Title :
Research on DEM interpolation algorithm adaptability with local terrain features
Author_Institution :
Inst. of Geospatial Inf., Inf. Eng. Univ., Zhengzhou, China
Abstract :
For the vast majority of the DEM interpolation algorithms, the interpolation process is carried out in the local area, which is largely dependent on terrain features of the dataset of sampling points within the local area. This paper selects surface roughness and spatial distribution indicators to establish the descriptive model of local terrain features, which is then used to describe the characteristics of the data set of the sampling point within the local area. Then, it uses K means clustering analysis and residuals comparative analysis to study the correlation of surface roughness indicators and spatial distribution indicators to DEM interpolation algorithm. The corresponding conclusions contribute to selecting the adaptability of local terrain features of DEM interpolation algorithm.
Keywords :
geophysical techniques; interpolation; surface roughness; DEM interpolation algorithm adaptability; clustering analysis; descriptive model; interpolation process; largely dependent terrain features; local area; local terrain feature adaptability; residual comparative analysis; sampling point data set characteristics; sampling point dataset; spatial distribution indicators; surface roughness indicator correlation; Accuracy; Algorithm design and analysis; Clustering algorithms; Graphical models; Interpolation; Rough surfaces; Surface roughness; Adaptability; Interpolation Algorithm; K Means Clustering Analysis; Local Terrain Features; Residuals Comparative Analysis; Spatial distribution; Surface Roughness;
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
Conference_Location :
Kaifeng
DOI :
10.1109/Geoinformatics.2013.6626194