The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

We explore and compare different methods for the spatial clustering of geostatistical data. A new methodology based on the likelihood is proposed and compared to the approach by Allard and Monestiez (1999). Both methods are compared on a heavy metal concentration data set in the Swiss Jura.

The knowledge about the spatial distribution of soil organic carbon stock (SOCS) helps in sustainable land-use management and ecosystem functioning. No such study has been attempted complex topography land use Himalayas, which is associated with great heterogeneity uncertainties. Therefore, this digital mapping (DSM) was used to predict evaluate SOCS using advanced geostatistical methods a mach...

Raster based digital elevation models (DEM) are the basis of some of the most important GIS workflows: hydrologic modeling, site suitability, and cost path analysis. While there are several techniques for generating digital elevation models (DEMs), none of them can produce a true elevation surface. Locally varying measurement error and the inexactness of the interpolation methods contribute to ...

BACKGROUND Geostatistical techniques are now available to account for spatially varying population sizes and spatial patterns in the mapping of disease rates. At first glance, Poisson kriging represents an attractive alternative to increasingly popular Bayesian spatial models in that: 1) it is easier to implement and less CPU intensive, and 2) it accounts for the size and shape of geographical ...

The first step in statistical data analysis is to verify three data features: dependency, stationarity, and distribution. If data are independent, it makes little sense to analyze them geostatisticaly. If data are not stationary, they need to be made so, usually by data detrending and data transformation. Geostatistics works best when input data are Gaussian. If not, data have to be made to be ...

Kriging techniques are used to map national public health data routinely reported to the Centers for Disease Control and Prevention (CDC). Although choropleth maps are commonly used to display geographic and temporal disease-related events for political (state and county) jurisdictions, kriged maps may offer opportunities to enhance visual communication of event patterns over time. As a geostat...