Baltic sea algae analysis using Bayesian spatial statistics methods

Spatial heterogeneity of nutrients in the Baltic Proper, Baltic Sea

The Baltic Proper shows many signs of eutrophication. Nutrient changes over time have been discernable, and also within the Sea there are large spatial patterns. Present study analyses the spatial patterns of dissolved inorganic nitrogen and phosphorus as well as dissolved silicate (DSi) in the euphotic zone for the period 1990-2001. The focus is on the spatial heterogeneity with the aim to ide...

Analysis of Drought Spatial Statistics in Iran

Drought is one of the environmental events and an inseparable part of climatic fluctuations. This phenomenon is one of the main characteristics of the various climates. Awareness of spatiotemporal behavior is effective in land planning. The spatial statistical methods provide the means by which they analyze the spatial patterns of random variables such as precipitation. In this study, using the...

SAR-Based Wind Resource Statistics in the Baltic Sea

Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR) images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps and from 10 meteorological masts, established specifically for wind energy in the study area, are compar...

Bayesian Thinking in Spatial Statistics

In the sections below we review basic motivations for spatial statistical analysis, review three general categories of data structure and associated inferential questions, and describe Bayesian methods for achieving inference. Our goal is to highlight similarities across spatial analytic methods, particularly with regards to how hierarchical probability structures often link approaches develope...

Bayesian Prediction in Spatial Data Analysis