Spatial interpolation methods are widely used in various fields and have been studied by several scholars with one or a few specific sampling datasets that do not reflect the complexity of the spatial characteristics and lead to conclusions that cannot be widely applied. In this paper, three factors that affect the accuracy of interpolation have been considered, i.e., sampling density, sampling...

This paper investigates the use of Kriging in random simulation when the simulation output variances are not constant. Kriging gives a response surface or metamodel that can be used for interpolation. Because Ordinary Kriging assumes constant variances, this paper also applies Detrended Kriging to estimate a non-constant signal function, and then standardizes the residual noise through the hete...

abstract guilan is a famous province in growing rice in iran. recently, due to shortage of water, farmers' desire to use groundwater in order to grow rice in northern part of iran has been increasing rapidly. the fact that rice is sensitive to water quality, caused concern about rice cultivation sustainability in the area, especially in drought years. this study was done to investigate the spat...

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

This paper presents the applications of Kriging spatial interpolation methods for meteorologic variables, including temperature and relative humidity, in regions of Vietnam. Three types of interpolation methods are used, which are as follows: Ordinary Kriging, Universal Kriging, and Universal Kriging plus Digital Elevation model correction. The input meteorologic data was collected from 98 grou...

Detailed maps of regional spatial distribution of soil organic carbon (SOC) are needed to guide sustainable soil uses and management decisions. Interpolation methods based on spatial auto-correlations, environmental covariates, or hybrid methods are commonly used to predict SOC maps. Many of these methods perform well for gentle terrains. However, it is unknown how these methods perform to capt...

Spatial interpolation methods have been applied to many disciplines, the ordinary kriging interpolation being one of the methods most frequently used. However, kriging comprises a computational cost that scales as the cube of the number of data points. Therefore, one most pressing problems in geostatistical simulations is that of developing methods that can reduce the computational time. Weight...

Geostatistika merupakan ilmu yang berfokus pada data spasial. Dalam geostatistika terdapat metode pendugaan untuk menangani variabel mempunyai nilai bervariasi dengan berubahnya lokasi atau tempat disebut teregionalisasi. Metode digunakan teregionalisasi kriging. ordinary kriging perlu memperhitungkan semivariogram. Hujan suatu proses jatuhnya air berasal dari awan ke bumi. di ukur memalui cura...

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...