This book presents the current research on space-based navigation models and the contents of spaces used for seamless indoor and outdoor navigation. It elaborates on 3D spaces reconstructed automatically and how indoor, semi-indoor, semi-outdoor, and outdoor spaces can mimic the indoor environments and originate a network based on the 3D connectivity of spaces. Case studies help readers understand theories, approaches, and models, including data preparation, space classification and reconstruction, space selection, unified space-based navigation model derivation, path planning, and comparison of results. Features: Provides novel models, theories, and approaches for seamless indoor and outdoor navigation path planning Includes real-life case studies demonstrating the most feasible approaches today Presents a generic space definition framework that can be used in research areas for spaces shaped by built structures Develops a unified 3D space-based navigation model that allows the inclusion of all types of spaces as 3D spaces and utilizes them for seamless navigation in a unified way Intended to motivate further research and developments, this book suits students, researchers, and practitioners in the field, and serves as a helpful introductory text for readers wanting to engage in seamless indoor/outdoor navigation research and teaching.

1. Captures advanced technologies and applications for assimilation and implementation and addresses a wide spectrum of water issues. 2. Provides real world applications and case studies of advanced spectral and spatial sensors combined with geospatially driven water process modelling. 3. Details applications of the latest remote sensor systems including GRACE, SMAP, AVIRIS, Sentential, MODIS, Landsat 8, RapidEye, AirSWOT, and pays special attention to multidisciplinary cases studies. 4. It is global in coverage with applications demonstrated by more than 170 experts from around the world. 5. Edited by extremely qualified authors with lifelong expertise in water sciences and with an extensive record in books and journal publications.

Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. Includes over 200 equations that illustrate how to follow examples in the book.

This is a comprehensive resource that integrates the application of innovative remote sensing techniques and geospatial tools in modeling Earth systems for environmental management beyond customary digitization and mapping practices. It identifies the most suitable approaches for a specific environmental problem, emphasizes the importance of physically based modeling, their uncertainty analysis, advantages, and disadvantages. The case studies on the Himalayas with a complex topography call for innovation in geospatial techniques to find solutions for various environmental problems. Features: Presents innovative geospatial methods in environmental modeling of Earth systems. Includes case studies from South Asia and discusses different processes and outcomes using spatially explicit models. Explains contemporary environmental problems through the analysis of various information layers. Provides good practices for developing countries to help manage environmental issues using low-cost geospatial approaches. Integrates geospatial modeling with policy and analysis its direct implication in decision making. Using a systems' approach analysis, Geospatial Modeling for Environmental Management: Case Studies from South Asia shall serve environmental managers, students, researchers, and policymakers.

Provides modern surveying practices with free software algorithm and R toolset for active learning Includes case studies from different geographical areas using arbitrary and international cartographic reference systems Enables and demonstrates the integration of traditional geomatics with nowadays geospatial big data technologies Explains data standards, equipment used, possible analyzes and the importance of error evaluation for scientific surveying Discusses different scales of landscapes and bring together the experiences of leading experts in the field

Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

Re-envisioning Advances in Remote Sensing: Urbanization, Disasters and Planning aims at portraying varied advancements in remote sensing applications, particularly in the fields of urbanization, disaster management and regional planning perspectives. The book is organized into three sections of overlapping areas of research covering chief remote sensing applications. Apart from introducing the advances in remote sensing through Indian remote sensing developments, it depicts the broader themes of: urbanization and its impacts; geospatial technology for disaster management; and, remote sensing applications in models and planning. It also provides outlook to future research agenda for remote sensing. Features: * Depicts advances in remote sensing in major fields through applications of geospatial technologies. * Covers remote sensing applications in varied aspects of urbanization, urban problems and disasters. * Includes advancements in remote sensing in model building and planning perspectives. * Analyses the usage of smartphones and other digital devices in mapping urban problems and monitoring disaster risks. * Explores future agenda for remote sensing advances and its ever-widening horizon. This book would be of interest to all the researchers and graduate students pursuing studies in the fields of remote sensing, GIS, geospatial technologies, urbanizations, disaster management, regional planning, environmental sciences, natural resource management and related fields.

Providing new developments in Geodesy, Cartography, and Geoinformatics

This book offers a unique multidisciplinary integration of the physics of turbulence and remote sensing technology. Remote Sensing of Turbulence provides a new vision on the research of turbulence and summarizes the current and future challenges of monitoring turbulence remotely. The book emphasizes sophisticated geophysical applications, detection, and recognition of complex turbulent flows in oceans and the atmosphere. Through several techniques based on microwave and optical/IR observations, the text explores the technological capabilities and tools for the detection of turbulence, their signatures, and variability. FEATURES Covers the fundamental aspects of turbulence problems with a broad geophysical scope for a wide audience of readers Provides a complete description of remote-sensing capabilities for observing turbulence in the earth's environment Establishes the state-of-the-art remote-sensing techniques and methods of data analysis for turbulence detection Investigates and evaluates turbulence detection signatures, their properties, and variability Provides cutting-edge remote-sensing applications for space-based monitoring and forecasts of turbulence in oceans and the atmosphere This book is a great resource for applied physicists, the professional remote sensing community, ecologists, geophysicists, and earth scientists.

This book explores how we create deep maps, delving into the development of methods and approaches that move beyond standard two-dimensional cartography. Deep mapping offers a more detailed exploration of the world we inhabit. Moving from concept to practice, this book addresses how we make deep maps. It explores what methods are available, what technologies and approaches are favorable when designing deep maps, and what lessons assist the practitioner during their construction. This book aims to create an open-ended way in which to understand complex problems through multiple perspectives, while providing a means to represent the physical properties of the real world and to respond to the needs of contemporary scholarship. With contributions from leading experts in the spatial humanities, chapters focus on the linked layers of quantitative and qualitative data, maps, photographs, images, and sound that offer a dynamic view of past and present worlds. This innovative book is the first to offer these insights on the construction of deep maps. It will be a key point of reference for students and scholars in the digital and spatial humanities, geographers, cartographers, and computer scientists who work on spatiality, sensory experience, and perceptual learning.

Detailed and accurate information on the spatial distribution of individual species over large spatial extents and over multiple time periods is critical for rapid response and effective management of environmental change. The twenty first century has witnessed a rapid development in both fine resolution sensors and statistical theories and techniques. These innovations hold great potential for improved accuracy of species mapping using remote sensing. Fine Resolution Remote Sensing of Species in Terrestrial and Coastal Ecosystems is a collection of eight cutting-edge studies of fine spatial resolution remote sensing, including species mapping of biogenic and coral reefs, seagrasses, salt and freshwater marshes, and grasslands. The studies illustrate the power of fine resolution imagery for species identification, as well as the value of unmanned aerial vehicle (UAV) imagery as an ideal source of high-quality reference data at the species level. The studies also highlight the benefit of LiDAR (Light Detection and Ranging) data for species identification, and how this varies depending on the species of interest as well as the nature of the context in which the species is found. The broad range of applications explored in the book demonstrates the major contribution of remote sensing to species-level terrestrial and coastal ecosystem studies as well as the potential for future advances. The chapters in this book were originally published as a special issue of the International Journal of Remote Sensing.

Geocomputation is the use of software and computing power to solve complex spatial problems. It is gaining increasing importance in the era of the 'big data' revolution, of 'smart cities', of crowdsourced data, and of associated applications for viewing and managing data geographically - like Google Maps. This student focused book: Provides a selection of practical examples of geocomputational techniques and 'hot topics' written by world leading practitioners. Integrates supporting materials in each chapter, such as code and data, enabling readers to work through the examples themselves. Chapters provide highly applied and practical discussions of: Visualisation and exploratory spatial data analysis Space time modelling Spatial algorithms Spatial regression and statistics Enabling interactions through the use of neogeography All chapters are uniform in design and each includes an introduction, case studies, conclusions - drawing together the generalities of the introduction and specific findings from the case study application - and guidance for further reading. This accessible text has been specifically designed for those readers who are new to Geocomputation as an area of research, showing how complex real-world problems can be solved through the integration of technology, data, and geocomputational methods. This is the applied primer for Geocomputation in the social sciences.

Sundarbans, a UNESCO heritage site, is the world's largest single chunk of mangroves distributed on the Indian and Bangladesh coasts. The mangroves and associated ecosystems are one of the most fertile ecosystems of the earth. Sundarbans Mangrove Systems: A Geo-Informatics Approach portrays different perspectives of studying Sundarbans and mangroves using geospatial analysis. This book highlights the major issues with the Sundarbans mangrove forest, its future conservation strategies and its ecological importance using geo-informatics technology. It explains the usage of remote sensing data for providing information about the present state of mangroves and their tropic status, including assessment in terms of extent, density of community, condition, diversity, identifying potential habitats and heterogeneity. Furthermore, it discusses the use of hyperspectral remote sensing data for species level classification of mangroves, community zonation for biodiversity assessment and for preparing management plans for conservation. KEY FEATURES Exclusively covers the ecological state of Sundarbans (mangrove systems) through geo-informatic studies Describes the application of a combination of geomorphological, biogeochemical and remote sensing methods to the analysis of temporal changes Includes environmental factors affecting the health and decline of mangroves Covers biodiversity and ecological controls in mangroves ecosystems Discusses a remote sensing approach for tropical forested island and mangroves mapping This book is aimed at graduate students and researchers in environmental sciences, ecology, marine sciences, biology, geosciences and GIS/remote sensing areas.

Satellite images acquired at night provide a visually arresting perspective of the Earth and the human activities that light up the otherwise mostly dark Earth. These night-time light satellite images can be compiled into a geospatial time series that represent an invaluable source of information for both the natural and social sciences. Night-time light remote sensing has been shown to be particularly useful for a range of natural science and social science applications, including studies relating to urban development, demography, sociology, fishing activity, light pollution and the consequences of civil war. Key sensors for these time-series include the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) and the Suomi National Polar-orbiting Partnership Satellite's Visible Infrared Imaging Radiometer Suite Day/Night Band (Suomi NPP/VIIRS DNB). An increasing number of alternative sources are also available, including high spatial resolution and multispectral sensors. This book captures key methodological issues associated with pre-processing night-time light data, documents state of the art analysis methods, and explores a wide range of applications. Major sections focus on NPP/VIIRS DNB processing; inter-calibration between NPP/VIIRS and DMPS/OLS; applications associated with socio-economic activities, applications in monitoring urbanization; and fishing activity monitoring. The chapters in this book were originally published as a special issue of the International Journal of Remote Sensing.

Monitoring continuous phenomena by stationary and mobile sensors has become a common due to the improvement in hardware and communication infrastructure and decrease in it's cost. Sensor data is now available in near real time via web interfaces and in machine-readable form, facilitated by paradigms like the Internet of Things (IoT). There are still some obstacles in the usability of the data since the positions (in space and time) of observation and the positions of interest usually do not coincide. Interpolation is the technique to fill such gaps and there are manifold methods to perform it. To actually operate a monitoring system, there are problems like unambiguous identification of interpolation method and associated parameters, appropriate interface to store observations and retrieve interpolated data, continuous update of the interpolation model for real time monitoring, compression and progressive retrieval of observational data and critical states definition and notification by using aggregation of values. This book proposes a general system architecture that addresses these problems. It is not confined to details about particular interpolation methods but rather takes a holistic view on the problem of monitoring. State-of-the-art technologies like geostatistics, sensor web enablement and field data types are introduced and applied in order to provide a viable toolset for the problem domain. The focus is on the overall organization of the monitoring and the architectural design of the software system and the associated simulation framework that is used to systematically evaluate different monitoring approaches. The whole cycle of a monitoring entailing observation, interpolation, discretization, storage, retrieval and notification is covered. Concrete solutions for several common problems in this context are provided.

This book studies the increasing use of data analytics and technology in urban planning and development in developing nations. It examines the application of urban science and engineering in different sectors of urban planning and looks at the challenges involved in planning 21st-century cities, especially in India. The volume analyzes various key themes such as auditory/visual sensing, network analysis and spatial planning, and decision-making and management in the planning process. It also studies the application of big data, geographic information systems, and information and communications technology in urban planning. Finally, it provides data-driven approaches toward holistic and optimal urban solutions for challenges in transportation planning, housing, and conservation of vulnerable urban zones like coastal areas and open spaces. Well supplemented with rigorous case studies, the book will be of interest to scholars and researchers of architecture, architectural and urban planning, and urban analytics. It will also be useful for professionals involved in smart city planning, planning authorities, urban scientists, and municipal and local bodies.

This book studies the increasing use of data analytics and technology in urban planning and development in developing nations. It examines the application of urban science and engineering in different sectors of urban planning and looks at the challenges involved in planning 21st-century cities, especially in India. The volume analyzes various key themes such as auditory/visual sensing, network analysis and spatial planning, and decision-making and management in the planning process. It also studies the application of big data, geographic information systems, and information and communications technology in urban planning. Finally, it provides data-driven approaches toward holistic and optimal urban solutions for challenges in transportation planning, housing, and conservation of vulnerable urban zones like coastal areas and open spaces. Well supplemented with rigorous case studies, the book will be of interest to scholars and researchers of architecture, architectural and urban planning, and urban analytics. It will also be useful for professionals involved in smart city planning, planning authorities, urban scientists, and municipal and local bodies.

Global Navigation Satellite Systems (GNSS) and their associated technologies have advanced by leaps and bounds in the nine years since the first edition of this book was published. The concept of survey has changed, especially in the disciplines of geomatics and geoinformatics. This revised and updated second edition provides a thorough understanding of the basic principles and techniques of GNSS, analyzes all four active systems, and explains clearly how each of these systems works. Because of its straightforward treatment of the subject, readers will gain an insight into the techniques, trends, and applications of GNSS and develop knowledge on selecting an appropriate GNSS instrument. Written for students and practitioners in geoinformatics, geomatics engineering, surveying, and remote sensing and GIS, this introductory and practical book includes questions and exercises in each chapter. Key Features: * Furnishes detailed information on GPS, GLONASS, Galileo, BeiDou, and other regional and augmented systems * Provides practical guidance for surveying, mapping, and navigation with GNSS * Sheds light on the latest developments and modern trends of GNSS * Includes a detailed glossary of related terms * Contains many illustrations that complement the text * Exercises for each chapter * MCQ, solution manual for mathematical problems, and PPT as online resources

The innovation in space technologies has generated a new method for observing and monitoring tsunamis from space. Most tsunami remote sensing studies focus on using classical image processing tools or conventional edge detection procedures. However, these methods do not use modern physics, applied mathematics, signal communication, remote sensing data and innovative space technologies. This book equips readers to understand how to monitor tsunamis from space with remote sensing technology art to create a better alarm warning system.

Master GIS Applications on Modelling and Mapping the Risks of Diseases Infections transmitted by mosquitoes, ticks, triatomine bugs, sandflies, and black flies cause significant rates of death and disease, especially in developing countries. Why are certain places more susceptible to vector-borne diseases? Modelling Interactions Between Vector-Borne Diseases and Environment Using GIS reveals how using geographic information systems (GISs) can provide a greater understanding of how vector-borne diseases are spread and explores the use of geographical techniques in vector-borne disease monitoring, management, and control. This text provides readers with a better understanding of the vector-borne disease problem and its impact on public health. Introduces New Spatial Approaches Based on Location and Environment The book exposes readers to information on how to identify vector hotspots, determine when and where they can occur, and eliminate vector breeding sites. Utilizing simple illustrations based on real data, as well as the authors' more than 20 years of experience in the field, this text combines key spatial analysis techniques available in modern GIS with real-world applications. It offers step-by-step instruction on developing vector-borne disease risk models at different spatial and temporal scales and helps practitioners formulate disease causation hypotheses and identify areas at risk. In addition, it addresses medical geography, GIS, spatial analysis, and modelling, and covers other factors related to the spread of vector-borne diseases. This book: Gives an overview of common vector-borne diseases, GIS-based mapping and modelling, impacts of climate change on vector distributions, and availability and importance of accurate epidemiologically relevant spatial data Describes modelling and simulating the prevalence of vector-borne diseases around the world Summarizes some key spatial techniques and how they can be used to aid in the analysis of geographical and attributed data Defines the concept of establishing and characterizing spatial data systems, including their quality, errors, references, and issues of scale, and building such a system from often quite separate, disparate sources Shows how to develop weather-based predictive modelling, which can be used to predict the weekly trend of vector abundance Provides a GIS case study for modelling the future potential distribution of vector-borne disease based on different climatic change scenarios Modelling Interactions Between Vector-Borne Diseases and Environment Using GIS combines spatial analysis techniques available in modern GIS, together with real-world applications to provide you with a better understanding of ways to map, model, prevent, and control vector-borne diseases.

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from the basics of disease mapping to the most advanced topics in this field. A multidimensional framework is offered that makes possible the joint modeling of several risks patterns corresponding to combinations of several factors, including age group, time period, disease, etc. Although theory will be covered, the applied component will be equally as important with lots of practical examples offered. Features: Discusses the very latest developments on multivariate and multidimensional mapping. Gives a single state-of-the-art framework that unifies most of the previously proposed disease mapping approaches. Balances epidemiological and statistical points-of-view. Requires no previous knowledge of disease mapping. Includes practical sessions at the end of each chapter with WinBUGs/INLA and real world datasets. Supplies R code for the examples in the book so that they can be reproduced by the reader. About the Authors: Miguel A. Martinez Beneito has spent his whole career working as a statistician for public health services, first at the epidemiology unit of the Valencia (Spain) regional health administration and later as a researcher at the public health division of FISABIO, a regional bio-sanitary research center. He has been also the Bayesian Hierarchical Models professor for several seasons at the University of Valencia Biostatics Master. Paloma Botella Rocamora has spent most of her professional career in academia although she now works as a statistician for the epidemiology unit of the Valencia regional health administration. Most of her research has been devoted to developing and applying disease mapping models to real data, although her work as a statistician in an epidemiology unit makes her develop and apply statistical methods to health data, in general.