for optimum planning, utilization, and management of lands, recognition of spatial variability of soil properties is necessary. this research was conducted to evaluate spatial variability of soil properties in 5000 ha of arsenjan plain in fars province. for this purpose, soil salinity, ph, particle size percentage, sodium, potassium, and organic carbon (oc) were measured on a systematic squared...

The analysis of spatial data occurs in many disciplines and covers a wide variety activities. Available techniques for such analysis include spatial interpolation which is useful for tasks such as visualization and imputation. This paper proposes a novel approach to interpolation using space-filling curves. Two simple interpolation methods are described and their ability to interpolate is compa...

Spatial interpolation is an important feature of a Geographic Information System, which is the procedure used to estimate values at unknown locations within the area covered by existing observations. In this paper, we propose a conservative spatial interpolation technique that incorporates the advantages of local interpolation, Euclidean interpolation, and conservative fuzzy reasoning. The main...

In this paper, we investigate the application of data mining to existing techniques for quality control/anomaly detection on weather sensor observations. Specifically we adapt the popular Barnes Spatial interpolation method to use time series distance rather than spatial distance to develop an online algorithm that uses readings from similar stations based on current and historical observations...

the present study was carried out to evaluate three interpolation methods including weighted moving average (wma) with the power of 2 and 3, kriging and cokriging methods. data of 23 wells in mazandaran province were collected in fall and spring 2006. seven parameters including electrical conductivity (ec), ph, total dissolved solids (tds), sodium adsorption ratio (sar), total hardness (th), ch...

As the development of earth sciences and cross-disciplinary, it’s more and more meaningful and valuable to analyze and estimate precipitation spatial distribution. Precipitation spatial information is important in many fields, such as water resource management, drought and flood disaster predication, and regional sustainable development. It’s unrealistic to get the accurate predication of a par...

among the usual interpolation methods, kriging and co-kriging are frequently used in the interpolation of precipitation data as one the best linear unbiased estimators, despite these advantages, there models show smoothness representation and because they are based on regional averages of the data, they predict maximum and minimum values   lower and higher than real values respectively. therefo...

This study presents a method to estimate land surface temperature (LST) by calibrating spatial interpolation using satellite-derived surface emissivity. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Kriging, and Cokriging were tested to interpolate LST in southern New England using ground temperatures measured at national weather stations (NWS) in summer...