Studies on Time Series Applications in Environmental Sciences
Studies on Time Series Applications in Environmental Sciences

Author: Alina Bărbulescu

Publisher: Springer

Published: 2016-03-12

Total Pages: 197

ISBN-13: 3319304364

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Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code.

Multivariate Time Series Analysis in Climate and Environmental Research
Multivariate Time Series Analysis in Climate and Environmental Research

Author: Zhihua Zhang

Publisher: Springer

Published: 2017-11-09

Total Pages: 293

ISBN-13: 3319673408

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This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

Author: Richard Chandler

Publisher: John Wiley & Sons

Published: 2011-03-25

Total Pages: 348

ISBN-13: 111999196X

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The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

Advanced Environmental Monitoring with Remote Sensing Time Series Data and R
Advanced Environmental Monitoring with Remote Sensing Time Series Data and R

Author: Alexandra Gemitzi

Publisher: CRC Press

Published: 2019-11-20

Total Pages: 117

ISBN-13: 0429557140

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This book provides a step-by-step guide on how to use various publicly available remotely sensed time series data sources for environmental monitoring and assessment. Readers will learn how to extract valuable information on global changes from a 20-year collection of ready-to-use remotely sensed data through the free open statistical software R and its geographic data analysis and modeling tools. The case studies are from the Mediterranean region—a designated hot spot regarding climate change effects. Each chapter is dedicated to specific remote sensing products chosen for their spatial resolution. The methods used are adapted from large-scale to smaller-scale problems for different land cover areas. Features Includes real-world applications of environmental remotely sensed data Analyzes the advantages and restrictions of each data source Focuses on a wide spectrum of applications, such as hydrology, vegetation changes, land surface temperature, fire detection, and impacts Includes R computer codes with explanatory comments and all applications use only freely available remotely sensed data Presents a step-by-step processing through open source GIS and statistical analysis software Advanced Environmental Monitoring with Remote Sensing Time Series Data and R describes and provides details on recent advances concerning publicly available remotely sensed time series data in environmental monitoring and assessment. This book is a must-have practical guide for environmental researchers, professionals, and students.

Hydrologic Time Series Analysis
Hydrologic Time Series Analysis

Author: Deepesh Machiwal

Publisher: Springer Science & Business Media

Published: 2012-03-05

Total Pages: 316

ISBN-13: 9400718616

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There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.

Time Series Data Analysis in Oceanography
Time Series Data Analysis in Oceanography

Author: Chunyan Li

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 483

ISBN-13: 1108474276

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Textbook for students and researchers in oceanography and Earth science on theory and practice of time series analysis using MATLAB.

Ecology, Genetics and Evolution of Metapopulations
Ecology, Genetics and Evolution of Metapopulations

Author: Ilkka A. Hanski

Publisher: Academic Press

Published: 2004-05-17

Total Pages: 717

ISBN-13: 0080530699

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Ecology, Genetics and Evolution of Metapopulations is acollection of specially commissioned articles that looks at fragmented habitats, bringing together recent theoretical advances and empirical studies applying the metapopulation approach. Several chapters closely integrate ecology with genetics and evolutionary biology, and others illustrate how metapopulation concepts and models can be applied to answer questions about conservation, epidemiology, and speciation. The extensive coverage of theory from highly regarded scientists and the many substantive applications in this one-of-a-kind work make it invaluable to graduate students and researchers in a wide range of disciplines. - Provides a comprehensive and authoritative account of all aspects of metapopulation biology, integrating ecology, genetics, and evolution - Developed by recognized experts, including Hanski who won the Balzan Prize for Ecological Sciences - Covers novel applications of the metapopulation approach to conservation

Artificial Intelligence Methods in the Environmental Sciences
Artificial Intelligence Methods in the Environmental Sciences

Author: Sue Ellen Haupt

Publisher: Springer Science & Business Media

Published: 2008-11-28

Total Pages: 418

ISBN-13: 1402091192

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How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Environmental Data Analysis with MatLab
Environmental Data Analysis with MatLab

Author: William Menke

Publisher: Elsevier

Published: 2011-09-02

Total Pages: 282

ISBN-13: 0123918863

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"Environmental Data Analysis with MatLab" is for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. This book teaches the basics of the underlying theory of data analysis, and then reinforces that knowledge with carefully chosen, realistic scenarios. MatLab, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. The book, though written in a self-contained way, is supplemented with data sets and MatLab scripts that can be used as a data analysis tutorial. It is well written and outlines a clear learning path for researchers and students. It uses real world environmental examples and case studies. It has MatLab software for application in a readily-available software environment. Homework problems help user follow up upon case studies with homework that expands them.