normalized Difference Water Index (NDWI) in the Delineation of Open Water Features. International Journal of Remote Sensing, 17(7): 1425–1432
- 12.Meng L K, Guo S X, Li S. 2012. Summary on Extraction of Water Body from Remote Sensing Image and Flood Monitoring. Water Resources Informatization(3): 18–25
- 13.Meng L K and Lü Q F. 2015. Improved Orthogonal T-snake Model for Complex Water Boundary Extraction. Acta Geodaetica et Cartographica Sinica, 44(6): 670–677
- 14.Peng Y. 2008. Research and Realization of Skeleton Extracting Technique for 3D Modeling. Wuhan: Huazhong University of Science and Technology
- 15.Shen Z Y, Li Z B, Li P and Wu J H. 2009. Research on the Algorithms of the Digital Channel Network Extraction based on Digital Elevation Model. Journal of Water Resources and Water Engineering, 20(1): 20–23, 28
- 16.Stefanelli R and Rosenfeld A. 1971. Some Parallel Thinning Algorithms for Digital Pictures. Journal of the ACM (JACM), 18(2): 255–264
- 17.Tribe A. 1992. Automated Recognition of Valley Lines and Drainage Networks from Grid Digital Elevation Models: a Review and a New Method. Journal of Hydrology, 139(1): 263–293
- 18.Zeng H W, Li L J, Liu Y M, Li B and Zhang Y X. 2011. Accuracy Analysis of Multisource DEMs on Extracted River Networks and Drainage Basin by Arc Hydro Tools: a Case Study of Taoerhe River Basin. Journal of Geo-Information Science, 13(1): 22–31
- 19.Zheng X W, Xiong H J, Gong J Y and Yue L W. 2015. A Robust Channel Network Extraction Method Combining Discrete Curve Evolution and the Skeleton Construction Technique. Advances in Water Resources, 83: 17–27
- 20.Zhou S G, Chen C and Yue J P. 2014. Extracting Roads from High-resolution RS Images based on Shape Priors and Graph Cuts. Acta Geodaetica et Cartographica Sinica, 43(1): 60–65


