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Proceedings Paper

Statistical texture for contour interval choice of 1:50,000 DEMs
Author(s): MingLiang Luo; Guoan Tang; Shijiang Yan; Youfu Dong
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Paper Abstract

How to choose contour interval in different geomorphologic type areas is a challenging job. In the paper a statistical texture method is used to measure the distance between Loess Hillock and Loess Ridge in Loess Plateau, which geomorphologic types are hills. The result shows that when the two areas classified into 25 classes or so with the contour interval 15 and 19 individually, the class separability seems more distinct than less than 25 classes. The results also shows that when the number of class is bigger than 25, the class separability decrease instead of increasing correspondingly. It seems that the too many classes used may produce more details in cost of decreasing class separability. And in the seven statistical variables, the number of polygons is the most stable while the mean grayscale, the standard variation of grayscale are the most sensitive when the contour interval changes. The result indicates that the contour interval mainly influences by elevation and relative relief without more information which being dominant. By aid of an appropriate contour interval, the landform features can be easily extracted and is very helpful in delaminate the topography.

Paper Details

Date Published: 10 November 2008
PDF: 11 pages
Proc. SPIE 7146, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses, 71462U (10 November 2008); doi: 10.1117/12.813200
Show Author Affiliations
MingLiang Luo, Nanjing Normal Univ. (China)
Institute of Mountain Hazards and Environment (China)
Guoan Tang, Nanjing Normal Univ. (China)
Shijiang Yan, Nanjing Normal Univ. (China)
Youfu Dong, Nanjing Normal Univ. (China)


Published in SPIE Proceedings Vol. 7146:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Advanced Spatial Data Models and Analyses
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang, Editor(s)

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