Mastering Data Analysis with R

Gain clear insights into your data and solve real-world data science problems with R – from data munging to modeling and visualization

Preface R has become the lingua franca of statistical analysis, and it's already actively and heavily used in many industries besides the academic sector, where it originated more than 20 years ago. Nowadays, more and more businesses are adopting R in production, and it has become one of the most commonly used tools by data analysts

Exercise eBook Learning ArcGIS Pro

Create, Analyze, Maintain, and Share 2D and 3D Maps With Powerful Tools of ArcGIS Pro

Preface Esri’s ArcGIS Platform is the premiere GIS solution for those wishing to build a fully functional and scalable GIS. ArcGIS includes many integrated components, such as desktop applications, databases, image and web servers, cloud applications, and data along with mobile and web applications. ArcGIS Pro is Esri’s latest addition to this already amazing GIS platform. 

Learning ArcGIS Pro

ArcGIS Pro is a 64-bit desktop GIS application that makes use of a modern ribbon interface. This means that it has the ability to make full use of modern computer hardware while at the same time presenting users with an easy-to-use and intuitive interface. It contains powerful tools for visualizing and analyzing 2D and 3D data. This book will take you from software installation to performing geospatial analysis. It is packed with how-to use for a host of commonly performed tasks. You start by learning how to download and install the software, including hardware limitations and recommendations.

Administering ArcGIS for Server

Installing and configuring ArcGIS for Server to publish, optimize, and secure GIS services

Foreword GIS is a mature industry, with its roots in the late 60s in forestry and county polygon maintenance through vector topology (others such as GRASS and IDRISI concentrated on the raster domain). Storing location and attribute information has been a challenge, not only since the early days of severely limited computing power and storage space, but even today in the management of ever-growing spatial and tabular repositories. 

Administering ArcGIS for Server

This has been handled in several ways: two tenors being Esri Arc/Info separating the spatial and the tabular repositories, and Oracle Spatial embedding them in database tables. Esri evolved from the desktop to the server by offering SDE, a layer between its data and RDBMS that effectively spatialises database tables. After the arrival of the Internet, further web services have been devised by commercial and open source technologies alike, but that is a subject in its own right? And while RDBMS scales hardware such as Oracle Exadata, as data expands to petabytes in real time, a whole other arena such as Amazon services or SAP in-memory addresses Big Data. But what about big geo data? ArcGIS for Server is the third generation that adds a host of management, integrity, and performance tools designed to help implement scalable enterprise GIS. Hussein is a geo enthusiast, whose chief concern is to make the "Gen 3" mid-section above amenable to geo experts and project engineers alike. As a practitioner in the field, he brings a deft touch to the ins-and-outs of this powerful yet complex offering. Esri being the de facto server geo standard, this book will benefit a wide array of infrastructure administrators and application engineers. Yet Hussein's clear prose explains it well enough; his first principles will allow his audience to apply their lessons learned to other platforms, and therein lies the "sweet spot": ArcGIS for Server offers interoperability to many other server and service platforms. This book will thus be a great learning guide to help you understand the interconnectivity of data and applications. The biggest takeaway may be that readers will discover the "Internet of things" as a real-world paradigm, rather than just concepts "in the clouds" or "in the cloud". As an IT and poet friend once said: "Ladies and gentlemen… start your servers… and let the geo begin!"

Preface If you are at a library and you grabbed this book, chances are that you have heard about ArcGIS for Server in a meeting and you want to know what this product is and what it is capable of. You might have picked up this book because you were explicitly asked by your manager to investigate the capability of this bleedingedge technology and report with tangible results. Or maybe you are a system administrator who is in the middle of implementing ArcGIS for Server as your backbone architecture. Whether you are a curious blogger, a business developer, or a technical system analyst, I can guarantee that this book won't disappoint you. Administering ArcGIS for Server was designed for all levels. You might get a satisfying definition of the product and its components, with comprehensive and straightforward illustrations, by reading the first chapter of this book. If you want to just test ArcGIS for Server, you can get it up and running in testing track—a quick, simple, and efficient method for installation—and do the exercises in most of the chapters. If you are planning to set up ArcGIS for Server on your production environment, you can fully read all of the chapters and appendices and explore the advanced security preferences and performance tips to make your setup run optimally.

What this book covers 

Chapter 1, Best Practices for Installing ArcGIS for Server, introduces the product and illustrates its architecture and components. It then takes you through three tracks for installing the product: the simple testing track, the advanced tech-savvy production track, and finally the last track, which will show you how to set up and configure ArcGIS for Server specifically as a virtualized environment. Chapter 2, Authoring Web Services, teaches you the concept behind a web service and different communication protocols. You will also learn how to author and publish GIS services so various clients can consume them.

Chapter 3, Consuming GIS Services, illustrates how to consume services that you learned to author and publish in the previous chapter. You will learn how to visualize, edit, and analyze services using different clients. Chapter 4, Planning and Designing GIS Services, is where you will analyze requirements and plan what services you want to have. You then will use the planning result to design the services you nominated with rich UML tools. You will also learn to design the underlying geodatabase, which is the source that feeds these services. Chapter 5, Optimizing GIS Services, shows you how to select the correct parameters and preferences that will make your ArcGIS for Server run at its optimal state. Optimization techniques such as pooling, process isolation, and caching can be applied to bring the most out of your ArcGIS for Server and make your services run much more efficiently and effectively. Chapter 6, Clustering and Load Balancing, introduces the concept of clustering, a new technique that allows you to group machines into a cluster. You can then assign services to run on each cluster based on machine power, memory, or even on networking factors. Chapter 7, Securing ArcGIS for Server, introduces different security mechanisms available on ArcGIS for Server. GIS-tier authentication, Web authentication, and HTTPS can be applied interchangeably, depending on the security level desired by your organization. Chapter 8, Server Logs, will teach you how to harvest the logs and reports generated by ArcGIS for Server and use them to monitor your system effectively. There are different levels of logs, ranging from abstract to detailed, and the level you configure for your setup will depend on how thoroughly you want to monitor your ArcGIS for Server. Fine and detailed logs come with a performance penalty. Appendix A, Selecting the Right Hardware, describes how to select the right hardware for your ArcGIS for Server environment by providing general rules of thumb. I have come up with formulas that you can use to calculate the number of cores and amount of memory required to serve your users. Appendix B, Server Architecture, will display the difference between the old and the new ArcGIS for Server architecture. You are going to learn how ArcGIS for Server has survived the 32-bit architecture locking trap and migrated to the more effective 64-bit architecture.

What you need for this book 

You need the following software for this book: • A Browser, preferably Google Chrome, which you can download from http://www.google.com/chrome. • Esri ArcGIS for Server 10.2 or 10.1, preferably 10.2, which you can download a trial of from http://www.esri.com/software/arcgis/trial or order from your local Esri distributor. • Esri ArcGIS for Desktop 10.2 or 10.1, preferably 10.2, which you can download a trial of from http://www.esri.com/software/arcgis/trial or order from your local Esri distributor. • Microsoft SQL Server Express 2012, which you can download for free from http://www.microsoft.com/en-us/download/details.aspx?id=29062. • Oracle VirtualBox, which you can download for free from https://www.virtualbox.org/.

Who this book is for

 Whether you are a GIS user, analyst, DBA, system administrator, or programmer with a basic knowledge of Esri GIS, this book is for you. Although the book is tailored to fit system administration and analyst requirements, users can find it equally useful. Each chapter segregates the advanced technical tips from the basic and required tasks. This makes it easier for users to perform only the necessary steps to run the software.

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Administering ArcGIS for Server

Exercise Workbook-Introduction to 3D Data Modeling with ArcGIS 3D Analyst and Google Earth

Introduction to 3D Data 

by K. Heather Kennedy

Preface Introduction to 3D Data teaches GIS specialists, analysts, and technicians how to use ESRI ’ s ArcGIS 3D Analyst to model and analyze three - dimensional geographical surfaces, create 3D data, and produce displays ranging from topographically realistic maps to 3D scenes and spherical earthlike views.

Report-Status of the World’s Soil Resources

Prepared by Intergovernmental Technical Panel on Soils (ITPS)

Preface | Scope of The State of the World’s Soil Resources

The main objectives of The State of the World’s Soil Resources are: (a) to provide a global scientific assessment of current and projected soil conditions built on regional data analysis and expertise; 

Status of the Soil Resources

(b) to explore the implications of these soil conditions for food security, climate change, water quality and quantity, biodiversity, and human health and wellbeing; and (c) to conclude with a series of recommendations for action by policymakers and other stakeholders. The book is divided into two parts. The first part deals with global soil issues (Chapters 1 to 8). This is followed by a more specific assessment of regional soil change, covering in turn Africa South of the Sahara, Asia, Europe, Latin America and the Caribbean, the Near East and North Africa, North America, the Southwest Pacific and Antarctica. (Chapters 9 to 16). The technical and executive summaries are published separately.
In Chapter 1 the principles of the World Soil Charter are discussed, including guidelines for stakeholders to ensure that soils are managed sustainably and that degraded soils are rehabilitated or restored. For long, soil was considered almost exclusively in the context of food production. However, with the increasing impact of humans on the environment, the connections between soil and broader environmental concerns have been made and new and innovative ways of relating soils to people have begun to emerge in the past two decades. Societal issues such as food security, sustainability, climate change, carbon sequestration, greenhouse gas emissions, and degradation through erosion and loss of organic matter and nutrients are all closely related to the soil resource. These ecosystem services provided by the soil and the soil functions that support these services are central to the discussion in the report.

Land Cover Mapping and Classification Accuracy Assessment in QGIS

The main goals of this Module are to become familiar with QGIS, an open source GIS software;

 construct a single-date land cover map by classification of a cloud-free composite generated from Landsat images; and complete an accuracy assessment of the map output. The tools for completing this work will be done using a suite of open-source tools, mostly focusing on QGIS.
The land cover map will be created by training a machine learning algorithm, random forests, to predict land cover across the landscape. The random forests model is trained from a user generated reference data set – collected either in the field or manually through examination of remotely sensed data sources.

The resulting model is then applied across the landscape. Finally you will assess agreement with a second reference data set generated using a stratified random sampling process and high resolution aerial imagery.

The reference data set will be compared to the classified map image to determine the accuracy estimates. Modules 3 and 4 have been adapted from Exercises and material developed by Dr. Pontus Olofsson, Christopher E. Holden, and Eric L. Bullock at the Boston Education in Earth Observation Data Analysis in the Department of Earth & Environment, Boston University. To learn more about their materials and
their work, visit their github site at https://github.com/beeoda

Introduction
The tools for completing the workflow in this module are all open-source; QGIS is the primary tool used to complete both the land cover map and land cover change map workflow. A QGIS install was created from the OSGeo4W and is included on the website for download.
It includes these additional packages:
 GDAL
 Orfeo ToolBox
 QGIS
 Python

Objectives
 Explore the QGIS Terminal
 Create a false color image from the SWIR, NIR, and Red bands from the cloud free Landsat composite image,
 Stack image bands, and
 Do some basic image band arithmetic.

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Book-GIS Basics

GIS Basics

 Preface of the Book

In today’s world – the flow of information especially digital information has become the critical ingredient for success in any activity. That is why, the period we live in is often referred to as an information age.

It is a simple fact that everything human beings do, do takes place at a certain location on the earth – it has a geographic component, although we tend not to think about it much.

Time Series Analysis and Its Applications With R Examples

Preface to the Third Edition -The goals of this book are to develop an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing data, and still maintain a commitment to theoretical integrity, as exemplified by the seminal works of Brillinger (1975) and Hannan (1970) and the texts by Brockwell and Davis (1991) and Fuller (1995). 

The advent of inexpensive powerful computing has provided both real data and new software that can take one considerably beyond the fitting of simple time domain models, such as have been elegantly described in the landmark work of Box and Jenkins (1970). This book is designed to be useful as a text for courses in time series on several different levels and as a reference work for practitioners facing the analysis of timecorrelated data in the physical, biological, and social sciences. We have used earlier versions of the text at both the undergraduate and graduate levels over the past decade. Our experience is that an undergraduate course can be accessible to students with a background in regression analysis and may include §1.1–§1.6, §2.1–§2.3, the results and numerical parts of §3.1– §3.9, and briefly the results and numerical parts of §4.1–§4.6. At the advanced undergraduate or master’s level, where the students have some mathematical statistics background, more detailed coverage of the same sections, with the inclusion of §2.4 and extra topics from Chapter 5 or Chapter 6 can be used as a one-semester course. Often, the extra topics are chosen by the students according to their interests. Finally, a two-semester upper-level graduate course for mathematics, statistics, and engineering graduate students can be crafted by adding selected theoretical appendices. For the upper-level graduate course, we should mention that we are striving for a broader but less rigorous level of coverage than that which is attained by Brockwell and Davis (1991), the classic entry at this level. The major difference between this third edition of the text and the second edition is that we provide R code for almost all of the numerical examples. In addition, we provide an R supplement for the text that contains the data and scripts in a compressed file called tsa3.rda; the supplement is available on the website for the third edition, http://www.stat.pitt.edu/stoffer/tsa3/,or one of its mirrors. On the website, we also provide the code used in each example so that the reader may simply copy-and-paste code directly into R. Specific details are given in Appendix R and on the website for the text. Appendix R is new to this edition, and it includes a small R tutorial as well as providing a reference for the data sets and scripts included in tsa3.rda. So there is no misunderstanding, we emphasize the fact that this text is about time series analysis, not about R. R code is provided simply to enhance the exposition by making the numerical examples reproducible. We have tried, where possible, to keep the problem sets in order so that an instructor may have an easy time moving from the second edition to the third edition. However, some of the old problems have been revised and there are some new problems. Also, some of the data sets have been updated. We added one section in Chapter 5 on unit roots and enhanced some of the presentations throughout the text. The exposition on state-space modeling, ARMAX models, and (multivariate) regression with autocorrelated errors in Chapter 6 have been expanded. In this edition, we use standard R functions as much as possible, but we use our own scripts (included in tsa3.rda) when we feel it is necessary to avoid problems with a particular R function; these problems are discussed in detail on the website for the text under R Issues. We thank John Kimmel, Executive Editor, Springer Statistics, for his guidance in the preparation and production of this edition of the text. We are grateful to Don Percival, University of Washington, for numerous suggestions that led to substantial improvement to the presentation in the second edition, and consequently in this edition. We thank Doug Wiens, University of Alberta, for help with some of the R code in Chapters 4 and 7, and for his many suggestions for improvement of the exposition. We are grateful for the continued help and advice of Pierre Duchesne, University of Montreal, and Alexander Aue, University of California, Davis. We also thank the many students and other readers who took the time to mention typographical errors and other corrections to the first and second editions. Finally, work on the this edition was supported by the National Science Foundation while one of us (D.S.S.) was working at the Foundation under the Intergovernmental Personnel Act. Davis, CA Robert H. Shumway Pittsburgh, PA David S. Stoffer September 2010

Characteristics of Time Series 

1.1 Introduction 

The analysis of experimental data that have been observed at different points in time leads to new and unique problems in statistical modeling and inference. The obvious correlation introduced by the sampling of adjacent points in time can severely restrict the applicability of the many conventional statistical methods traditionally dependent on the assumption that these adjacent observations are independent and identically distributed. The systematic approach by which one goes about answering the mathematical and statistical questions posed by these time correlations is commonly referred to as time series analysis. The impact of time series analysis on scientific applications can be partially documented by producing an abbreviated listing of the diverse fields in which important time series problems may arise. For example, many familiar time series occur in the field of economics, where we are continually exposed to daily stock market quotations or monthly unemployment figures. ments. An epidemiologist might be interested in the number of influenza cases observed over some time period. In medicine, blood pressure measurements traced over time could be useful for evaluating drugs used in treating hypertension. Functional magnetic resonance imaging of brain-wave time series patterns might be used to study how the brain reacts to certain stimuli under various experimental conditions. Many of the most intensive and sophisticated applications of time series methods have been to problems in the physical and environmental sciences. This fact accounts for the basic engineering flavor permeating the language of time series analysis. One of the earliest recorded series is the monthly sunspot numbers studied by Schuster (1906). More modern investigations may center on whether a warming is present in global temperature measurementsor whether levels of pollution may influence daily mortality in Los Angeles. The modeling of speech series is an important problem related to the efficient transmission of voice recordings. Common features in a time series characteristic known as the power spectrum are used to help computers recognize and translate speech. Geophysical time series such as those produced by yearly depositions of various kinds can provide long-range proxies for temperature and rainfall. Seismic recordings can aid in mapping fault lines or in distinguishing between earthquakes and nuclear explosions. The above series are only examples of experimental databases that can be used to illustrate the process by which classical statistical methodology can be applied in the correlated time series framework. In our view, the first step in any time series investigation always involves careful scrutiny of the recorded data plotted over time. This scrutiny often suggests the method of analysis as well as statistics that will be of use in summarizing the information in the data. Before looking more closely at the particular statistical methods, it is appropriate to mention that two separate, but not necessarily mutually exclusive, approaches to time series analysis exist, commonly identified as the time domain approach and the frequency domain approach. The time domain approach is generally motivated by the presumption that correlation between adjacent points in time is best explained in terms of a dependence of the current value on past values. The time domain approach focuses on modeling some future value of a time series as a parametric function of the current and past values. In this scenario, we begin with linear regressions of the present value of a time series on its own past values and on the past values of other series. This modeling leads one to use the results of the time domain approach as a forecasting tool and is particularly popular with economists for this reason

Training Manual on Remote Sensing and GIS

Application of Remote Sensing and Geographic Information Systems for Mapping and Monitoring of Glaciers Part 2 - Glacier Database Generation using ArcGIS

Training Manual

About the Manual

This manual provides an introduction to Geographic Information Systems (GIS) and ArcGIS software.

The ArcGIS platform and tools are explained so that they can be used for generating glacier database, analysis on glacier database and preparing glacier maps. The manual is divided into three parts – first part includes the introduction of GIS and descriptions of some of the fundamental terms used in GIS. The second part includes the hands-on exercise on ArcGIS to make you familiar on the software and the third part includes the detail exercise for generating different attribute of the glacier polygon with some analysis.

Read the manual carefully before doing hands-on exercises. Step by step processes are explained in bullet point format and short introductions to the data processing steps are in normal format. Practice data for this manual are available at this link: http://www.icimod.org/glacierdata/glacier_training_data.zip

Optical Remote Sensing

Optical Remote Sensing 

Preface- In recent years, much has transpired in the field of remote sensing and, in particular, polarization. Polarization is an outgrowth of multiple, highly accurate photometric measurements. Plane polarization is the difference between precision photometric measurements in two mutually perpendicular directions. 

Optical Remote Sensing

Circular polarization is used as a refinement in the complete description of the optical properties of surfaces and of the atmosphere in terms of Stokes parameters.

REMOTE SENSING – APPLICATIONS

Preface- Nowadays it is hard to find areas of human activity and development that have not profited from or contributed to remote sensing. 

Natural, physical and social activities find in remote sensing a common ground for interaction and development. From the end-user point of view, Earth science, geography, planning, resource management, public policy design, environmental studies, and health, are some of the areas whose recent development has been triggered and motivated by remote sensing. From the technological point of view, remote sensing would not be possible without the advancement of basic as well as applied research in areas like physics, space technology, telecommunications, computer science and engineering.

GIS for Web Developers

Preface of the Book

We are on the edge of the next big wave of technology, and it has GIS written all over it. Soon every new cell phone will have GPS (or some form of location-based services) built in as a standard feature. 

GIS for Web Developers

Nearly every major database vendor now includes native geographic data types. Free sources of geographic data and free applications are just waiting for you to pull them together and do something clever. You might create a simple digital version of the pushpin map, or you might write the next Google Maps killer. All of our lives we’ve asked “Where am I?” and “How do I get from here to there?” You start by rolling over, then crawling, and then walking. You walked to school or were driven or took the bus. Maybe you eventually drove yourself. When you got older, you joined a society of people who use different modes of transportation every day. We ride subways to work. We take airplane flights to far-off places. We visit client locations. We attend conferences or night classes. We go shopping. We eat out at restaurants. Unless you spend your days physically tied to something large, heavy, and immobile, you probably spend a significant portion of your time thinking about how to get from here to there and back again. And how does traditional geography make that easier? It offers you vector and raster data, orthographically rectified and portrayed in the Universal Transverse Mercator projection. (Don’t you feel better already?) Even asking a simple question like “What is your current latitude and longitude?” will likely cause most people to back away slowly, hands up, muttering, “That’s OK—I’ll ask someone else for directions.”
In GIS for Web Developers we’ll talk about GIS in simple terms and demonstrate its real-world uses. We have always been awash in spatial data: houses and buildings have street addresses, customers cluster together in cities and states, you probably store your friends and family in one or more electronic address books. What has been missing up until now are tools targeted at developers without formal training in GIS. What was once a specialized field is now open to new class of technically savvy but untrained map hackers—neogeographers1 . This book is squarely targeted at this new generation of mapmakers. A word of warning to the faint of heart: you will be forced to wade through a quagmire of polysyllabic jargon. My apologies in advance. What you have to look forward to is that by the end of the book you’ll be able to sling these phrases around with confidence, much like saying “instantiate” and “polymorphic” to your fellow software developers. Every application and API presented in this book is free or open source. I have taken great pains to make sure that they are supported on all the major operating systems (Mac OS X, Linux, and Windows). You will have enough on your plate simply battling the obscure lingo and the incompatible file formats. The last things you need to worry about are platform-specific solutions, let alone expensive platform-specific solutions.

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GIS Cartography: A Guide to Effective Map Design

GIS Cartography

 The reader of this book is assumed to have a basic understanding of geography and GIS principles. For example, in Chapter 3, “Layout Design,” there is a section on projections. 

It is assumed that you know what projections are and why they are an important component of any GIS work. The section, therefore, deals with only whether a map designer ought to include projection information on a printed map document and, if so, how it ought to be formatted design‑wise.

ArcGIS Tutorial E-book-ArcGIS By Example

ArcGIS by example

Preface of the book:

 Over the last two years, I have written three books on ArcGIS technology. Each book covers different topics and fields of this increasingly ubiquitous technology. 

Although I used examples and various real-life project approaches to explain the technology in all my books, this is the first book where the content evolves with the help of examples. I have been working with Esri ArcGIS since 2005 when ArcGIS 9.1 was released, so writing this title from a technological point of view was not difficult.
In fact, it was thrilling. The challenging part was to come up with three unique real life examples and to build them up as I wrote the book. Each example should target certain features of the technology and explain them along the way. These three examples are all from my own imagination and they are not linked to or correlate with any actual projects that I personally worked on or witnessed. You will not find any of these examples in Esri's help or on any online resource. All the code that is available in this book is written from scratch for this book that you are holding in your hands.

GIS Tutorial E book-PYTHON Scripting for ArcGIS

Preface 

The impetus for writing this book came from the lessons I’ve learned from using and teaching geographic information systems (GIS) for over 10 years at several different universities. One of these lessons is that “a little bit of code can go a long way.” Those of us who learned our first computer skills back in the days of MS-DOS became familiar with using a command prompt to carry out basic tasks.

Early versions of ArcGIS for Desktop Advanced (ArcInfo) software also relied heavily on a command line interface, in addition to the use of the ARC Macro Language (AML). 

SOIL ORGANIC CARBON MAPPING Book

Chapter 1 Presentation

Soils provide ecosystem services critical to life on Earth. The Food and Agricultural Organization of the United Nations (FAO) recognizes the need to preserve soil resources from degradation and boost healthy soils. In 2012, FAO members established the Global Soil Partnership (GSP) as a mechanism to improve soil governance at global, regional and national levels. 

The GSP aims to promote sustainable soil management at all levels through different means including normative tools, capacity development, international events and field projects relying on evidence-based science. Understanding the status of a given soil in different land uses, including its properties and functions, and relating this information to the various ecosystem services provided by them, becomes mandatory for sustainable soil management decisions. As the availability of soil data and information is fundamental to underpin these decisions, partners of the GSP decided to establish a Global Soil Information System (GLOSIS) based on a distributed model whereby the system is fed by national soil information systems. In the process of establishing GLOSIS, a number of components are being established, including the International Network of Soil Information Institutions

Handbook of Disaster and Emergency Management

Preface-Tolley’s Handbook of Disaster and Emergency Management: Principles and Practice has been produced to assist those who are either directly or peripatetically engaged in Disaster or Emergency Management issues. 

Handbook of Disaster and Emergency Management

In the broadest context the Handbook will be of use to those in Occupational Safety and Health, Emergency Planning, COMAH operations, Civil Defense, Business Continuity and Insurance, Loss Prevention, Risk Management, Fire Safety, Public Health and Environmental Management. It is relevant to both the private and the public sectors. The publication will also be of interest to practitioners in countries which have a similar approach to that of the UK because of the inclusion of information and case studies relevant to all those with responsibility for Crisis, Disaster and Emergency Management.

A Dictionary of Earth Sciences third edition Edited by michael allaby

A Wide Ranging and Authoritative Guide Containing over 6250 entries of Geo-sciences.

Dictionary of Earth Sciences

Preface to the Third Edition 

The second edition of Oxford’s Dictionary of Earth Sciences was published eight years ago, in 1999, and although the dictionary was reprinted with corrections in 2003, it was possible then to make only minor changes. This edition is entirely new. Every entry has been scrutinized and brought up to date where necessary. New entries have been added and the number of diagrams has increased. The new entries added in the second edition related predominantly to the expansion of planetary exploration and satellite technology. Those entries have been updated. Many of the new entries in this edition serve to expand the dictionary’s coverage of geomorphological terms.

It is in the nature of dictionaries to grow longer with each revision, and I make no apology for the fact that this one conforms to that rule. Such growth is unavoidable, because the language itself is always growing, but when new terms are introduced it does not mean that older terms are discarded. Even terms that do become obsolete do so gradually, surviving for many years in established and much loved texts. The first edition was compiled with the help of many contributors and advisers, and a smaller number of contributors assisted in preparing the second edition. The value of their hard work endures, and I gladly and fully acknowledge it, for without it there would have been no dictionary to revise. I have worked alone in preparing this third edition, however, so if any new errors have crept in they are mine alone. 

Michael Allaby Tighnabruaich, Argyll 

www.michaelallaby.com

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Dictionary of Earth Sciences

Simulation of Groundwater Flow and Effects of Groundwater Irrigation on Stream Base Flow in the Elkhorn and Loup River Basins, Nebraska

This report presents the phase-two groundwater-flow simulations and predicted effects of groundwater irrigation on stream base flow in the Elkhorn and Loup River Basins of central Nebraska. 

Simulation of Groundwater Flow and Effects of Groundwater Irrigation

Remote Sensing Models and Methods for Image Processing

Preface-This book began as a rather conservative revision of my earlier textbook, Techniques for Image Processing and Classification in Remote Sensing. 

Like many “limited” endeavors, however, it soon grew to be a much larger project! When it became clear that simply a revision would not suffice, I gave considerable thought on a new way to present the subject of image processing in the context of remote sensing.

Training Manual-A Practical Guide to Geo-statistical Mapping of Environmental Variables

The guide consists of four chapters. The first chapter is an introductory chapter to the practice of geostatistical mapping and gives an overview of the spatial prediction techniques. The second chapter zooms into regression-kriging and its characteristics, advantages and limitations. 

A Practical Guide to Geostatistical Mapping of Environmental Variables

The third chapter is completely dedicated to installation and doing first steps in the software, and the last, fourth, chapter gives a step-by-step guide through analysis and generation of final layouts by using a digital soil mapping case study. After reading the first chapter, you should understand what the geostatistical mapping is; after reading the second chapter, you should know how to select the right spatial prediction technique for your application; after reading the third chapter, you should be able to install all packages used in the handbook and be aware of their capabilities; and after reading the fourth chapter, you should know how to run geostatistical mapping, prepare final layouts and interpret the results of analysis for your own case study. This guide evolved as a lecturing material that has been used for a 5-day training course called “Hands-on-geostatistics: Merging GIS and Spatial Statistics”. The objective of this course was to provide theoretical backgrounds and practical training on the use of hybrid geostatistical/GIS tools for various applications ranging from spatial prediction to sampling and error propagation. In addition, the leitmotive of the course was to provide practical training in command-based software packages such as R. We aimed at Master and PhD level students and post-doctoral researchers in various fields of environmental and geo-sciences interested in spatial prediction and analysis of environmental variables. We have run this course already twice: at the Facolta di Agraria in Naples (29.01-03.02.2007), and at JRC Ispra (03.06-07.06.2007). At both occasions, the interest exceeded our expectations.

Image Interpretation in Geology

Remote sensing roughly means extending human sensory perception to distances greater than we can achieve unaided and to information that is far beyond our physiological capabilities. 

Image Interpretation in Geology

Vision is far and away our most powerful and flexible sense, and so the strict focus is on capturing information about the Earth's properties in the nearly continuous, two-dimensional fashion that is characteristic of images. This is possible only for those properties that control how Earth materials interact with electromagnetic radiation-not only visible light, but a spectrum that extends from gamma- to microwave radiation. Other attributes relenting to natural variations in density, magnetic and electrical properties are detectable, but only in a discontinuous fashion-from point to point or along surveyed lines. The same holds for variations in chemistry, topographic elevation and the geometric structure of rocks, both at and beneath the surface, plus a host of other kinds of geological information. Although some of these attributes can be measured from a distance, the immediate results are not images.They are not excluded from the book, however, because there are means of recasting numbers distributed irregularly in two cartographic dimensions into the form of images. Visual perception is unsurpassed in extracting nuances from any kind of image, whatever its means

of derivation. So, there is an overlap between remote sensing and more familiar means of gathering geo-scientific information. Part of it is through images, and part through data analysis itself. One of the most important new tools is using computers to find patterns and correlations among far more layers of information than the human intellect can grasp. We deal as a matter of routine with spatial and to a lesser extent time dimensions, but a geological problem often involves tens of different dimensions.

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DIGITAL ELEVATION MODELS-A Guidance Note on how Digital Elevation Models are created and used – includes key definitions, sample Terms of Reference and how best to plan a DEM-mission.

Digital Elevation Model

Executive Summary

The cost of creating DEMs can be significant, often running into millions of dollars, due to their diverse and extensive utility. The use of DEMs is abundant in spatial analyses. As such, a clear understanding of the range of DEM types and applications, their operational requirements, and pros and cons of each model is important before deciding whether to acquire existing data or commissioning a new survey. Having robust background knowledge can help plan the optimal DEM acquisition. 

Book-Radar remote sensing to support tropical forest management

Radar remote sensingto supporttropical forest management

Abstract -van der Sanden, J.J., 1997. Radar remote sensing to support tropical forest management. Wageningen, The Netherlands (Wageningen Agricultural University), Tropenbos-Guyana Series 5, doctoral thesis, 330 p. 

This text describes an investigation into the potential of radar remote sensing for application to tropical forest management. The information content of various radar images is compared and assessed with regard to the information requirements of parties involved in tropical forest management at the global, national and local spatial levels. 

Book:Principles of Sedimentology and Stratigraphy, 4th Edition by SAM BOGGS, JR

This book describes and discusses the physical, chemical, and biological characteristics of sedimentary rocks and the interpretations that we draw from these characteristics about the origin of sedimentary rocks

. 

Geologists disagree somewhat about how the various kinds of sedimentary rocks should be classified; however, such rocks can conveniently be placed into three fundamental groups on the basis of composition and origin: siliciclastic, chemical/biochemical, and carbonaceous. Siliciclastic sedimentary rocks are composed dominantly of silicate minerals, such as quartz and feldspar, and rock fragments (clasts).

Download MATLAB Software

Download MATLAB Software: Software

Laser Remote Sensing

 INTRODUCTION 

 From Visual Perception to Lidar

 Sensual perception of remote objects by processing of radiative stimuli is a capability widely encountered in animals. Humans perceive only passively, that is, see and hear objects that either radiate themselves or scatter and re-transmit radiation from an external source. Some animals can locate objects actively as well, using optical or acoustical radiation they generate on purpose. 

Laser Remote Sensing

edited by Takashi Fujii Central Research Institute of Electrical Power Industry Tokyo, Japan 

Tetsuo Fukuchi 

Central Research Institute of Electrical Power Industry Tokyo, Japan

Several species of fish literally carry lanterns. Horses and elephants are known to utilize active acoustic means for orientation in complete darkness. Bats use it to locate and catch prey. Man has been using illumination with visible light from artificial sources for active optical detection of objects. Distance is inferred stereoscopically, that is, from the slightly different images obtained at the viewing angles of the two eyes, by mental construction, from two two-dimensional images, of a three-dimensional geometric relationship between different parts of the scene, or, for more remote objects, from the decrease of visual contrast. Fuji and Fukuchi / Laser Remote Sensing DK1181_c001 Final Proof page 2 18.5.2005 7:23pm 2 Weitkamp Except for stereoscopic viewing, which fails at longer distance, these methods yield relative values only. Distance can be determined in a quantitative way by measuring the transit time of radiation from the source to the object and back. Systems that rely on this principle require a pulsed or modulated source and a detection system with adequate time resolution, approximately a million times better in the optical case than in the acoustical case. Man’s senses do not nearly meet this requirement. Therefore, the technique became available to us only after the advent of suitable microwave, light, and sound sources and time-resolving detection systems. Depending on whether sound, radiowaves, or light is used, these systems are called SONAR (Sound Navigation Ranging) or SODAR (Sound Detection And Ranging), RADAR (Radio wave Detection And Ranging), or LIDAR (Light Detection And Ranging). Sonar works under water, the remaining techniques in the atmosphere. Lidar uses not just visible wavelengths (400 nm < l < 700 nm), but also ultraviolet (225 nm < l < 400 nm) and infrared radiation (0.7mm < l < 12mm). All these techniques are based on the same simple principle. A short pulse of radiation is transmitted into water or air, and the backscattered radiation is detected and analyzed. Clearly, radiation scattered from an object at a closer distance comes back sooner than that from an object at a longer distance. Scattering occurs not only on solid objects but also from the molecules and particulate matter in air and water. The return signal will, therefore, not be of the same length as the transmitted pulse, but extended in time, with a huge, but short peak from a solid object (if there is any) sitting on a much weaker, but temporally extended signal from air or water.

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