This book highlights studies of differentiation problems of natural geosystems because of anthropogenic impact. The systematic methodology of comprehensive ecological assessment of anthropogenic impact on natural geosystems and their differentiations on the level of technogenic conditionality for ensuring rational environmental management and environmental protection are discussed. The practical importance of this book lies in the evidence-based recommendations and actions for conservation and quality management of the environment in order to decrease the degree of anthropogenic impact and in prevention of degradation processes. The book is useful to the researchers, industrial, scientific, and other organizations in establishing the purpose of the problem and solution to environmental protection and rational environmental management.

Geographical Information System and Crime Mapping features a diverse array of Geographic Information System (GIS) applications in crime analysis, from general issues such as GIS as a communication process, interjurisdictional mapping and data sharing to specific applications in tracking serial killers and predicting violence-prone zones. It supports readers in developing and implementing crime mapping techniques. The distribution of crime is explained with reference to theories of human ecology, transport network, built environment, housing markets, and forms of urban management, including policing. Concepts are supported with relevant case studies and real-time crime data to illustrate concepts and applications of crime mapping. Aimed at senior undergraduate, graduate students, professionals in GIS, Crime Analysis, Spatial Analysis, Ergonomics and human factors, this book: Provides an update of GIS applications for crime mapping studies Highlights growing potential of GIS for crime mapping, monitoring, and reduction through developing and implementing crime mapping techniques Covers Operational Research, Spatial Regression model, Point Analysis and so forth Builds models helpful in police patrolling, surveillance and crime mapping from a technology perspective Includes a dedicated section on case studies including exercises and data samples

Drive innovation, expand capacity, coordinate maintenance, and reduce costs. Location intelligence is changing the way transportation agencies and departments protect and maintain their infrastructure and achieve operational excellence. Mapping plays a big part, but geospatial analytics, real-time dashboards, and mobile applications are driving new, more efficient workflows and paving the way for innovative, cost-effective solutions. With advancements in smart technologies, location intelligence for transportation management is not just for GIS specialists. In Moving Forward: GIS for Transportation, see how ports, airports, transit authorities, and departments of transportation around the world have implemented geographic information systems (GIS) to visualize and analyze data for operational efficiency, safety and security, asset management, and planning and sustainability. In this collection of case studies and guidance, learn about how GIS was used to: * Expand airport capacity within limited space, while saving millions. * Centralize multi-faceted port security for monitoring daily operations. * Coordinate daily transit maintenance work on $1 trillion in hard assets. * Plan modern data governance for a state-wide department of transportation. Through web apps, online maps, dashboards, and other GIS solutions, transportation professionals develop a deeper understanding of infrastructure maintenance and operational performance within a real-world context, increasing efficiency, while improving communication and collaboration. Discover how GIS and location intelligence are helping transportation organizations strengthen their ability to maintain roads and highways, railway systems, and other vital infrastructures with Moving Forward: Applying GIS for Transportation. -- Keith Mann

Social Sensing and Big Data Computing for Disaster Management captures recent advancements in leveraging social sensing and big data computing for supporting disaster management. Specifically, analysed within this book are some of the promises and pitfalls of social sensing data for disaster relevant information extraction, impact area assessment, population mapping, occurrence patterns, geographical disparities in social media use, and inclusion in larger decision support systems. Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive, heterogeneous, noisy, and unreliable in some aspects. It comes in continuous streams, and often lacks geospatial reference information. Together, these issues represent a grand challenge toward fully leveraging social sensing for emergency management decision making under extreme duress. Meanwhile, big data computing methods and technologies such as high-performance computing, deep learning, and multi-source data fusion become critical components of using social sensing to understand the impact of and response to the disaster events in a timely fashion. This book was originally published as a special issue of the International Journal of Digital Earth.

This book provides a state-of-the art overview of satellite archaeology and it is an invaluable volume for archaeologists, scientists, and managers interested in using satellite Earth Observation (EO) to improve the traditional approach for archaeological investigation, protection and management of Cultural Heritage.

The recent increasing development of EO techniques and the tremendous advances in Information and Communication Technologies (ICT) have resulted primarily in Cultural Heritage applications. The book focuses on new challenging prospects for the use of EO in archaeology not only for probing the subsurface to unveil sites and artifacts, but also for the management and valorization as well as for the monitoring and preservation of cultural resources. The book provides a first-class understanding of this revolutionary scenario which was unthinkable several years ago.

The book offers: (i) an excellent collection of outstanding articles focusing on satellite data processing, analysis and interpretation for archaeological applications, (ii) impressive case studies, (iii) striking examples of the high potential of the integration of multi-temporal, multi-scale, multi-sensors techniques.

Each chapter is composed as an authoritative contribution to help the reader grasp the value of its content. The authors are renowned experts from the international scientific community.

"Audience" This book will be of interest to scientists in remote sensing applied to archeology, geoarcheology, paleo-environment, paleo-climate and cultural heritage.

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As the use of geographical information systems develops apace, a significant strand of research activity is being directed to the fundamental nature of geographic information. This volume contains a collection of essays and discussions on this theme. What is geographic information? What fundamental principles are associated with it? How can it be represented? How does it represent the world? How can geographic information be quantified? How can it be communicated and related to the other information sciences? How does HCI tie in with it? A number of other more specific but relevant issues are considered, such as Spatio-temporal relationships, boundaries, granularity and taxonomy. This book is a revised and updated version of a collection of presentations given by a group of distinguished researchers in the field of Geographic Information Science who gathered in Manchester in July 2001. It should be useful for graduate students as well as researchers and high-level professionals.

The past 10 years have brought amazing changes to the technologies used to turn remotely sensed data into maps. As a result, the principles and practices necessary for assessing the accuracy of those maps have also evolved and matured. This third edition of Assessing the Accuracy of Remotely Sensed Data: Principles and Practices is thoroughly updated and includes five new chapters. Now 15 chapters long, this text is the only one of its kind to provide geospatial analysts with the requisite considerations, tools, and theory necessary to conduct successful and efficient map accuracy assessments; and map users with the knowledge to fully understand the assessment process to ensure effective use of maps. See What's New in the Third Edition: All original chapters have been updated to include new standards, practices, and methodologies. A new chapter on planning accuracy assessments. A new chapter on assessing maps created using object-based technologies. Two case study chapters - one showcasing the assessment of maps created from traditional methods, and one on the assessment of object-based maps. Emphasis on considering and planning for positional accuracy in concert with thematic accuracy. An appendix containing the internationally recognized ASPRS Positional Accuracy Standards. A new final chapter summarizing the key concepts, considerations and lessons learned by the authors in their decades of implementing and evaluating accuracy assessments. Assessing map accuracy is complex; however, the discussions in this book, together with the many figures, tables, and case studies, clearly present the necessary concepts and considerations for conducting an assessment that is both is practical, statistically reliable, and achievable.

This book provides readers with an insight into the development of a novel method for regridding gridded spatial data, an operation required to perform the map overlay operation and apply map algebra when processing spatial data. It introduces the necessary concepts from spatial data processing and fuzzy rulebase systems and describes the issues experienced when using current regridding algorithms. The main focus of the book is on describing the different modifications needed to make the problem compatible with fuzzy rulebases. It offers a number of examples of out-of-the box thinking to handle aspects such as rulebase construction, defuzzification, spatial data comparison, etc. At first, the emphasis is put on the newly developed method, and additional datasets containing information on the underlying spatial distribution of the data are identified. After this, an artificial intelligent system (in the form of a fuzzy inference system) is constructed using this knowledge and then applied on the input data to perform the regridding. The book offers an example of how an apparently simple problem can pose many different challenges, even when trying to solve it with existing soft computing technologies. The workflow and solutions to solve these challenges are universal and may therefore be broadly applied into other contexts.

Geospatial information modeling and mapping has become an important tool for the investigation and management of natural resources at the landscape scale. Spatial Statistics: GeoSpatial Information Modeling and Thematic Mapping reviews the types and applications of geospatial information data, such as remote sensing, geographic information systems (GIS), and GPS as well as their integration into landscape-scale geospatial statistical models and maps. The book explores how to extract information from remotely sensed imagery, GIS, and GPS, and how to combine this with field data-vegetation, soil, and environmental-to produce a spatial model that can be reconstructed and displayed using GIS software. Readers learn the requirements and limitations of each geospatial modeling and mapping tool. Case studies with real-life examples illustrate important applications of the models. Topics covered in this book include: An overview of the geospatial information sciences and technology and spatial statistics Sampling methods and applications, including probability sampling and nonrandom sampling, and issues to consider in sampling and plot design Fine and coarse scale variability Spatial sampling schemes and spatial pattern Linear and spatial correlation statistics, including Moran's I, Geary's C, cross-correlation statistics, and inverse distance weighting Geospatial statistics analysis using stepwise regression, ordinary least squares (OLS), variogram, kriging, spatial auto-regression, binary classification trees, cokriging, and geospatial models for presence and absence data How to use R statistical software to work on statistical analyses and case studies, and to develop a geospatial statistical model

Optical Remote Sensing is one of the main technologies used in sea surface monitoring. Optical Remote Sensing of Ocean Hydrodynamics investigates and demonstrates capabilities of optical remote sensing technology for enhanced observations and detection of ocean environments. It provides extensive knowledge of physical principles and capabilities of optical observations of the oceans at high spatial resolution, 1-4m, and on the observations of surface wave hydrodynamic processes. It also describes the implementation of spectral-statistical and fusion algorithms for analyses of multispectral optical databases and establishes physics-based criteria for detection of complex wave phenomena and hydrodynamic disturbances including assessment and management of optical databases. This book explains the physical principles of high-resolution optical imagery of the ocean surface, discusses for the first time the capabilities of observing hydrodynamic processes and events, and emphasizes the integration of optical measurements and enhanced data analysis. It also covers both the assessment and the interpretation of dynamic multispectral optical databases and includes applications for advanced studies and nonacoustic detection. This book is an invaluable resource for researches, industry professionals, engineers, and students working on cross-disciplinary problems in ocean hydrodynamics, optical remote sensing of the ocean and sea surface remote sensing. Readers in the fields of geosciences and remote sensing, applied physics, oceanography, satellite observation technology, and optical engineering will learn the theory and practice of optical interactions with the ocean.

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation. The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media. While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book. Introducing SAR imaging from a systems point of view, the author: Considers the recent development of MIMO SAR technology Includes selected GPU implementation Provides a numerical analysis of system parameters (including platforms, sensor, and image focusing, and their influence) Explores wave-target interactions, signal transmission and reception, image formation, motion compensation Covers all platform motion compensation and error analysis, and their impact on final image radiometric and geometric quality Describes a ground-based SFMCW system Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach is dedicated to the use, study, and development of SAR systems. The book focuses on image formation or focusing, treats platform motion and image focusing, and is suitable for students, radar engineers, and micr

This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.

This book provides insights into the benefits of using remote sensing data from a geoscientist's perspective, by integrating the data with the understanding of Earth's surface and subsurface. In 3 sections, the book takes a detailed look at what data explorationists use when they explore for hydrocarbon resources, assess different terrain types for planning and hazards and extract present-day geologic analogs for subsurface geologic settings. The book presents the usage of remote sensing data in exploration in a structured way by detecting individual geologic features as building blocks for complex geologic systems. This concept enables readers to build their own workflows for the assessment of complex geologic systems using various combinations of remote sensing data. Section 1 introduces readers to the foundations of remote sensing for exploration, covers various methods of image processing and studies different digital elevation and bathymetry models. Section 2 presents the concept of geomorphology as a means to integrate surface and subsurface data. Different aspects of rendering in 2D and 3D are explained and used for the interpretation and extraction of geologic features that are used in exploration. Section 3 addresses remote sensing for hydrocarbon exploration in detail, from geophysical data acquisition to development and infrastructure planning. The organization of this chapter follows an exploration workflow from regional to local modeling studying basin and petroleum system modeling as well as logistics planning of seismic surveys and near-surface modeling. Aspects of field development and infrastructure planning comprise multi-temporal and dynamic modeling. The section closes with a structured approach to extracting geologic analogs from interpreted remote sensing data. The book will be of interest to professionals and students working in exploration for hydrocarbons and water resources, as well as geoscientists and engineers using remote sensing for infrastructure planning, hazard assessment and dynamic environmental studies.

Coordinates are integral building tools for GIS, cartography, surveying and are vital to the many applications we use today such as smart phones, car navigation systems and driverless cars. Basic GIS Coordinates, Third Edition grants readers with a solid understanding of coordinates and coordinate systems and how they operate as well as valuable insight into what causes them to malfunction. This practical and comprehensive guide lays out the foundation of a coordinate system and the implications behind building it as it elaborates on heights, two coordinate systems, and the rectangular system.The previous editions described horizontal and vertical datums such as the North American Datum 1983 (NAD 83) and the North American Vertical Datum 1988 (NAVD 88). Both will be replaced in 2022 or thereabouts. The National Geodetic Survey (NGS) plans to replace NAD83 with a new semi-dynamic terrestrial reference frame for North America and a new vertical datum will replace NAVD88. The foundation of the new vertical datum will be a temporally tracked gravimetric geoid. The interim period is intended to smooth the transition to the new paradigm and this new edition explores the changes and provides assistance in understanding them.

The explosion of public interest in the natural environment can, to a large extent, be attributed to greater public awareness of the impacts of global warming and climate change. This has led to increased research interest and funding directed at studies of issues affecting sensitive, natural environments. Not surprisingly, much of this work has required the innovative application of GIS and has led to a crucial research question: How should the environment be represented, modeled, analyzed, and visualized within a GIS? With contributions from recognized international experts, Representing, Modeling, and Visualizing the Natural Environment explores the interplay between data representation, modeling, and visualization in environmental studies. It reviews state-of-the-art GIS applications for the natural environment and presents them in the context of a range of recent studies. This focus identifies analytical challenges and illustrates broader opportunities for applying GIS within other areas of the sciences and social sciences. The integrated approach reflects the need for a single volume covering all aspects While many texts cover aspects of GIS application within an environmental context, few of these books focus specifically on the natural environment nor do they integrate the questions that encompass the full process of enquiry associated with GIS application in studies of the environment. The thirteenth volume in the widely recognized Innovations of GIS series, this book investigates each of these questions in turn, explicitly addressing all aspects of GIS application in the natural environment.

GIS for Sustainable Development examines how GIS applications can improve collaboration in decision making among those involved in promoting sustainable development. This volume reviews leading GIScience, providing an overview of research topics and applications that enable GIS newcomers and professionals to apply GIScience methods to sustainable spatial planning. Divided into three parts, the book begins with an introduction to the issues of sustainability, focusing on concepts concerning GIS adoption and use within public organizations that are planning development. Part II focuses on GIScience methods, which can be used to support sustainable development and solve environmental problems. Part III presents research projects and best practices relating to different areas of application within the field. This text provides the latest research findings, delivers complete references to related publications, and supplies you with a complete reference framework for each topic.

This book explains the fundamentals and intricacies of telegeoinformatics. The book is divided into three parts: Theories and Technologies; Integrated Data and Technologies; and Applications. These sections are divided into smaller contributed chapters, each of which addresses a topic crucial to the understanding of telegeoinformatics. This volume covers the concepts and technologies related to GIS and geoprocessing, remote sensing, the GPS, and wireless systems. It also explores the main issues of integrated data and technologies in LBC, LBS, mediated reality, and mobile augmented reality systems. The final part discusses applications of telegeoinformatics in emergency response, mobile inspection data collection, and ITS.

Have you ever considered how much effect information technology has on society throughout the world? Progress often places lower income and marginalized communities at a distinct disadvantage. Community Participation and Geographic Information Systems, however, offers a detailed look at numerous incidences around the world where communities have actually taken control of the technology and really used it to their advantage. This is presented in the form of case studies and models such as Philadelphia's neighborhoods, the Atlanta Project, and neighborhood revitalization in Minneapolis, reflect on public participation in GIS concepts, best practices, constraints and opportunities.

One of the ongoing problems researchers in geography and GIS have is studying data that is inherently spatial over a long period of time. One of the main hurdles they have to overcome is the study of groups of people classified by their socio-economic status (one of the main means for governments, companies and research organisations to group together segments of the population). The amount of data collected by governments, business and research organisations has increased markedly in recent years. Geographic Information Systems have been more widely used than ever before for the storage and analysis of this information. Most GIS can handle this information spatially rather than temporally, and have difficulty with the management of socio-economic time series, which relate to spatial units. Accordingly, this book covers the issues ranging from the formal model to differentiate aspects of spatio-temporal data, through philosophical and fundamental reconsideration of time and space to the development of practical solutions to the problem. This book draws together an interdisciplinary group of scientists in the field of geography, computing, surveying and philosophy. It presents the definitive sourcebook on temporal GIS as applied to socio-economic units.

In today's world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source Software is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data. Specific Features of this Book: The first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow) Presents approaches suited for real world images and data targeting large scale processing and GIS applications Introduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration) Suited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills. Includes deep learning techniques through many step by step remote sensing data processing exercises.

This book is a compendium of peer reviewed papers resulting from the International Symposium on Spatial Data Handling (SDH), held in Ottawa, Canada, July 9-12, 2002. It presents a selection of papers that demonstrate a maturing in geographical information science (GISc). Of the many challenges under the general topic of spatial data handling, a number of key areas provide the focus for this book. They tackle issues such as database design and architecture, interoperability, integration, fusion, spatial reasoning, visualisation and web-based mapping, among a number of other aspects.

Optical Properties and Remote Sensing of Inland and Coastal Waters discusses the methodology and the theoretical basis of remote sensing of water. It presents physical concepts of aquatic optics relevant to remote sensing techniques and outlines the problems of remote measurements of the concentrations of organic and inorganic matter in water. It also details the mathematical formulation of the processes governing water-radiation interactions and discusses the development of bio-optical models to incorporate optically complex bodies of water into remote sensing projects. Optical Properties and Remote Sensing of Inland and Coastal Waters derives and evaluates the interrelationships among inherent optical properties of natural water, water color, water quality, primary production, volume reflectance spectra, and remote sensing. This timely and comprehensive text/reference addresses the increasing tendency toward multinational and multidisciplinary climate studies and programs.

This book shows how to build a "INFelecPHY GPS Unit" (IEP-GPS) tracking system for fleet management that is based on 3G and GPRS modules. This model should provide reliability since it deals with several protocols: 1) HTTP and HTTPS to navigate, download and upload in real time the information to a web server, 2) FTTP and FTTPS to handle in a non-real time the files to the web application, and 3) SMTP and POP3 to send and receive email directly from the unit in case of any alert. Similar to a mobile device, but without screen for display, it is multifunctional because it links to a GPRS module, a camera, a speaker, headphone, a keypad and screen.

Wireless Sensor Networks overcome the difficulties of other monitoring systems. However, they require further efficiencies for Outdoor Environment Monitoring (OEM) applications due to their harsh operational conditions, huge targeted areas, limited energy budget, and required 3D setups. A fundamental issue in defeating these practical challenges is deployment planning. The deployment plan is a key factor of many intrinsic properties of OEM networks, summarized in connectivity, lifetime, fault-tolerance, and cost-effectiveness. This book investigates the problem of WSNs deployments that address these properties in order to overcome the unique challenges and circumstances in OEM applications.

Remote sensing of impervious surfaces has matured using advances in geospatial technology so recent that its applications have received only sporadic coverage in remote sensing literature. Remote Sensing of Impervious Surfaces is the first to focus entirely on this developing field. It provides detailed coverage of mapping, data extraction, and modeling techniques specific to analyzing impervious surfaces, such as roads and buildings. Written by renowned experts in the field, this book reviews the major approaches that apply to this emerging field as well as current challenges, developments, and trends. The authors introduce remote sensing digital image processing techniques for estimating and mapping impervious surfaces in urban and rural areas. Presenting the latest modeling tools and algorithms for data extraction and analysis, the book explains how to differentiate roads, roofs, and other manmade structures from remotely sensed images for individual analysis. The final chapters examine how to use impervious surface data for predicting the flow of storm- or floodwater and studying trends in population, land use, resource distribution, and other real-world applications in environmental, urban, and regional planning. Each chapter offers a consistent format including a concise review of basic concepts and methodologies, timely case studies, and guidance for solving problems and analyzing data using the techniques presented.