Comparison Of Interpolation Methods Research Articles

Mapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation Methods

Mapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation Methods

Mapping of Temperature Trend Slope in Iran′s Zayanderud River Basin: A Comparison of Interpolation Methods

The spatial distribution of daily, nightly and mean temperature trend in Iran′s Zayanderud river basin was carried out in this study by applying three approaches of interpolation including Inverse Distance Weighting (IDW), Multiple Linear Regression (MLR) and integration of these two methods (IDW+MLR). In this paper, t-test and statistical measures including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), systematic Root Mean Square Error (RMSEs) and unsystematic Root Mean Square Error (RMSEu) were used to evaluate the performance of approaches. This study reveals that temperature trends are inversely correlated with the altitude. All three interpolation methods overestimate in the prediction of daily and mean temperature trend and underestimate in estimating nightly temperature trend. Among three methods, IDW is the most accurate and precise in predicting daily and mean temperature trends. IDW is the most accurate and IDW+MLR is the most precise method to estimate nightly temperature trend. The MLR method for estimating nightly, mean temperature trend and the IDW method for estimating daily temperature trend have the lowest systematic error.

Comparison of Interpolation Methods in the Diagnosis of Carpal Tunnel Syndrome

Comparison of Interpolation Methods in the Diagnosis of Carpal Tunnel Syndrome

Comparison of interpolation methods and image correlation in the collection of data for digital elevation model

Digital Relief Model (DRM) is the name used officially in Croatia, and we distinguish between the original and derived DRM. Referring to the regular raster structure of elevations stored in the derived DRM, the term digital elevation model (DEM) was used for this model. Three geomorphometrically different landscapes have been tested. The elevation points were created using two methods, interpolation from the data obtained in the photogrammetric survey and image correlation, in two resolutions (5x5 and 25x25 meters). The paper presents the differences in the application of two methods of calculating DEM. The causes of differences discussed and the relative estimation of the accuracy of each method elaborated by comparing the height of points on new models with the heights on original DRM. The recommendation for the usage of the acceptable method is given related to the accuracy, the speed of data collection and a higher degree of automation.

Сравнение интерполяционных методов масштабирования растровых изображений

Сравнение интерполяционных методов масштабирования растровых изображений

Espacialização da erosividade das chuvas no Brasil a partir de séries sintéticas de precipitação

The aim of this study was to spatialize the rainfall erosivity in Brazil from synthetic precipitation series. The study was conducted in Brazil, using data from 142 stations pluviographic. The erosivity were calculated from actual daily rain gauge records and from pluviographic daily synthetic series, generated from the ClimaBR software. A computer routine was specifically developed to identify rain erosive considered. For the spatial distribution of erosivity the methods of inverse distance interpolation power and ordinary, simple and universal kriging were evaluated. Comparison of interpolation methods was done by means of statistical measures, average percentage error, mean absolute error, root mean square error and Willmott index. The results indicate that the inverse power method of distance presented better performance to interpolate the erosivity relative to the kriging method.

A comparison of interpolation methods on the basis of data obtained from a bathymetric survey of Lake Vrana, Croatia

Abstract. The bathymetric survey of Lake Vrana included a wide range of activities that were performed in several different stages, in accordance with the standards set by the International Hydrographic Organization. The survey was conducted using an integrated measuring system which consisted of three main parts: a single-beam sonar HydroStar 4300 and GPS devices; a Ashtech ProMark 500 base, and a Thales Z-Max® rover. A total of 12 851 points were gathered. In order to find continuous surfaces necessary for analysing the morphology of the bed of Lake Vrana, it was necessary to approximate values in certain areas that were not directly measured, by using an appropriate interpolation method. The main aims of this research were as follows: (a) to compare the efficiency of 14 different interpolation methods and discover the most appropriate interpolators for the development of a raster model; (b) to calculate the surface area and volume of Lake Vrana, and (c) to compare the differences in calculations between separate raster models. The best deterministic method of interpolation was multiquadric RBF (radio basis function), and the best geostatistical method was ordinary cokriging. The root mean square error in both methods measured less than 0.3 m. The quality of the interpolation methods was analysed in two phases. The first phase used only points gathered by bathymetric measurement, while the second phase also included points gathered by photogrammetric restitution. The first bathymetric map of Lake Vrana in Croatia was produced, as well as scenarios of minimum and maximum water levels. The calculation also included the percentage of flooded areas and cadastre plots in the case of a 2 m increase in the water level. The research presented new scientific and methodological data related to the bathymetric features, surface area and volume of Lake Vrana.

Comparison of interpolation methods for precipitation fields using the physically based and spatially distributed model of river runoff on the example of the Gharesou basin, Iran

Spatial variability of input data for distributed and physically based models has a significant impact on the results of model simulations. The objective of this study was to compare the methods of precipitation spatial interpolation, namely, the method of Thiessen polygons (THI), Inverse Distance Weighting (IDW), and Universal Kriging (UNK) using the physically based and spatially distributed hydrological WetSpa model. The paper also illustrates how these methods allow more accurate estimation of river discharge simulated with the WetSpa model for the Gharesou basin in Iran. Daily data of 22 precipitation gaging stations were used in this study. In order to simulate hydrological processes for the basin, especially river runoff, we used the precipitation data interpolated with THI, IDW, and UNK as well as digital information on topography, the land use and soil type of the basin. For comparing three interpolation methods, they were applied to the simulation of river discharge using the WetSpa model. Simulated daily values of water discharge in the basin were compared with observational data. The quality of data simulated using these three methods was very good or excellent. According to the efficiency criterion of Aggregated Measure (0.879), the application of THI method provided more accurate forecast of river discharge than that of IDW and UNK methods.

Comparison of Interpolation Methods in Bayer CFA Image Compression Based on Structure Separation and APBT-JPEG

Comparison of Interpolation Methods in Bayer CFA Image Compression Based on Structure Separation and APBT-JPEG

Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ~15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.

On the comparison of interpolation methods

A study of different cubic interpolation kernels in the frequency domain is presented that reveals novel aspects of both cubic spline and cubic convolution interpolation. The kernel used in cubic convolution is of finite support and depends on a parameter to be chosen at will. At the Nyquist frequency, the spectrum attains a value that is independent of this parameter. Exactly the same value is found at the Nyquist frequency in the cubic spline interpolation. If a strictly positive interpolation kernel is of importance in applications, cubic convolution with the parameter value zero is recommended.

Comments on “A Comparison of Interpolation Methods for Sparse Data: Application to Wind and Concentration Fields”

Comments on “A Comparison of Interpolation Methods for Sparse Data: Application to Wind and Concentration Fields”