ABSTRACT Optimal scale selection is the key step of the slope segmentation. Taking three geomorphological units in different parts of the loess as test areas and 5 m-resolution DEMs as original test date, this paper employed the changed ROC-LV (Lucian, 2010) in judging the optimal scales in the slope segmentation process. The experiment results showed that this method is effective in determining the optimal scale in the slope segmentation. The results also showed that the slope segmentation of the different geomorphological units require different optimal scales because the landform complexity is varied. The three test areas require the same scale which could distinguish the small gully because all the test areas have many gullies of the same size, however, when come to distinguish the basins, since the complexity of the three areas is different, the test areas require different scales.
Cite this paper
M. Zhao, F. Li and G. Tang, "Optimal Scale Selection for DEM Based Slope Segmentation in the Loess Plateau," International Journal of Geosciences, Vol. 3 No. 1, 2012, pp. 37-43. doi: 10.4236/ijg.2012.31005.
 Z. H. Zhang, “Regional Geologic and Physiognomy Cha- racteristic as Well as Contemporary Erosion Process of Loess Plateau,” Acta Geologic Sinica, Vol. 55, No. 4, 1981, pp. 308-319.
 W. N. Chen, “Statistical Analysis of Gepmorphic Conditions Effection Loess Erosion in Loess Ridge-Hill Gully Region,” Scientia Geographical Sinica, Vol. 8, No. 4, 1998, pp. 323-329.
 Q. Li, Z. C. Lu and B. Y. Yuan, “Quantitative Study Of the Stage of Geomorphological Evolution,” Acta Geogra- phica Sinica, Vol. 45, No. 1, 1990, pp. 110-120.
 X. Z. Ma, Z. C. Lu and D. S. Jin, “Evolution and Pissipa- tive Structure in the Drainage-Geomorphic System,” Acta Geographica Sinica, Vol. 48, No. 4, 1993, pp. 367-376.
 D. S. Jin, “Experiment and Simulation in Geomophology,” Earthquake Press, Beijin, 1995.
 L. P. Zhang and Z. Z. Ma, “The Research on the Relation between Gully Density and Cutting Depth in Different Drainage Landform Evolution Periods,” Geographical Re- search, Vol. 17, No. 3, 1998, pp. 273-278.
 X. N. Xiao, L. Z. Cui, C. Wang, et al., “Analysis of Spa- tial Data for Simulating the Development Process of Topographic Feature of Watershed,” Scientia Geographical Sinica, Vol. 24, No. 4, 2004, pp. 439-443.
 G. A. Tang, F. Y. Li, X. J. Liu, et al., “Research on the Slope Spectrum of the Loess Plateau,” Science in China Series E: Technological Sciences, Vol. 51, Supp. 1, 2008, pp. 175-185. doi:10.1007/s11431-008-5002-9
 Y. Zhou, G. A. Tang, X. Yang, et al., “Positive and Nega- tive Terrains on Northern Shaanxi Loess Plateau,” Journal of Geographical Sciences, Vol. 20, No. 1, 2010, pp. 64- 76. doi:10.1007/s11442-010-0064-6
 W. N. Chen, “Statistical Analysis of Gepmorphic Condi- tions Effection Loess Erosion in Loess Ridge-Hill Gully Region,” Scientia Geographical Sinica, Vol. 8, No. 4, 1998, pp. 323-329.
 F. Y. Li, “DEM and Image Based Loess Slope Segmenta- tion,” 3rd International Congress on Image and Signal Processing, Yantai, 16-18 October 2010, pp. 2534-2538.
 E. H. Hammond, “Analysis of Properties in Landform Geo-Graphy: An Application to Broadscale Landform Mapping,” Annals of the Association of American Geo- graphers, Vol. 54, 1964, pp. 11-19.
 R. Dikau, E. E. Brabb and R. M. Mark, “Landform Clas- sification of New Mexico by Computer,” US Geological Survey, US Department of the Interior, Open-File Report, 1991.
 P. T. Giles and S. E. Franklin, “An Automated App- Roach to the Classification of the Slope Units Using Di- gital Data,” Geomorphology, Vol. 21, No. 3, 1998, pp. 251-264. doi:10.1016/S0169-555X(97)00064-0
 L. Dragut and T. Blaschke, “Automated Classification of Landform Elements Using Object-Based Image Analy- sis,” Geomorphology, Vol. 81, 2006, pp. 330-344.
 P. M. Atkinson and P. J. Curran, “Defining an Optimal Size of Support for Remote Sensing Investigations,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 33, No. 3, 1995, pp. 768-776. doi:10.1109/36.387592
 C. Woodcock and A. Strahler, “The Factor of Scale in Remote Sensing,” Remote Sensing of Environment, Vol. 21, No. 3, 1987, pp. 311-332.
 H. Yu, S.-Q. Zhang and B. Kong, “Optimal Segmentation Scale for Object-oriented Remote Sensing Image Classi- fication,” Journal of Image and Graphics, Vol. 15, No. 2, 2010, pp. 352-360.
 D. Marceau and G. Hay, “Remote Sensing Contributions to the Scale Issue,” Canadian Journal of Remote Sensing, Vol. 25, No. 4, 1999, pp. 357-366.
 T. S. Roger, S. Georges and L. Jean, “Using Color, Texture, and Hierarchical Segmentation for High-Resolution Remote Sensing,” ISPRS Journal of Photogrammetric & Remote Sensing, Vol. 63, No. 2, 2008, pp. 156-168.
 J. L. Silvan-Cardenas, L. Wang and F. B. Zhan, “Repre- senting Geographical Objects with Scale-Induced Indeter- Minate Boundaries: A Neural Network-Based Data Mo- del,” International Journal of Geographical Information Science, Vol. 23, No. 3, 2009, pp. 295-318.
 C. E. Woodcock, A. H. Strahler and D. L. B. Jupp, “The Use of Variograms in Remote Sensing II: Real Digital Images,” Remote Sensing of Environment, Vol. 25, No. 5, 1988, pp. 349-379. doi:10.1016/0034-4257(88)90109-5
 J. Schiewe, L. Tufte and M. Ehlers, “Potential and Prob- lems of Multi-Scale Segmentation Methods in Remote Sensing,” Zeitschrift fur Geoinformationssysteme, Vol. 6, No. 6, 2001, pp. 34-39.
 P. Aplin, “On Scales and Dynamics in Observing the Environment,” International Journal of Remote Sensing, Vol. 27, No. 11, 2006, pp. 2123-2140.
 P. Fisher, “The Pixel: A Snare and a Delusion,” Interna- tional Journal of Remote Sensing, Vol. 18, No. 15, 1997, pp. 679-685. doi:10.1080/014311697219015
 T. Blaschke and J. Strobl, “What’s Wrong with Pixels? Some Recent Developments Interfacing Remote Sensing and GIS,” Zeitschrift fur Geoinformationssysteme, Vol. 14, No. 6, 2001, pp. 12-17.
 G. Smith, et al., “UK Land Cover Map Production through the Generalisation of OS MasterMap(R),” Cartographic Journal, Vol. 44, No. 3, 2007, pp. 276-283.
 T. Blaschke, S. Lang and G. Hay, “Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications,” Springer-Verlag, Berlin, 2008.
 G. Meinel and M. Neubert, “A Comparison of Segmen- tation Programs for High Resolution Remote Sensing Da- ta,” Proceedings of 20th ISPRS Congress, Istanbul, 2004.
 L. Drǎgu?, D. Tiede and S. R. Levick, “ESP: A Tool to Estimate Scale Parameter for Multiresolution Image Seg- mentation of Remotely Sensed Data,” International Jour- nal of Geographical Information Science, Vol. 24, No. 6, 2010, pp. 859-871. doi:10.1080/13658810903174803
 C. E. Woodcock, A. H. Strahler and D. L. B. Jupp, “The Use of Variograms in Remote Sensing I: Scene Models and Simulated Images,” Remote Sensing of Environment, Vol. 25, No. 20, 1998, pp. 323-348.
 M. Kim and T. Warner, “Estimation of Optimal Image Object Size for the Segmentation Stands with Multispectral IKONOS Imagery,” In: T. Blaschke, S. Lang and G. J. Hay, Eds., Object-Based Image Analysis-Spatial Concepts for Knowledge Driven Remote Sensing Application, Springer, Berlin, 2008, pp. 291-307.