Bayesian geostatistical models applied to malaria risk data quantify the environment-disease relations, identify significant environmental predictors of malaria transmission and provide model-based predictions of malaria risk together with their precision. These models are often based on the stationarity assumption which implies that spatial correlation is a function of distance between locatio...

When MCMC methods for Bayesian spatiotemporal modeling are applied to large geostatistical problems, challenges arise as a consequence of memory requirements, computing costs, and convergence monitoring. This article describes the parallelization of a reparametrized and marginalized posterior sampling (RAMPS) algorithm, which is carefully designed to generate posterior samples efficiently. The ...

Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014) using the Ordinary Kriging method based on ...

ATLAS OF ANTARCTICA: TOPOGRAPHIC MAPS FROM GEOSTATISTICAL ANALYSIS OF SATELLITE RADAR ALTIMETER DATA / Ute Christina Herzfeld. Berlin: Springer Verlag, 2004. xvi, 364 pp.: 169 illus., CD-ROM; 10.8 7.800. ISBN 3-540-43457-7 (cloth), US$159.00. Available from: Springer, 233 Spring Street, New York, NY 10013 USA. Toll-free tel. 1-800-SPRINGER. E-mail [email protected]. Web http://www.spr...

International Journal of Remote Sensing Publication details, including instructions for authors and subscription information: http://www.informaworld.com/smpp/title~content=t713722504 Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach C. Zhang a; W. Li a; D. Travis b a Department of Geography, Kent State University, b Department of Geography and Geology, Universit...

This paper proposes the use of Gaussian Mixture Models to estimate conditional probability density functions in an environmental risk mapping context. A conditional Gaussian Mixture Model has been compared to the geostatistical method of Sequential Gaussian Simulations and shows good performances in reconstructing local PDF. The data sets used for this comparison are parts of the digital elevat...

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. No...

Leaf area index (LAI) is a key parameter used to describe vegetation structures and is widely used in ecosystem biophysical process and vegetation productivity models. Many algorithms have been developed for the estimation of LAI based on remote sensing images. Our goal was to produce accurate and timely predictions of grassland LAI for the meadow steppes of northern China. Here, we compare the...

Catchments as space-time filters – a joint spatio-temporal geostatistical analysis of runoff and precipitation J. O. Skøien and G. Blöschl Institute for Hydraulic and Water Resources Engineering, Vienna University of Technology, Karlsplatz 13, 1040 Vienna, Austria Received: 29 March 2006 – Accepted: 21 April 2006 – Published: 12 June 2006 Correspondence to: J. O. Skøien ([email protected])

We aimed to map the probability of Schistosoma haematobium infection being >50%, a threshold for annual mass praziquantel distribution. Parasitologic surveys were conducted in Burkina Faso, Mali, and Niger, 2004-2006, and predictions were made by using Bayesian geostatistical models. Clusters with >50% probability of having >50% prevalence were delineated in each country.