Science-Based Spatiotemporal Statistics : Practical Guide with Environmental and Human Exposure Applications book cover
1st Edition

Science-Based Spatiotemporal Statistics
Practical Guide with Environmental and Human Exposure Applications

  • Available for pre-order. Item will ship after August 15, 2021
ISBN 9781482238037
August 15, 2021 Forthcoming by Chapman and Hall/CRC
350 Pages 15 B/W Illustrations

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Book Description

This book provides an introduction to the theoretical development and practical methodology of the so-called science-based spatiotemporal statistics. The book capitalizes on the significance of integrating different knowledge sources (physical, ecological, health, and social) into formal spatiotemporal statistics and provides an array of practical procedures for incorporating these sources into composite space-time analysis, modeling, and estimation/prediction.

Table of Contents

Introduction. A review of spatiotemporal statistics. Science-based vs. data-processing statistics. Space-time metrics: Euclidean (spatially isotropic and non-isotropic). Non-Euclidean (river network, gravity model, isomap). Spatiotemporal random field theory (S/TRF): Ordinary S/TRF. Generalized S/TRF. Spatiotemporal statistics of data sets. Standard two-point statistics: Ordinary covariance and variogram. Generalized covariance and variogram. Extension to multi-point statistics. Spatiotemporal exploratory analysis (pattern recognition). Empirical orthogonal method: Atmospheric and hydrological applications. Dynamic factor analysis: Ecological and environmental applications. Spatiotemporal clustering analysis: SaTscan and other works. Spatiotemporal statistics of differential equations. The analytical approach: Closed form expressions of physical and biophysical laws. Low- and high-order (diagrammatic) approximations of groundwater flow. The numerical approach: First order second moment (FOSM) method. Adjoint method. Spatiotemporal trend analysis. Non-parametric approaches. The generalized additive model. The Kernel smoothing method. Spatiotemporal regression.

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George Christakos is a distinguished professor and S.M. Birch Endowed Chair of the Department of Geography at San Diego State University, California, USA. He is also a Yongqian Chair Professor of the College of Environmental and Resource Sciences at Zhejiang University, China.

Hwa-Lung Yu is an associate professor of the Department of Bioenvironmental Systems Engineering at National Taiwan University, Taipei.