In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson'...

Global Moran’s I and local Moran’s Ii are the most commonly used test statistics for spatial autocorrelation in univariate map patterns or in regression residuals. They belong to the general class of ratios of quadratic forms for whom a whole array of approximation techniques has been proposed in the statistical literature, such as the prominent saddlepoint approximation by Offer Lieberman (199...

spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

Visualizing correlations, i.e., the tendency of uncertain data values at different spatial positions to change contrarily or according to each other, allows inferring on the possible variations of structures in the data. Visualizing global correlation structures, however, is extremely challenging, since it is not clear how the visualization of complicated long-range dependencies can be integrat...

BACKGROUND Investigation of global clustering patterns across regions is very important in spatial data analysis. Moran's I is a widely used spatial statistic for detecting global spatial patterns such as an east-west trend or an unusually large cluster. Here, we intend to improve Moran's I for evaluating global clustering patterns by including the weight function in the variance, introducing a...

introduction the knowledge about spatial variability of precipitation is a key issue for regionalization in hydro-climatic studies. measurements of meteorological parameters by the traditional methods require a dense rain gauge network. but, due to the topography and cost problems, it is not possible to create such a network in practice. in these cases the spatial distribution pattern of precip...

A variety of image registration techniques have been investigated for applications such as image analysis, fusion, compression, enhancement, and creating mosaics. In particular, robust registration is a key component of successful multi-frame processing aimed at super-resolution or high dynamic range imaging of space objects. Image registration techniques are broadly categorized as global (area...