Download Free Environmental Data Management Book in PDF and EPUB Free Download. You can read online Environmental Data Management and write the review.

Focused on the mechanics of managing environmental data, this book provides guidelines on how to evaluate data requirements, assess tools and techniques, and implement an effective system. Moving beyond the hypothetical, Gerald Burnette illustrates the decision-making processes and the compromises required when applying environmental principles and practices to actual data. Managing Environmental Data explains the basic principles of relational databases, discusses database design, explores user interface options, and examines the process of implementation. Best practices are identified during each portion of the process. The discussion is summarized via the development of a hypothetical environmental data management system. Details of the design help establish a common framework that bridges the gap between data managers, users, and software developers. It is an ideal text for environmental professionals and students. The growth in both volume and complexity of environmental data presents challenges to environmental professionals. Developing better data management skills offers an excellent opportunity to meet these challenges. Gaining knowledge of and experience with data management best practices complements students’ more traditional science education, providing them with the skills required to address complex data requirements.
Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. - Introduces novel intelligent techniques needed to address environmental pollution for the well-being of the global environment - Offers perspectives on the design, development and commissioning of intelligent applications - Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies surrounding the monitoring and mitigation of environmental pollution - Puts forth insights on future generation intelligent pollution monitoring techniques
The report outlines key elements to consider in designing a program to create climate-quality data from satellites. It examines historical attempts to create climate data records, provides advice on steps for generating, re-analyzing, and storing satellite climate data, and discusses the importance of partnering between agencies, academia, and industry. NOAA will use this report-the first in a two-part study-to draft an implementation plan for climate data records.
The diverse nature of environmental problems mankind has encountered within the last decade has developed a new understanding of the nature of environmental processes. Currently, the environment is considered as a continuum of air, soil and water as the vital components for sustaining life on earth. The interactive nature of these components requires that the environment is managed and protected as a cohesive whole. This can only be accomplished through an integrated approach to environmental management. Besides the concept of environmental continuum, prospects for sustainable development of natural resources and the recent recognition of global climate change impacts have also necessitated such an integrated approach to environmental management. Two basic tools for integrated management of the environment are modeling and environmental data. Both tools were available and valid in the past; however, the recent requirements for integrated environmental management have also led to a significant evolution of both modeling procedures and data management systems.
Throughout the world a staggering amount of resources have been used to obtain billions of environmental data points. Some, such as meteorological data, have been organized for weather map display where many thousands of data points are synthesized in one compressed map. Most environmental data, however, are still widely scattered and generally not used for a systems approach, but only for the purpose for which they were originally taken. These data are contained in relatively small computer programs, research files, government and industrial reports, etc. This Conference was called to bring together some of the world's leaders from research centers and government agencies, and others concerned with environmental data management. The purpose of the Conference was to organize discussion on the scope of world environmental data, its present form and documentation, and whether a systematic approach to a total system is feasible now or in the future. This same subject permeated indirectly the Stockholm Conference on the environment, where, although no single recommendation came forth suggesting a consolidated environmental data pool, bank or network, each recommendation indicated that substantial environmental data needed to be obtained or needed to be pooled and analyzed from existing data sources.
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.
"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.
ENVIRONMENTAL MANAGEMENT SERIES The current expansion of both public and scientific interest in environ mental issues has not been accompanied by a commensurate production of adequate books, and those which are available are widely variable in approach and depth. The Environmental Management Series has been established with a view to co-ordinating a series of volumes dealing with each topic within the field in some depth. It is hoped that this Series will provide a uniform and quality coverage and that, over a period of years, it will build up to form a library of reference books covering most of the major topics within this diverse field. It is envisaged that the books will be of single, or dual authorship, or edited volumes as appropriate for respective topics. The level of presentation will be advanced, the books being aimed primarily at a research/consultancy readership. The coverage will include all aspects of environmental science and engineering pertinent to manage ment and monitoring of the natural and man-modified environment, as well as topics dealing with the political, t:conomic, legal and social con siderations pertaining to environmental management.
Professionals in environmental health and safety (EHS) management use statistics every day in making decisions. This book was created to provide the quantitative tools and techniques necessary to make important EHS assessments. Readers need not be statistically or mathematically inclined to make the most of this book-mathematical derivations are kept to a minimum and subjects are approached in a simple and factual manner, complemented with plenty of real-world examples. Chapters 1-3 cover knowledge of basic statistical concepts such as presentation of data, measurements of location and dispersion, and elementary probability and distributions. Data gathering and analysis topics including sampling methods, sampling theory, testing, and interference as well as skills for critically evaluating published numerical material is presented in Chapters 4-6. Chapters 7-11 discuss information generation topics-regression and correlation analysis, time series, linear programming, network and Gnatt charting, and decision analysis-tools that can be used to convert data into meaningful information. Chapter 12 features six examples of projects made successful through statistical approaches being applied. Readers can use these approaches to solve their own unique problems. Whether you are a EHS professional, manager, or student, Health, Safety, and Environmental Data Analysis: A Business Approach will help you communicate statistical data effectively.
The National Oceanic and Atmospheric Administration (NOAA) collects, manages, and disseminates a wide range of climate, weather, ecosystem and other environmental data that are used by scientists, engineers, resource managers, policy makers, and others in the United States and around the world. The increasing volume and diversity of NOAA's data holdings - which include everything from satellite images of clouds to the stomach contents of fish - and a large number of users present NOAA with substantial data management challenges. NOAA asked the National Research Council to help identify the observations, model output, and other environmental information that must be preserved in perpetuity and made readily accessible, as opposed to data with more limited storage lifetime and accessibility requirements. This report offers nine general principles for effective environmental data management, along with a number of more specific guidelines and examples that explain and illustrate how these principles could be applied at NOAA.