Full text: Proceedings, XXth congress (Part 2)

ul 2004 
5. CONCLUSION 
In this paper we compare 12 different interpolation 
methods. For each method, we analyze its 
applicability, algorithm, efficiency and advantage. 
There is no absolutely best method but only the 
optimal choice under certain circumstances. One 
should first review the characteristic and theorem of 
each method as well as the property and spatial 
analysis of data before he or she can successfully 
select a spatial interpolation method which is 
relatively best in certain situation. However, the 
outcome should be evaluated by conscientious 
experiences. 
References: 
l. Briggs IC. Machine Contouring Using Minimum 
785 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004 
Curvature [J], Geophysics, 1974,39(1):39. 
2. Barnett V. Interpreting multivariate data [M]. 
NewYork, 1981:21. 
3. Franke R. Scattered Data Interpolation: Test of 
Some Methods [J]. Mathematics of Computations, 
1982.33(457):181. 
4. Franke R, Nielson G. Smooth Interpolation of 
Large Sets of Scattered Data [J]. International 
Journal for Numerical Methods in Engineering, 
1980,15(2):1691. 
5. Lee DT, Schachter BJ. Two Algorithms for 
Constructing a Delaunay Triangulation, 
International Journal of Computer and Information 
Sciences [J].1980,9(3):219. 
6. SURFER on-line manual 
 
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.