Points Group of Topographical Feature Based on SOFM

Author

Tian Jian ; Tang Gou-an ; Zhou Yi

Author_Institution

Key Lab. of Virtual Geographic Environ., Nanjing Normal Univ., Nanjing, China

fYear

2012

fDate

1-3 June 2012

Firstpage

1

Lastpage

4

Abstract

Spatial pattern of points group about topographical landscape is important topic for geographical cognition. This paper applied improved self-organizing feature maps method for researching the pattern of peaks, and cluster statistic parameter is generalized distance calculated both spatial and attribute information about points group. This method is employed for Terrain analysis about the Loess Plateau. Experimental result is showed that improved SOFM is effective method for analyzing points group of complex topographical features.

Keywords

geographic information systems; geophysics computing; self-organising feature maps; terrain mapping; Loess Plateau; attribute information; cluster statistic parameter; complex topographical features; geographical cognition; points group spatial pattern; self-organizing feature maps method; spatial information; terrain analysis; topographical landscape; Educational institutions; Information science; Neural networks; Neurons; Spatial databases; Surface topography;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4673-0872-4

Type

conf

DOI

10.1109/RSETE.2012.6260656

Filename

6260656