Space-time geostatistics for geography : a case study of radiation monitoring across parts of Germany
Geostatistical methods in geography part II : applications in physical geography. Special issue
Bremen ; Geostatistics ; Germany ; Krigeage ; Model ; Niedersachsen ; North Rhine Westfalia ; Observation network ; Radiation ; Rhineland-Palatinate ; Spatial variation ; Stochastic model
This paper first summarizes the main concepts of space-time geostatistics. The AA. use here a model-based geostatistical approach to characterize space-time variability. The space-time variable of interest is treated as a sum of independent
Assessing heavy metal contamination in soils of the Zagreb region (Northwest Croatia) using multivariate geostatistics
Topsoil samples were collected in the Zagreb area (Northwest Croatia) and the total contents of trace and major elements were determined. A multivariate geostatistical analysis was used to estimate soil chemical composition variability. Factorial
Burgos ; Castilla-León ; Cenozoic ; Erosion surface ; Geographical information system ; Geostatistics ; Model ; Palaeogeography ; Spain ; Vertical movement
The AA. have developed a method to reconstruct palaeorelief by means of detailed geomorphological and geological studies, geostatistical tools, GIS and a DEM. This method has been applied to the Sierra de Atapuerca (NE Duero Basin) allowing to model
a three-dimensional reconstruction of the relief evolution from the Middle Miocene to the present. The modelling procedure is based on geostatistical recovery of the palaeosurfaces characteristic of each geomorphological evolution stage, using polynomial
England ; Geochemistry ; Geostatistics ; Model ; Remote sensing ; Soil ; Soil properties ; Thematic mapping ; United Kingdom
The AA. have analysed the joint spatial variation of the gamma signal and the soil geochemical data using multivariate geostatistical methods. The results support the expectation that radiometric signals for K and Th provide information on parent
Czech Republic ; Flood ; Geographical information system ; Geomatics ; Geostatistics ; Human impact ; Hydrology ; River basin
The article presents application of geoinformatic and geostatistical techniques in finding relations between observed consequences of the extreme flood in August 2002 and the set of casual factors - anthropogenic transformation of the landscape
Central Europe ; Europe ; Exceptional event ; Flood ; Geomatics ; Geostatistics ; Impact ; Landscape
A complex impacts of environmental changes in landscape and consequences of extreme floods. The solution is based on geostatistical approach and applies to the Otava river basin located in the zone of extreme floods. The situation mapping in August
variability of soil organic matter (SOM) was characterized using geostatistics, which consider the randomized and structured nature of spatial variables and the spatial distribution of the samples. The results confirm that erosion appears as a redistribution
The main objective of this research was to validate the geopedological mapping methodology by statistical and geostatistical methods in the Borujen region, Central Iran. This study demonstrated that, when comparing the same factors from sample
The application of geostatistics in grain size trend analysis : a case study of eastern Beibu Gulf
China ; Coastal dynamics ; Coastal environment ; Geostatistics ; Grain size distribution ; Pacific Ocean ; Sediment transport ; Sedimentology ; South China Sea ; Trend surface
After applying geostatistical analysis to the mean size, sorting and skewness for the sediment samples collected from the eastern Beibu Gulf, the AA. compared the semivariograms of these 3 parameters by using different interpolation distance
The AA. chose the major valleys of the Adriatic foothills (central Italy), affected since Late Miocene by a differential tectonic uplift which is still active. In particular, (i) they applied the geostatistical analysis to reconstruct the original
Geostatistical estimations of bathymetric LiDAR errors on rivers
Bathymetry ; Channel geometry ; Error ; France ; Gard ; Geostatistics ; Languedoc-Roussillon ; LiDAR ; Methodology ; River bed ; Statistical bias ; Stream
The AA. designed a methodology to assess the quality of LiDAR topographical data within rivers using a specific geostatistical method that conducts upscaling as well as interpolation of reference data that takes into account uncertainties