The oceans cover approximately 71% of Earth's surface, 90% of the biosphere and contains 97% of Earth's water. Since the first launch of SEASAT satellite in 1978, an increasing number of SAR satellites have or will become available, such as the European Space Agency's ERS-1/-2, ENVISAT, and Sentinel-1 series; the Canadian RADARSAT-1/-2 and the upcoming RADARSAT Constellation Mission series satellites; the Italian COSMO-SkyMed satellites, the German TERRASAR-X and TANDEM-X, and the Chinese GAOFEN-3 SAR, among others. Recently, European Space Agency has launched a new generation of SAR satellites, Sentinel-1A in 2014 and Sentinel-1B in 2016. These SAR satellites provide researchers with free and open SAR images necessary to carry out their research on the global oceans. The scope of Advances in SAR Remote Sensing of Oceans is to demonstrate the types of information that can be obtained from SAR images of the oceans, and the cutting-edge methods needed for analysing SAR images. Written by leading experts in the field, and divided into four sections, the book presents the basic principles of radar backscattering from the ocean surface; introduces the recent progresses in SAR remote sensing of dynamic coastal environment and management; discusses the state-of-the-art methods to monitor parameters or phenomena related to the dynamic ocean environment; and deals specifically with new techniques and findings of marine atmospheric boundary layer observations. Advances in SAR Remote Sensing of Oceans is a very comprehensive and up-to-date reference intended for use by graduate students, researchers, practitioners, and R&D engineers working in the vibrant field of oceans, interested to understand how SAR remote sensing can support oceanography research and applications.

In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Many disciplines are concerned with manipulating geometric (or spatial) objects in the computer - such as geology, cartography, computer aided design (CAD), etc. - and each of these have developed their own data structures and techniques, often independently. Nevertheless, in many cases the object types and the spatial queries are similar, and this book attempts to find a common theme.

Sixty years after its birth, Synthetic Aperture Radar (SAR) evolved as a key player of earth observation, and it is continually upgraded by enhanced hardware functionality and improved overall performance in response to user requirements. The basic information gained by SAR includes the backscattering coefficient of targets, their phases (the truncated distance between SAR and its targets), and their polarization dependence. The spatiotemporal combination of the multiple data operated on the satellite or aircraft significantly increases its sensitivity to detect changes on earth, including temporal variations of the planet in amplitude and the interferometric change for monitoring disasters; deformations caused by earthquakes, volcanic activity, and landslides; environmental changes; ship detection; and so on. Earth-orbiting satellites with the appropriate sensors can detect environmental changes because of their large spatial coverage and availability. Imaging from Spaceborne and Airborne SARs, Calibration, and Applications provides A-to-Z information regarding SAR researches through 15 chapters that focus on the JAXA L-band SAR, including hardware description, principles of SAR imaging, theoretical description of SAR imaging and error, ScanSAR imaging, polarimetric calibration, inflight antenna pattern, SAR geometry and ortho rectification, SAR calibration, defocusing for moving targets, large-scale SAR imaging and mosaic, interferometric SAR processing, irregularities, application, and forest estimation. Sample data are created by using L-band SAR, JERS-1, PALSAR, PALSAR-2, and Pi-SAR-L2. This book is based on the author's experience as a principal researcher at JAXA with responsibilities for L-band SAR operation and researches. It reveals the inside of SAR processing and application researches performed at JAXA, which makes this book a valuable reference for a wide range of SAR researchers, professionals, and students.

This book reviews the contributions of Earth Observation (EO) to public health practices. It examines how EO is being used to understand, track, predict, and manage infectious and chronic diseases, and it provides discussion on the current challenges and the significant development potential of EO to a One Health approach. Its objective is to address a set of questions: How does EO currently assist public health activities? What are the challenges for operational use of EO in public health? What are the opportunities for EO to benefit public health in the near future? This review concentrates on the following priority themes to which EO and geomatics can make important contributions: mosquito-borne and tick-borne diseases; water-borne diseases; air quality and extreme heat effects; and geospatial indicators of vulnerable human populations. EO has also demonstrated potential during the COVID-19 pandemic as an efficient provider of data on rapid environmental and socio-economic changes and impacts. Remotely sensed data are particularly useful for risk modelling and mapping projects to help generate information on occurrence and spatio-temporal trends of disease risk. Similarly, EO can be used to identify risk factors for disease risk or emergence detected in surveillance, and support development of early warning systems. Risk maps enable public health professionals to anticipate and prepare for health threats, and they can support responses to infectious disease epidemics or existing endemic conditions. This book emerged from the collaboration of the Public Health Agency of Canada and the Canadian Space Agency with contributions of international experts. Their findings will be of great value to public health and EO professionals interested in developing and applying geospatial applications in the risk assessment and management of public health issues.

This open access book is a consolidation of lessons learnt and experiences gathered from our efforts to utilise Earth observation (EO) science and applications to address environmental challenges in the Hindu Kush Himalayan region. It includes a complete package of knowledge on service life cycles including multi-disciplinary topics and practically tested applications for the HKH. It comprises 19 chapters drawing from a decade's worth of experience gleaned over the course of our implementation of SERVIR-HKH - a joint initiative of NASA, USAID, and ICIMOD - to build capacity on using EO and geospatial technology for effective decision making in the region. The book highlights SERVIR's approaches to the design and delivery of information services - in agriculture and food security; land cover and land use change, and ecosystems; water resources and hydro-climatic disasters; and weather and climate services. It also touches upon multidisciplinary topics such as service planning; gender integration; user engagement; capacity building; communication; and monitoring, evaluation, and learning. We hope that this book will be a good reference document for professionals and practitioners working in remote sensing, geographic information systems, regional and spatial sciences, climate change, ecosystems, and environmental analysis. Furthermore, we are hopeful that policymakers, academics, and other informed audiences working in sustainable development and evaluation - beyond the wider SERVIR network and well as within it - will greatly benefit from what we share here on our applications, case studies, and documentation across cross-cutting topics.

As coastal environments around the world face unprecedented natural and anthropogenic threats, advancements in the technologies that support geospatial data acquisition, imaging, and computing have profoundly enhanced monitoring capabilities in coastal studies. Providing systematic treatment of the key developments, Remote Sensing of Coastal Environments brings together renowned scholars to supply a clear presentation of the state-of-the-art in this technically complex arena. Edited by a recipient of the prestigious PECASE award, this book provides unrivaled coverage of the issues unique to coastal environments. It presents the best available data for measuring and monitoring coastal zones and explains how decision makers and resource managers can use this data to address contemporary issues in coastal zone management. The text illustrates the latest developments in active remote sensing, hyperspectral remote sensing, high spatial resolution remote sensing, the integration of remote sensing and in situ data, and covers the effects of land-cover and land-use change on coastal environments. Complete with representative case studies, this authoritative resource provides a timely snapshot of the wide range of remote sensing applications in coastal issues to enhance the understanding of how increasing disturbances to our coastal regions are affecting the ecological dynamics, biological diversity, and ecosystem health of our coastal environments.

Field Measurements for Environmental Remote Sensing: Instrumentation, Intensive Campaigns, and Satellite Applications is an academic synthesis of invaluable in situ measurements and techniques leveraged by the science of environmental remote sensing. Sections cover in situ datasets and observing methods used for satellite remote sending applications and validation, synthesizing the various techniques utilized by well-established application areas under a common paradigm. The book serves as both a textbook for students (upper-level undergraduate to graduate level) and a reference book for practitioners and researchers in the atmospheric, oceanic and remote sensing fields.

One of the key geographical developments over the last two centuries has been that of urbanisation. In recent years this has exploded globally, particularly in developing countries. It is essential for governments, planners and researchers in geography and allied fields to understand this process and the main way of being able to do this is to accurately map these changes. The main method of this mapping is Remote Sensing. This up-to-date analysis of the area looks at a wide range of methodologies currently being used to produce and analyse remotely sensed data of urban areas. The authors examine the various techniques used to extract information from digital, multispectral images of urban areas. Donnay and Barnsley then go on to look at the identification of urban forms, the delineation of agglomerations and the development of urban morphology, considering the analysis of integrated data sets and surface models and going on to look at the estimation of human population levels.

Ideal for both undergraduate and graduate students in the fields of geography, forestry, ecology, geographic information science, remote sensing, and photogrammetric engineering, LiDAR Remote Sensing and Applications expertly joins LiDAR principles, data processing basics, applications, and hands-on practices in one comprehensive source. The LiDAR data within this book is collected from 27 areas in the United States, Brazil, Canada, Ghana, and Haiti and includes 183 figures created to introduce the concepts, methods, and applications in a clear context. It provides 11 step-by-step projects predominately based on Esri's ArcGIS software to support seamless integration of LiDAR products and other GIS data. The first six projects are for basic LiDAR data visualization and processing and the other five cover more advanced topics: from mapping gaps in mangrove forests in Everglades National Park, Florida to generating trend surfaces for rock layers in Raplee Ridge, Utah. Features Offers a comprehensive overview of LiDAR technology with numerous applications in geography, forestry and earth science Gives necessary theoretical foundations from all pertinent subject matter areas Uses case studies and best practices to point readers to tools and resources Provides a synthesis of ongoing research in the area of LiDAR remote sensing technology Includes carefully selected illustrations and data from the authors' research projects Before every project in the book, a link is provided for users to download data

Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data in Python. This book starts with an introduction to geodata and covers topics such as GIS and common tools, standard formats of geographical data, and an overview of Python tools for geodata. Specifics and difficulties one may encounter when using geographical data are discussed: from coordinate systems and map projections to different geodata formats and types such as points, lines, polygons, and rasters. Analytics operations typically applied to geodata are explained such as clipping, intersecting, buffering, merging, dissolving, and erasing, with implementations in Python. Use cases and examples are included. The book also focuses on applying more advanced machine learning approaches to geographical data and presents interpolation, classification, regression, and clustering via examples and use cases. This book is your go-to resource for machine learning on geodata. It presents the basics of working with spatial data and advanced applications. Examples are presented using code (accessible at github.com/Apress/machine-learning-geographic-data-python) and facilitate learning by application. What You Will Learn Understand the fundamental concepts of working with geodata Work with multiple geographical data types and file formats in Python Create maps in Python Apply machine learning on geographical data Who This Book Is For Readers with a basic understanding of machine learning who wish to extend their skill set to analysis of and machine learning on spatial data while remaining in a common data science Python environment

This is an introductory textbook on spatial analysis and spatial statistics through GIS. Each chapter presents methods and metrics, explains how to interpret results, and provides worked examples. Topics include: describing and mapping data through exploratory spatial data analysis; analyzing geographic distributions and point patterns; spatial autocorrelation; spatial clustering; geographically weighted regression and OLS regression; and spatial econometrics. The worked examples link theory to practice through a single real-world case study, with software and illustrated guidance. Exercises are solved twice: first through ArcGIS, and then GeoDa. Through a simple methodological framework the book describes the dataset, explores spatial relations and associations, and builds models. Results are critically interpreted, and the advantages and pitfalls of using various spatial analysis methods are discussed. This is a valuable resource for graduate students and researchers analyzing geospatial data through a spatial analysis lens, including those using GIS in the environmental sciences, geography, and social sciences.

Offers New Insight on Uncertainty Modelling Focused on major research relative to spatial information, Uncertainty Modelling and Quality Control for Spatial Data introduces methods for managing uncertainties-such as data of questionable quality-in geographic information science (GIS) applications. By using original research, current advancement, and emerging developments in the field, the authors compile various aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book launches into areas that are rarely addressed. Topics covered include: New developments of uncertainty modelling, quality control of spatial data, and related research issues in spatial analysis Spatial statistical solutions in spatial data quality Eliminating systematic error in the analytical results of GIS applications A data quality perspective for GIS function workflow design Data quality in multi-dimensional integration Research challenges on data quality in the integration and analysis of data from multiple sources A new approach for imprecision management in the qualitative data warehouse A multi-dimensional quality assessment of photogrammetric and LiDAR datasets based on a vector approach An analysis on the uncertainty of multi-scale representation for street-block settlement Uncertainty Modelling and Quality Control for Spatial Data serves university students, researchers and professionals in GIS, and investigates the uncertainty modelling and quality control in multi-dimensional data integration, multi-scale data representation, national or regional spatial data products, and new spatial data mining methods.

With the widespread use of PDAs, wireless internet, Internet-based GIS, and 3G and 4G telecommunications, the technology supporting mobile GIS is rapidly gaining popularity and effectiveness. Dynamic and Mobile GIS: Investigating Changes in Space and Time addresses Web GIS, mobile GIS, and the modeling, processing, and representation of dynamic events, as well as current demands to update GIS representations. Providing a comprehensive overview of this emerging technology, this book highlights innovations, new ways of modeling both spatial objects and dynamic processes affecting them, and advances in visualization. Featuring contributions from established GIS workers, it begins with an introduction of extant technology and previews future developments. The book examines challenges to security and privacy and presents practical solutions to these problems while focusing on modeling approaches and exploring the need to display an appropriate level of information in a mobile environment. Concluding with a study of mobility, the book also contains practical examples of applications of mobile devices for disaster management and environmental monitoring. Dynamic and Mobile GIS: Investigating Changes in Space and Time offers detailed cases of successful applications and identifies the current cutting-edge aspects of mobile and dynamic GIS. The book also looks to the future, investigating important research directions and potential challenges.

Written by world renowned scientists, this book provides an excellent overview of a wide array of methods and techniques for the processing and analysis of multitemporal remotely sensed images. These methods and techniques include change detection, multitemporal data fusion, coarse-resolution time series processing, and interferometric SAR multitemporal processing, among others. A broad range of multitemporal datasets are used in their methodology demonstrations and application examples, including multispectral, hyperspectral, SAR and passive microwave data. This book features a variety of application examples covering both land and aquatic environments. Land applications include urban, agriculture, habitat disturbance, vegetation dynamics, soil moisture, land surface albedo, land surface temperature, glacier and disaster recovery. Aquatic applications include monitoring water quality, water surface areas and water fluctuation in wetland areas, spatial distribution patterns and temporal fluctuation trends of global land surface water, as well as evaluation of water quality in several coastal and marine environments. This book will help scientists, practitioners, students gain a greater understanding of how multitemporal remote sensing could be effectively used to monitor our changing planet at local, regional, and global scales.

This standard textbook covers in its extensively revised 5th edition all main directions of geodesy, providing the theoretical background as well as modern principles of measurement and evaluation methods. Today’s geodetic work is comprehensively presented by numerous examples of instruments. New: Novel geodetic reference system; Future gravity field mission concepts and technologies; Principle of quantum gravimetry.

Remote Sensing plays a key role in monitoring the various manifestations of global climate change. It is used routinely in the assessment and mapping of biodiversity over large areas, in the monitoring of changes to the physical environment, in assessing threats to various components of natural systems, and in the identification of priority areas for conservation.

This book presents the fundamentals of remote sensing technology, but rather than containing lengthy explanations of sensor specifications and operation, it concentrates instead on the application of the technology to key environmental systems. Each system forms the basis of a separate chapter, and each is illustrated by real world case studies and examples.

Readership

The book is intended for advanced undergraduate and graduate students in earth science, environmental science, or physical geography taking a course in environmental remote sensing. It will also be an invaluable reference for environmental scientists and managers who require an overview of the use of remote sensing in monitoring and mapping environmental change at regional and global scales.

Additional resources for this book can be found at: http: //www.wiley.com/go/purkis/remote.

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty's fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.

Mapping Space, Sense, and Movement in Florence explores the potential of digital mapping or Historical GIS as a research and teaching tool to enable researchers and students to uncover the spatial, kinetic and sensory dimensions of the early modern city. The exploration focuses on new digital research and mapping projects that engage the rich social, cultural, and artistic life of Florence in particular. One is a new GIS tool known as DECIMA, (Digitally-Encoded Census Information and Mapping Archive), and the other is a smartphone app called Hidden Florence. The international collaborators who have helped build these and other projects address three questions: how such projects can be created when there are typically fewer sources than for modern cities; how they facilitate more collaborative models for historical research into social relations, senses, and emotions; and how they help us interrogate older historical interpretations and create new models of analysis and communication. Four authors examine technical issues around the software programs and manuscripts. Five then describe how GIS can be used to advance and develop existing research projects. Finally, four authors look to the future and consider how digital mapping transforms the communication of research results, and makes it possible to envision new directions in research. This exciting new volume is illustrated throughout with maps, screenshots and diagrams to show the projects at work. It will be essential reading for students and scholars of early modern Italy, the Renaissance and digital humanities.

Ideally, every tract of land has a description on paper and a physical survey on the ground. When boundary disputes arise, all parties concerned must quickly learn the vocabulary and processes involved with real estate. Written for anyone dealing in real estate transactions, Subdividing the Land: Metes and Bounds and Rectangular Survey Systems provides this background. It defines key legal terms, examines key concepts of Metes and Bounds, the structure of the U.S. Land Survey System and offers many illustrations and tables that clearly explain the concepts. Each state has its own property laws, but the book's material is generic enough to be applicable across the entire United States and even Canada. Taking into account that local laws may be influenced by many factors, the book also covers the roots of English property laws and the effects of French, Spanish, and Mexican legacies. The author discusses topics such as water law, mining claims, and the Metes and Bounds and Torrens system of property registry. He provides a section of basic legal concepts applicable to land transactions and a glossary of special or semi-technical terms. Unlike most other topics related to surveying, there is no math associated with the topics given; yet the subjects can be complex and tricky. Subdividing the Land is a resource of many interrelated topics, and thus presents a knowledge base for land surveyors and the background for handling many types of land transactions conducted by real estate agents, engineers, architects, and lawyers.

A close relationship exists between GIS and numerous applications, including cartography, photogrammetry, geodesy, surveying, computer and information science, and statistics, among others. Scientists coined the term "geographic information science (GIScience)" to describe the theory behind these fields. A Research Agenda for Geographic Information Science extensively details the issues and fundamental scientific problems that must be solved if the use of GIS in these and other fields is to advance. Immediately following the founding of the University Consortium for Geographic Information Science (UCGIS), the group identified in a Research Agenda the topics that represented major challenges to the GIS research community. The first chapter of this book delivers an introduction to the agenda and to the collective guidance that the agenda provides to researchers. Chapters 2-10 discuss nine original research challenges. Chapters 11-14 provide the basis of the agenda's four "Emerging Themes." Each chapter, written by researchers involved in the conception of the topics, discusses basic research elements, the UCGIS approach, the need for the National research agenda, contributions to knowledge and society, and offers a complete set of references. The final section draws general conclusions about the UCGIS approach and the defined research challenges.

Contents:
Foreword
Acknowledgments
Contents
List of contributors
List of Figures
List of tables
List of abbreviations
List of Appendices
Preface

CHAPTER 1 SDIs
1.1 Introduction
1.2 Building Spatial Data Infrastructures
1.2.1 Building Human Capacity through Partnerships and Networks
1.2.2 Support Resources for Developing the People Developing SDIs
1.3 Strengthening Institutional Capacity
1.3.1 The Need for Capacity Building to Facilitate SDI Development.
1.3.2 The Role of Research in SDI Development.
1.4 Sustainable Development as a research driver
1.4.1 The Triple Bottom Line
1.4.2 Technology
1.5 SDI development into the future
1.6 Conclusion
1.7 References

CHAPTER 2 Spatial Data Infrastructures:Concept, Nature And SDI Hierarchy
2.1 Introduction
2.2 The Need for Spatial Data
2.2.1 Sharing Spatial Data
2.2.2 Spatial Data and Decision Support Systems
2.3 Spatial Data Infrastructure
2.3.1 SDI Nature and Characteristics
(a) Partnerships
(b) Different Views to Understanding and Development
(c) The Importance of People
(d) Dynamic Nature
2.3.2 Current SDI initiatives (Global, Regional, National, State, Local)
2.4 SDI Hierarchy
2.4.1 The Theory of Hierarchy
(a) Definition of Hierarchy
(b) Purpose and Levels of a Hierarchical Structure
2.4.2 Hierarchical Reasoning
(a) Principles of HSR
(b) Properties of Hierarchies
2.4.3 Different Views on SDI Hierarchy
2.5 Applying Hierarchy Theory on SDIs
2.5.1 Hierarchy Theory and An SDI Hierarchy
2.6 Relationships among Different SDIs
2.7 Conclusion

CHAPTER 3 Global Initiatives
3.1 Introduction
3.2 GSDI
3.2.1 History and Background
3.2.2 SDI Components and Organisational Model
3.2.3 SDI Current Status of Development
3.2.4 Issues and Challenges
3.2.5 Future Plans and Discussion
3.3 Global Map
3.3.1 Background
3.3.2 SDI Components and Organisational Model
(a) Institutional Arrangements
(b) Technical Standards
(c) Fundamental Data
3.3.3 SDI Current Status of Development
3.3.4 Issues and Challenges
3.3.5 Future Plans and Discussion
3.4 Other Multi-National Initiatives
3.5 Evaluation of Global Initiatives
3.6 Recommendations and Future Directions
3.7 References

CHAPTER 4 Regional SDIs
4.1 Introduction
4.2 European Umbrella Organisation For Geographic Information (EUROGI)
4.2.1 History and background
4.2.2. Current Status
4.2.3. Issues and Challenges
4.3 Permanent Committee On GIS Infrastructure For Asia And The Pacific (PCGIAP)
4.3.1 History and Background
4.2.1 Current Status of Development
(a) Institutional Framework
(b) Technical Standards
(c) Fundamental Datasets
(d) Access network
4.3.3 Issues and Challenges
4.3.4 Future Plans and Discussions
4.4 Permanent Committee On Spatial Data Infrastructure For The Americas (PCIDEA)
4.4.2 Current Status
4.4.3 Issues and Challenges
4.5 Comparative Evaluation
4.6 References

CHAPTER 5 Regional SDI Diffusion
5.1 Introduction
5.2 Asia and the Pacific region and Regional SDI activities: a case study
5.2.1 Current Progress of PCGIAP and APSDI development
5.3 SDI Diffusion
5.4 Influencing Factors for Regional SDI Diffusion
5.4.1 Environmental Factors
5.4.2 Capacity Factors
5.4.3 SDI Organisation Factors
5.5 SDI Development Models
5.6 Recommendations
5.6.1 Organisational Restructure
5.6.2 Redesign Future Strategy Based on Asia-Pacific Social System
5.6.3 Modify APSDI Conceptual Model
5.6.4 Adopting SDI Process-Based Model
5.7 Conclusion and Recommendations
5.8 References

CHAPTER 6 National SDI Initiatives
6.1 Introduction
6.2 Overview on National SDI
6.3 Role and Relationships within SDI Hierarchy
6.4 Current Situation
6.4.1 First Generation of National SDI Initiatives
a) Australia SDI
b) USA National SDI
6.4.2 Second Generation of National SDI Initiatives
a) National Geographic Information Infrastructure for Lebanon
b) Iranian National Spatial Data Infrastructure
6.4.3 Comparative Analysis
6.5 Recommendations and Future Directions
6.6 References

CHAPTER 7 State SDI Initiatives
7.1 Introduction
7.2 Spatial Information
8.4.1 ANZLIC
8.4.2 Public Sector Mapping Agencies
8.4.3 Spatial Information Industry Action Agenda
8.4.4 Australian Spatial Information Business Association
8.4.5 Spatial Sciences Coalition
8.4.6 Spatial Information Cooperative Research Centre
8.5 ASDI Implementation
8.5.1 Fundamental Datasets
8.5.2 Australian Spatial Data Directory (ASDD)
8.5.3 ASDI Clearinghouse Definition
8.5.4 Pricing Policy
8.6 Current Issues And Future Directions
8.7 References

CHAPTER 9 State SDI Development: A Victorian Perspective
9.1 Introduction
9.1.1 Administration of Spatial Information
9.1.2 Development of State SDI
9.1.3 Spatial Information for Victoria: Early Beginnings
9.2 Victoria's Strategy for building SDI
9.2.1 Framework Information
9.2.2 Key Business Information
9.2.3 Custody
9.2.4 Metadata
9.2.5 Access Infrastructure
9.2.6 Pricing and Licensing
9.2.7 Spatial Accuracy
9.2.8 Awareness
9.3 Role and Responsibility for Developing Victorian SDI
9.4 Building Blocks Of Victoria's SDI
9.4.1 Land Exchange
9.4.2 Property Information Project (PIP)
9.4.3 Rural Addressing
9.4.4 Online Service Delivery
9.4.5 Land Channel
9.4.6 Land Channel Sales
9.5 Role within the Australian SDI Development
9.5.1 Growing the Private Sector
9.5.2 Participation in Standards Development
9.5.3 Jurisdictional Linkages
9.6 Conclusion
9.7 References

CHAPTER 10 SDI Development: Roles of Local and Corporate SDIs
10.1 Introduction
10.1.1 The Concept of SDI
10.2 Local SDI Development at Geelong
10.2.1 History of Geelong SDI Development
10.2.2 Current Geelong SDI (components and organisation model)
10.2.3 Linkages of Greater Geelong SDI through corporate SDI
10.3 Corporate SDI in multi-level SDI development- the case of DNRE
10.3.1 Catchment and Water
10.3.2 Parks Flora and Fauna
10.3.3. Department wide effort
10.4 Some patterns of SDI development
10.4.1 Some good practices
10.4.2 Two scales of SDI development
10.5 Conclusions
10.6 References

CHAPTER 11 Sustainable Development, the Place for SDIs and the Case for E-Governance
11.1 Introduction
11.2 The Effect on Government
11.2.1 Participatory Administration
11.2.2 Social Capital
11.3 The Role for SDIs
11.4 The Case for E-Governance
11.5 Conclusion

CHAPTER 12 Spatial Data Infrastructures and Descision-Support
12.1 Introduction
12.2 Spatial Decision-Making
12.2.1 Decision Process
12.2.2 Decision Complexity
12.2.3 Participation in Decision-Making
12.2.4 Measuring Reach and Range for Decision Support
12.3 The Role of SDIs in Decision-Support
12.4 Institutional Frameworks to Support Decision-Making
12.4.1 People
12.4.2 Policies
12.4.3 Mechanisms
12.5 The Case for Decision-Enabled SDI
12.6 Conclusions
12.7 References

CHAPTER 13 Financing Spatial Data Infrastructure Development: Examining Alternative Funding Models
13.1 Introduction
13.2 The Economic issues of SDI implementation
13.3 The Concept of SDI Funding Models
13.3.1 Funding Models of the First Generation of SDIs
13.4 Alternative Funding Models
13.4.1 Infrastructure Classification
(a) Natural Monopoly
13.4.2 Funding Models for SDIs Classified as Classic Infrastructures/Natural Monopolies
13.4.3 Funding Models for SDIs Classified as Network Infrastructures
13.5 Customizing the Alternative Funding Models for Emerging Nations
13.6 Conclusion
13.7 References

CHAPTER 14 Developing Evaluation and Performance Indicators for SDIs
14.1 Introduction
14.2 Land Administration Systems and the Role of SDIs
14.3 Evaluation And A Framework For Evaluation
14.4 Evaluation of SDIs
14.5 Conclusions
14.6 References


CHAPTER 15 Administrative Boundary Design in Support of SDI Objectives
15.1 Introduction
15.2 A Definition of the Spatial Hierarchy Problem
15.2.1 The First Solution: surface modelling
15.2.2 The Second Solution: data interpolation
15.2.3 The Third Solution: derived boundaries
15.2.4 The Fourth Solution: re-aggregation
15.3 Administrative Boundaries within SDI
15.3.1 Access
15.3.2 People
15.3.3 Data
(a) Confidentiality
(b) The modifiable-area-unit problem (MAUP)
15.3.4 Technical standards
(a) Hierarchical spatial reasoning (HSR) applied to administrative boundaries
(b) The structure of administrative boundaries
15.3.5 Policy
15.3.6 Summary
15.4 Conclusion
15.5 References

CHAPTER 16 SDI and Location Based Wireless Applications
16.1 Introduction
16.2 SDI as a foundation for location based services
16.3 Augmenting the SDI Model
16.3.1 Access Network
16.3.2 Policies
16.3.3 Standards
16.3.4 Data
16.3.5 People
16.4 Framework to Facilitate Wireless Applications
16.4.1 SDI Requirements
16.4.2 User Environment
16.5 Case Study
16.5.1 Use Case Scenarios
16.6 Discussion, Recommendations and Future Directions
16.7 References

CHAPTER 17 SDI and Positional Accuracy
17.1 Introduction
17.2 SDI And Positional Accuracy
17.3 Some Definitions
17.3.1 Reference Systems and Reference Frames
17.3.2 Dynamic Reference Frames
17.3.3 Height Datums
17.3.4 Coordinate Systems
17.3.5 Error
17.3.6 Positional Accuracy
17.3.7 Precision
17.4 Spatial Data Referencing
17.5 Transforming between different reference frames
17.6 Measuring and Recording Positional ACCURACY
17.7 Case Study 1: The GEOcentric datum of Australia
17.8 Case Study 2: PCGIAP
17.9 Conclusions And Recommendations
17.10 References

CHAPTER 18 Future Direction for SDI Development
18.1 Introduction
18.2 SDI Development Issues
18.3 SDI Development Models
18.3.1 The Product and Process-based Models
18.3.2 Assessment of Current SDI Initiatives
18.4 Relationships between SDI Hierarchy and different Models of SDI Development
18.5 Conclusion and Recommendations
18.6 References

Andean dry forest ecosystems are threatened by deforestation and unsustainable land use methods. The negative effects for the livelihood of the local population, biodiversity, and the regional climate could be countered by reforestation measures; however, dry land forests have not attracted the same level of interest and investment like other ecosystems. This book describes the development of a priority-zone map for reforestation measures, showing where reforestation might have the greatest social and ecological benefits. To achieve this, a problem analysis of a case study region is conducted and thematic reforestation benefits are determined. Using remote sensing and GIS, the areas where benefits can be obtained are mapped in individual layers and compiled into a summarizing priority-zone map. It is thus possible to identify areas where reforestation would achieve multiple benefits. The concept of priority maps could be used to facilitate reforestation strategies by local communities and municipal governments and could thus contribute to initiate an integrated forest and landscape restoration of the Bolivian montane dry forests.

Geographis Information Systems (GIS) and related technologies have a new and powerful role to play in archaeological interpretation
Beginning with a conceptual approach to the representation of space adopted by the GIS; the book examines spatial databases; the acqusition and compilation of data; the analytical functionality of GIS and the creation and utilisation of critical foundation data layers such as the Digital Elevation Model (DEM).
The ways in which GIS can most usefully facilitaate archaeological analysis and interpretation is then explored, particularly as a tool for the management of archaeological resources. Formal analysis of archaeological material, and the use of trend surface, contouring and interpolation proceedures are considered. Predictive modeling analysis of visibility and intervisibility are explained. Finally, there is a discussion of leading-edge issues, including three-dimensional GIS, object oriented GIS, the relationship between GIS and 'Virtual Reality' technologies, and the integration of GIS with distributed systems and the internet.
The approach is light, and the detail is kept to a minimum, recognising that most readers are simply interested in using GIS effectively. The text is carefully illustrated with worked case-studies usingarchaeological data. The book provides a single reference source for archaeologists - students, professional archaeologists and academics in archaeology as well as those in anthrolpology and related disciplines.
Key Features
* accessible textbook
* heavily illustrated
* full colour section

Real Estate and GIS focuses on the application of geographic information systems (GIS) and mapping technologies in the expanding property and real estate discipline. Whilst a thorough understanding of location is understood to be fundamental to the property discipline, real estate professionals and students have yet to harness the full potential of spatial analysis and mapping in their work. This book demonstrates the crucial role that technological advances can play in collecting, organising and analysing large volumes of real estate data in order to improve decision-making. International case studies, chapter summaries and discussion questions make this book the perfect textbook for property and applied GIS courses. Property and real estate professionals including surveyors, valuers, property developers, urban economists and financial analysts will also find this book an invaluable guide to the understanding and application of GIS technology within a real estate industry context.