A thoroughly contemporary treatment of a substantial interdisciplinary inter
Trade Review
"This is an extremely well-composed book, offering an interdisciplinary exposure to the concepts and methods that are very valuable to perform environmental and ecological data analysis. The contributors are recognized experts in the topics of their writing...Noteworthy features in this book are introducing uncertainty, anisotropy and non-stationarity, threshold exceedance, coenospace, stochasticity, tail-down models, entropy-based design among others...I highly recommend this book to environmental, climate, statistics and computing researchers and practicing professionals."
- Ramalingam Shanmugam, JSCS, Aug 2020
Table of Contents
Introduction. Methodology for Statistical Analysis of Environmental Processes. Basics of modeling for environmental processes. Time series methodology. Dynamic models. Geostatistical modeling for environmental processes. Point patterns. Data fusion. Analysis of Extremes. Environmental sampling methods. Zero-inflation modeling and hurdle models. Ordination methods. Topics in Ecological Processes. Species distribution models – Plants. Species distribution models - Animals. Demography. Modeling traits. Ecology of infectious diseases. Wildfires and fire recovery. Modeling of streams. Topics in Environmental Exposure. Modeling environmental contaminants. Data fusion for exposure. Modeling other exposures and modeling personal exposure. Preferential sampling with regard to exposure levels. Dynamic source apportionment. Dynamics of environmental epidemiology. Connecting exposure to outcome. Experimental design for environmental epidemiology. Topics in Climatology. Trends in climatology. Climate models. Spatial analysis for climatology. Remote sensing - the statistical contribution. Data assimilation. Spatial extremes with application to climate and environmental exposure. Paleoclimate and paleoecology. Detection and attribution. Effects of climate change on health effects.
