Title :
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
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;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0872-4
DOI :
10.1109/RSETE.2012.6260656
