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Author : Peng Liu,Zhe Zhang,Mohd Anul Haq,Yizhe Zhan
Publisher : Frontiers Media SA
Page : 192 pages
File Size : 40,6 Mb
Release : 2022-06-01
Category : Science
ISBN : 9782889762927
Author : Moses Eterigho Emetere
Publisher : Springer
Page : 227 pages
File Size : 52,6 Mb
Release : 2019-02-21
Category : Technology & Engineering
ISBN : 9783030134051
This book introduces methods of re-processing images to extract numerical information that can be used to quantify the observables in environmental modelling. Experiments or procedures that yield large images can be statistically or parametrically examined. Through the use of open source libraries, the book shows how ‘big data’ in the form of images or datasets can be comparatively analysed along same defined procedures or standards. This book helps to solve the challenges of discarding datasets that are relevant directly or indirectly to the research. The habit of screening datasets leads to the discard of over 90% of the original dataset or images generated in the experiments or procedure. If the images or datasets are generated under the same principles or conditions, then each measurement may be the narrative of unique events. The focus of this book is to enlighten researchers on how to analyse measurements with the aim of ensuring 100% utilization.
Author : Jiaping Wu,Junyu He,George Christakos
Publisher : Elsevier
Page : 504 pages
File Size : 49,9 Mb
Release : 2021-12-04
Category : Science
ISBN : 9780128163429
Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations introduces the notion of chronotopologic data analysis that offers a systematic, quantitative analysis of multi-sourced data and provides information about the spatial distribution and temporal dynamics of natural attributes (physical, biological, health, social). It includes models and techniques for handling data that may vary by space and/or time, and aims to improve understanding of the physical laws of change underlying the available numerical datasets, while taking into consideration the in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). It considers the synthesis of scientific theory-based methods (stochastic modeling, modern geostatistics) and data-driven techniques (machine learning, artificial neural networks) so that their individual strengths are combined by acting symbiotically and complementing each other. The notions and methods presented in Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Including real-world practical applications as well as practice exercises, this book is a comprehensive step-by-step tutorial of theory-based and data-driven techniques that will help students and researchers master data analysis and modeling in earth and environmental sciences (including environmental health and human exposure applications). Explores the analysis and processing of chronotopologic (i.e., space-time and spacetime) data that varies spatially and/or temporally, which is the case with the majority of data in scientific and engineering disciplines Studies the synthesis of scientific theory and empirical evidence (in its various forms) that offers a mathematically rigorous and physically meaningful assessment of real-world phenomena Covers a wide range of data describing a variety of attributes characterizing physical phenomena and systems including earth, ocean and atmospheric variables, environmental and ecological parameters, population health states, disease indicators, and social and economic characteristics Includes case studies and practice exercises at the end of each chapter for both real-world applications and deeper understanding of the concepts presented
Author : Anthony J. Jakeman,Alexey A. Voinov,Andrea E. Rizzoli,Serena H. Chen
Publisher : Elsevier
Page : 384 pages
File Size : 50,9 Mb
Release : 2008-09-11
Category : Science
ISBN : 0080915302
The complex and multidisciplinary nature of environmental problems requires that they are dealt with in an integrated manner. Modeling and software have become key instruments used to promote sustainability and improve environmental decision processes, especially through systematic integration of various knowledge and data and their ability to foster learning and help make predictions. This book presents the current state-of-the-art in environmental modeling and software and identifies the future challenges in the field. State-of-the-art in environmental modeling and software theory and practice for integrated assessment and management serves as a starting point for researchers Identifies the areas of research and practice required for advancing the requisite knowledge base and tools, and their wider usage Best practices of environmental modeling enables the reader to select appropriate software and gives the reader tools to integrate natural system dynamics with human dimensions
Author : Tanvir Islam,Prashant K. Srivastava,Manika Gupta,Xuan Zhu,Saumitra Mukherjee
Publisher : Springer Science & Business Media
Page : 275 pages
File Size : 55,8 Mb
Release : 2014-02-14
Category : Science
ISBN : 9789401786423
Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.
Author : Moses Eterigho Emetere,Esther Titilayo Akinlabi
Publisher : Springer Nature
Page : 239 pages
File Size : 54,5 Mb
Release : 2020-01-03
Category : Technology & Engineering
ISBN : 9783030362072
This book introduces numerical methods for processing datasets which may be of any form, illustrating adequately computational resolution of environmental alongside the use of open source libraries. This book solves the challenges of misrepresentation of datasets that are relevant directly or indirectly to the research. It illustrates new ways of screening datasets or images for maximum utilization. The adoption of various numerical methods in dataset treatment would certainly create a new scientific approach. The book enlightens researchers on how to analyse measurements to ensure 100% utilization. It introduces new ways of data treatment that are based on a sound mathematical and computational approach.
Author : Michael F. Goodchild,Louis T. Steyaert,Bradley O. Parks,Carol Johnston,David Maidment,Michael Crane,Sandi Glendinning
Publisher : John Wiley & Sons
Page : 536 pages
File Size : 42,5 Mb
Release : 1996-09-30
Category : Technology & Engineering
ISBN : 0470236779
GIS and Environmental Modeling: Progress and Research Issues Michael F. Goodchild, Louis T. Steyaert, Bradley O. Parks, Carol Johnston, David Maidment, Michael Crane, and Sandi Glendinning, Editors With growing pressure on natural resources and landscapes there is an increasing need to predict the consequences of any changes to the environment. Modelling plays an important role in this by helping our understanding of the environment and by forecasting likely impacts. In recent years moves have been made to link models to Geographical Information Systems to provide a means of analysing changes over an area as well as over time. GIS and Environmental Modeling explores the progress made to date in integrating these two software systems. Approaches to the subject are made from theoretical, technical as well as data stand points. The existing capabilities of current systems are described along with important issues of data availability, accuracy and error. Various case studies illustrate this and highlight the common concepts and issues that exist between researchers in different environmental fields. The future needs and prospects for integrating GIS and environmental models are also explored with developments in both data handling and modelling discussed. The book brings together the knowledge and experience of over 100 researchers from academic, commercial and government backgrounds who work in a wide range of disciplines. The themes followed in the text provide a fund of knowledge and guidance for those involved in environmental modelling and GIS. The book is easily accessible for readers with a basic GIS knowledge and the ideas and results of the research are clearly illustrated with both colour and black and white graphics.
Author : Andrew Skidmore
Publisher : CRC Press
Page : 268 pages
File Size : 43,6 Mb
Release : 2003-09-02
Category : Technology & Engineering
ISBN : 1134578709
Most government agencies and private companies are investing significant resources in the production and use of geographical data. The capabilities of Geographical Information Systems (GIS) for data analysis are also improving, to the extent that the potential performance of GIS software and the data available for analysis outstrip the abilities of managers and analysts to use and analyze the information. This is especially true for environmental applications. Here the need to keep up-to-date is essential for providing effective and efficient services. Environmental Modeling with GIS and Remote Sensing derives from a training course run by ITC for professionals and managers in the environmental sciences, detailing the applications of remote sensing and GIS for environmental modeling and assessment. It sets out the current research results and provides operational methods for environmental mapping and monitoring.
Author : Mike J. Barnsley
Publisher : CRC Press
Page : 433 pages
File Size : 41,9 Mb
Release : 2007-02-13
Category : Technology & Engineering
ISBN : 9781420021462
Increasingly used to represent climatic, biogeochemical, and ecological systems, computer modeling has become an important tool that should be in every environmental professional’s toolbox. Environmental Modeling: A Practical Introduction is just what it purports to be, a practical introduction to the various methods, techniques, and skills required for computerized environmental modeling. Exploring the broad arena of environmental modeling, the book demonstrates how to represent an environmental problem in conceptual terms, formalize the conceptual model using mathematical expressions, convert the mathematical model into a program that can be run on a desktop or laptop computer, and examine the results produced by the computational model. Equally important, the book imparts skills that allow you to develop, implement, and experiment with a range of computerized environmental models. The emphasis is on active engagement in the modeling process rather than on passive learning about a suite of well-established models. The author takes a practical approach throughout, one that does not get bogged down in the details of the underlying mathematics and that encourages learning through “hands on” experimentation. He provides a set of software tools and data sets that you can use to work through the various examples and exercises presented in each chapter, as well as presentational material and handouts for course tutors. Comprehensive and up-to-date, the book discusses how computational models can be used to represent environmental systems and illustrates how such models improve understanding of the ways in which environmental systems function.
Author : Sue Ellen Haupt,Antonello Pasini,Caren Marzban
Publisher : Springer Science & Business Media
Page : 418 pages
File Size : 46,7 Mb
Release : 2008-11-28
Category : Science
ISBN : 9781402091193
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.
Author : Thomas Huang,Tiffany C. Vance,Christopher Lynnes
Publisher : John Wiley & Sons
Page : 356 pages
File Size : 41,6 Mb
Release : 2022-11-22
Category : Science
ISBN : 9781119467571
Big Data Analytics in Earth, Atmospheric and Ocean Sciences SPECIAL PUBLICATIONS SERIES Big Data Analytics in Earth, Atmospheric, and Ocean Sciences An ever-increasing volume of Earth data is being gathered. These data are “big” not only in size but also in their complexity, different formats, and varied scientific disciplines. As such, big data are disrupting traditional research. New methods and platforms, such as the cloud, are tackling these new challenges. Big Earth Data Analytics explores new tools for the analysis and display of the rapidly increasing volume of data about the Earth. Volume highlights include: An introduction to the breadth of big earth data analytics Architectures developed to support big earth data analytics Different analysis and statistical methods for big earth data Current applications of analytics to Earth science data Challenges to fully implementing big data analytics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Author : Keith C. Clarke,Bradley O. Parks,Michael P. Crane
Publisher : Unknown
Page : 340 pages
File Size : 47,8 Mb
Release : 2002
Category : Science
ISBN : MINN:31951D02018967X
This book provides readers with the most comprehensive and authoritative treatment of the topic available. Topics covered include modeling frameworks, paradigms and approaches; model development, calibration and validation; dynamic systems modeling and four-dimensional GIS; and more. Includes case studies in GIS/EM. This book is intended for readers interested in advanced Geographic Information Systems, Spatial Data Processing, or Environmental Modeling.
Author : W K Michener,J W Brunt,S G Stafford
Publisher : CRC Press
Page : 582 pages
File Size : 48,7 Mb
Release : 1994-08-08
Category : Technology & Engineering
ISBN : 9781482272505
Most environmental studies are based upon data collected at fine spatial scales plots, sediments, cores, etc.. Furthermore, temporal scales of these studies have been relatively short days, weeks, months and few studies have exceeded three years duration the typical funding cycle.; Despite this history, environmental scientists are now being called
Author : Ashok N. Srivastava,Ramakrishna Nemani,Karsten Steinhaeuser
Publisher : CRC Press
Page : 354 pages
File Size : 47,5 Mb
Release : 2017-08-01
Category : Computers
ISBN : 9781315354460
From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.
Author : T. P. Singh,Dharmaveer Singh,R. B. Singh
Publisher : Springer Nature
Page : 237 pages
File Size : 46,9 Mb
Release : 2021-09-14
Category : Science
ISBN : 9789811647680
Globally, concerns for the environment and human well-being have increased as results of threats imposed by climate change and disasters, environmental degradation, pollution of natural resources, water scarcity and proliferation of slums. Finding appropriate solutions to these threats and challenges is not simple, as these are generally complex and require state-of-the-art technology to collect, measure, handle and analyse large volumes of varying data sets. However, the recent advances in sensor technology, coupled with the rapid development of computational power, have greatly enhanced our abilities to capture, store and analyse the surrounding physical environment. This book explores diverse dimensions of geo-intelligence (GI) technology in developing a computing framework for location-based, data-integrating earth observation and predictive modelling to address these issues at all levels and scales. The book provides insight into the applications of GI technology in several fields of spatial and social sciences and attempts to bridge the gap between them.
