Given the above model of stationary random spatial effects { ( ) : } s s R   , our ultimate objective is to apply these concepts to spatial models involving global trends, ( ) s  , i.e., to spatial stochastic models of the form, ( ) ( ) ( ) , Y s s s s R      . In continuous spatial data analysis, the most fully developed models of this type focus on spatial prediction, where values of ...

Recently, spatial data set for fine zone scale becomes more important in urban planning. However, social or economic activity data such as transportation or production output are often difficult to get in the fine zone scale, due to the difficulties in survey. Comparing to these data, demographic data obtained in national census is able to easily get, so then an area interpolation by a regressi...

During recent years, oak decline has been widely spread across Brant’s oak (Quercus Brantii Lindl.) stands in the Zagros Mountains, Western Iran, which caused large-area forest dieback in several sites. Mapping the intensity and spatial distribution of forest dieback is essential for developing management and control strategies. This study evaluated a range of geostatistical and interpolation m...

drought monitoring is a fundamental component of drought risk management. it is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables. in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolation of spatially referenced data and the prediction of values...