A key problem in environmental monitoring is the spatial interpolation. The main current approach in spatial interpolation is geostatistical. Geostatistics is neither the only nor the best spatial interpolation method. Actually there is no “best” method, universally valid. Choosing a particular method implies to make assumptions. The understanding of initial assumption, of the methods used, and...

so far several methods have been developed for mapping and interpolation of isohyets.one of the recently accepted methods is geographically weighting regression which is suitable for evaluation of spatial heterogeneity of dependent variable by using local regressions. in order to evaluate annually precipitation spatial variation, this study was conducted in gilan province which precipitation is...

Rainfall data is useful in many fields such as urban management, agriculture, and so on. Spatial interpolation is widely used to interpolation continue rainfall data from discrete rainfall gauges. The uncertainty in spatial interpolation is change in different region. Paper focus on urban small area of Beijing city, Xicheng District and analyses uncertainty of spatial interpolation from four as...

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 propose two adaptive interlaced-to-progressive conversion techniques in which the adequacy of the estimated motion vector is evaluated. If the motion vector is unlikely to give a good temporal motion compensated interpolation result, spatial interpolation is favored or selected to avoid temporal artifacts. In the rst proposed interlaced-to-progressive conversion technique, cal...

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...

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...