This introductory scholarly treatment explores the fundamentals of modern geostatistics, a
group of spatiotemporal concepts and methods related to the advancement of the epistemic …

The purpose of this paper is to stress the importance of a Bayesian/maximum-entropy view
toward the spatial estimation problem. According to this view, the estimation equations …

Trustonlymovement. Life happens at the level of events not of words. Trust movement. A.
Adler As its title suggests, the main goal of this book is the development of advanced fu-tions …

Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a
holistic, conceptual and quantitative framework for Environmental Health Modelling in space …

Abstract The Bayesian Maximum Entropy (BME) method of spatial analysis and mapping
provides definite rules for incorporating prior information, hard and soft data into the …

In this paper, a new data fusion-based methodology is presented for spatio-temporal (ST)
redesigning of Groundwater Level Monitoring Networks (GLMNs). The kriged maps of three …

Current soil process models require the most accurate values for each of their input
parameters at the finest spatial scale. Traditionally, soil property values are obtained either …

Soil moisture (SM) plays a fundamental role in the land–atmosphere exchange process.
Spatial estimation based on multi in situ (network) data is a critical way to understand the …

Comprehensive river water quality monitoring and assessment helps to identify emerging
water quality problems as well as developing sustainable water management strategies to …

This paper presents a new methodology for analyzing the spatiotemporal variability of water
table levels and redesigning a groundwater level monitoring network (GLMN) using the …