Regionalization is to divide a set of spatial objects into a number of spatially contiguous regions while optimizing an objective function, which is usually a homogeneity (or etereogenity) measure of the derived regions. In this paper we propose a new regionalization method for spatial functional data by means of a Dynamic Clustering Algorithm. The method optimizes a criterion of spatial associ...

Autocorrelation has been viewed as a problem in telemetry studies because sequential observations are not independent in time or space, therefore violating assumptions for statistical inference. Yet nearly all ecological and behavioural data are autocorrelated in both space and time. We argue that there is much to learn about the structure of ecological and behavioural data from patterns of aut...

Geostatistics combined with GIS spatial technology was applied to analyze the time and spatial variability of pH in topsoil(0-20cm) for planted tobacco region in Sanmenxia district. The results indicated that the pH value range form 6.5 to 8.8 and meet to the need of produce high quality tobacco, but the pH value of partial region is high. The pH value accord with logarithm normal distribution,...

Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy pollutants around mines can provide scientific basis for control. The structure effect random semivariogram be used to determine reason spatial differences in content surface soil, coefficient variation regression analysis confirm that verification accuracy meets geostatistical...

Kriging is one of the most frequently used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM (Parallel Virtual Ma...

Kriging is one of the most often used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM. An example will show the...

This paper took the wheat field of typical alluvial soil area as the research site, aimed to explore the spatial pattern of the soil nutrients, such as soil available potassium, soil available phosphorus, soil organic matter (SOM) and soil alkali hydrolysable nitrogen. With the help of DGPS, a total of 104 topsoil(0–20cm) samples were collected. Based on classical statistics, research results i...