Terrain similarity characterizing approach based on two-dimensional continuous wavelet

TitleTerrain similarity characterizing approach based on two-dimensional continuous wavelet
Publication TypeConference Paper
Year of Publication2013
AuthorsYan, Shijiang, Jie Wang, and Fayuan Li
Refereed DesignationRefereed
Conference NameGeomorphometry 2013
Date Published2013
Conference LocationNanjing, China
AbstractCharacterizing and analysis of characteristics of terrain self-similarity, multi-scale and hierarchy structure has been a key point and hard problem. The traditional terrain analysis approaches based on window shaped filters is hard to overcome the nearsighted and unsteady effects. This paper design and realize a new approach to analyze these self-similarity characteristics after a complete analysis of the shortness of the state of the art. This paper also develops index to reveal terrain scale similarity. The paper takes Shannxi province as an example to calculate the scale similarity over the province. The mechanism between the scale issues of terrain landscape and landform geomorphometry is also been analyzed. The spatial distribution of the scale similarity is used to analysis the loess landscape pattern. The findings of the paper are as following: There is orderly distribution of the scale similarity over Shannxi province. The highest scale similarity appears in the northern areas with wolds and gullies, southeast areas with low hills. The lowest similarity appears in the in-between areas of sand and loess in the northern area of the province, the Guanzhong Basin et al. The similarity in the belt of Hanzhong Basin and and Ankang falls in between these two kinds of areas. The consistency of spatial distribution of the landform morphology and the scale similarity has proved that the two dimensional continuous wavelet based methods fulfill task of scale similarity characterizing in Shannxi province. The frequency domain based approach of characterizing terrain scale similarity is a well supplication of analysis toolsets of digital terrain analysis.
2.5
Your rating: None Average: 2.5 (4 votes)