Comparative analysis of spatial interpolation methods of different field measurements for cognitive radio

2017 ◽  
Author(s):  
K. Bhaskar Reddy ◽  
P. Venkata Ramana ◽  
K. Sumiya
Keyword(s):  
Comparative Analysis ◽  
Cognitive Radio ◽  
Spatial Interpolation ◽  
Field Measurements ◽  
Interpolation Methods ◽  
Spatial Interpolation Methods

scholarly journals Comparative Analysis of Spatial Interpolation Methods in the Mediterranean Area: Application to Temperature in Sicily

Water ◽  
2015 ◽  
Vol 7 (12) ◽  
pp. 1866-1888 ◽  
Author(s):  
Annalisa Piazza ◽  
Francesco Conti ◽  
Francesco Viola ◽  
Emanuele Eccel ◽  
Leonardo Noto
Keyword(s):  
Comparative Analysis ◽  
Spatial Interpolation ◽  
Mediterranean Area ◽  
Interpolation Methods ◽  
The Mediterranean ◽  
Spatial Interpolation Methods

scholarly journals A COMPARATIVE ANALYSIS OF DIFFERENT DEM INTERPOLATION METHODS IN GIS: CASE STUDY OF RAHOVEC, KOSOVO

2019 ◽  
Vol 45 (5) ◽  
pp. 43-48 ◽  
Author(s):  
Besim Ajvazi ◽  
Kornél Czimber
Keyword(s):  
Comparative Analysis ◽  
Real World ◽  
Spatial Interpolation ◽  
Kriging Interpolation ◽  
Surface Model ◽  
Control Points ◽  
Data Set ◽  
The Real ◽  
Interpolation Methods ◽  
Spatial Interpolation Methods

Geographic Information System (GIS) uses geospatial databases as a model of the real world. Since we are speaking of the real world this entails that in many cases the information about the Earth’s surface is highly important. Therefore, the generation of a surface model is significant. Basically, the quality of the Digital Elevation Model (DEM) depends on the source data or techniques used to obtain them. However, different spatial interpolation methods used for the same data may provide different results. This paper compares the accuracy of different spatial interpolation methods such as IDW, Kriging, Natural Neighbor and Spline. Since interpolation is essential in DEM generation, then is important to do a comparative analysis of such methods to find out which one provides more accurate results. The DEM data set used is from an aero photogrammetric surveying. According to this data set, three scenarios are performed for each of the methods. Selected random control points are derived from the base data set. The first example includes 10% of randomly selected control points, the second example includes 20%, and the third example includes 30%. The Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) are calculated. We find out that results do not have much difference; however, the most accurate results are derived from the Spline and Kriging interpolation methods.

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