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Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
This book contains a selection of refereed papers presented at the
6 Specialist Meeting on Microwave Radiometry and Remote Sensing of
the Environment held in Florence, Italy on March 15-18, 1999.
This study presents recent findings on home-ownership in the 1990s. It examines economic and social issues central to the housing market and provides an analysis of "winners" and "losers": those who gained financially and those who became victims of negative equity. Covering the postwar period the authors trace developments in the housing market in relation to class, race, gender and income with special reference to the growth and evolution of home-ownership since the Second World War; the sale of council houses; the role of government in encouraging home-ownership; and changes in bank and building society lending in the 1970s and 1980s and the consequences. This accessible volume should appeal to undergraduates of urban planning, human geography, social policy and applied economics but should also be of interest and value to policy makers.
This book departs from typical cartography textbooks, which tend to focus on the characteristics of the methods and means of expression. Instead, it offers an explanation of the individual perspective on the map as a specific product of civilization, one that constitutes a component of social communication. The layout highlights the essential property of cartographic notation, namely: the way of forming the map's content elements, adjusted to its purpose. This property is ensured thanks to the dimension of reference units in relation to the observation scale of the objects, and by topological consistency between the reference units system and real layout of the objects. An exploration of the characteristics of various ways of depicting a map's content elements, organized in the reference units dimension, is preceded by a general section accentuating the position of cartography among other sciences, as well as the definition and general properties of a map. The book's closing chapter includes a separate textbook overview of the applications of taxonomic methods in cartography.
This text in the series "Innovations in GIS", continues the theme of directions in geographical information systems research established by the four previous Research UK (GISRUK) conferences. The chapters reflect the interdisciplinary nature of GIS research and includes coverage of such themes as: virtual GIS; spatial analysis; artificial intelligence; spatial agents and fuzzy systems; and space-time GIS and GIS applications.
Recent advances in theory and observations using passive microwave remote sensing have hightlighted the potential of spaceborne sensors for contributing to the required land surface measurements of soils, vegetation, snow cover and precipitation. Furthermore, the spatial resolution of passive microwave observations matches the special scales of large-scale models of land-atmosphere interactions both for data assimilation and validation. In order to stimulate and focus this research a workshop, sponsored by ESA and NASA, was organized to review the state-of-the-art in microwave radiometry related to land applications and to exchange ideas leading into new directions for future research. This volume contains the refereed papers from the aforementioned ESA/NASA workshop, which are arranged by topic, as well as the (edited) working group reports.
This book presents a comprehensive coverage of remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies in detail how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence. The author explains multiple methods of attaining data, describes the pros and cons of each method, and encourages readers to choose the best method applicable to their case. The author offers a practical approach to data analysis using the most appropriate methods and software. 1. Covers all major natural hazards including hurricanes, tornadoes, wildfires, and avalanches. 2. Studies each natural hazard holistically, ranging from spatial extent, severity, impact assessment, causes, and prediction of occurrence. 3. Explains different remotely sensed data and the most appropriate method used. 4. Compares different ways of sensing and clarifies the pros and cons of any selected data or their analysis. 5. Provides ample examples of each aspect of a natural hazard studied augmented with graphic illustrations and quality assurance information. All professionals working in the field of natural hazards, senior undergraduate, and graduate students, will find in-depth approaches and sufficient information to become knowledgeable in the methods of yielding and analyzing data provided with remote sensing technology, ultimately providing a deeper understanding of natural hazards.
Geographic information system (GIS) computer technology is
revolutionizing the way we interact with information. Data, text,
drawings, maps, and images contain information that can be accessed
and used intuitively through drawings containing graphical
representations of the facilities to which they apply, e.g.,
emission stacks, sampling locations, and sites, to name only a few
examples.
Geographical Information Systems, Three Volume Set is a computer system used to capture, store, analyze and display information related to positions on the Earth's surface. It has the ability to show multiple types of information on multiple geographical locations in a single map, enabling users to assess patterns and relationships between different information points, a crucial component for multiple aspects of modern life and industry. This 3-volumes reference provides an up-to date account of this growing discipline through in-depth reviews authored by leading experts in the field. VOLUME EDITORS Thomas J. Cova The University of Utah, Salt Lake City, UT, United States Ming-Hsiang Tsou San Diego State University, San Diego, CA, United States Georg Bareth University of Cologne, Cologne, Germany Chunqiao Song University of California, Los Angeles, CA, United States Yan Song University of North Carolina at Chapel Hill, Chapel Hill, NC, United States Kai Cao National University of Singapore, Singapore Elisabete A. Silva University of Cambridge, Cambridge, United Kingdom
Interferometric synthetic aperture radar (InSAR) is a relatively new remote sensing tool that is capable of measuring ground-surface deformation with centimeter-to-subcentimeter precision at a spatial resolution of tens of meters over an area of hundreds to thousands of square kilometers. With its global coverage and all-weather imaging capability, InSAR has become an increasingly important technique for studying volcanoes in remote regions such as the Aleutian Islands. The spatial distribution of surface deformation data derived from InSAR images enables the construction of detailed mechanical models to enhance the study of magmatic processes. InSAR Imaging of Aleutian Volcanoes: * Provides a theoretical framework for InSAR observations and capabilities * Discusses state-of-the-art InSAR analysis techniques * Describes the structure, eruptive history, and magma composition of volcanoes along the entire Aleutian arc * Presents conceptual models for the magma plumbing systems of Aleutian volcanoes based on InSAR results combined with geophysical, geological and geochemical observations. * Synthesizes observations of deformation along the Aleutian arc and compares those results to other active arcs around the world. * Is illustrated throughout with high-resolution color satellite radar images
This volume aims to provide a definitive description of the various models of Mission Operations Systems (MOS) available to the Project Manager, the Operations Manager, or to the student, to aid in the understanding and design of a cost-effective mission operations system for future unmanned, remote sensing missions, either Earth-observing or planetary. The text provides an account of the Mission Operations Systems design process and of general principles of the designs themselves. Professionals designing a Mission Operations System, and students of remote sensing or other spacecraft missions who need to know how one is organized and run, should find it useful. NASA's program, the Magellan mission to Venus, is described as a detail MOS case study. The principles expressed in this book can be applied to all types of scientific remote sensing missions to effect an efficient, comprehensive and cost-effective design.
This book addresses opportunities for observation of earth surface processes using remote sensing from space. It should provide a data source for scientists studying global change. The challenges created by global environmental change demand research approaches that are worldwide in scope and interdisciplinary in application. This book is a response to the need for the interchange of ideas and experiences between researchers from those sciences studying the land surface of the earth, its form, and features, and remote sensing specialists. It is founded on the premise that attention should focus on the analysis of specific components of the earth system and on the synthesis of the findings of individual disciplines in terms of how the earth and its atmosphere function as an open system. Earth system science aims to identify how this system changes (both over human and geological timescales) and how such changes can be predicted. Reliable prediction requires scientific understanding, which in turn requires models, theories and data. Remote sensing is capable of providing such data on appropriate temporal and spatial scales.
A temporal GIS is an information system designed to describe spatial change over time. As yet, there are no temporal GISs, although the seeds exist. This book examines the conceptual, logical and physical design of a temporal GIS. It provides a broad survey of research on spatiotemporality, the philosophy of time, temporal databases and spatial data structuring. The book also describes an investigation of spatiotemporal data structuring and accessing possibilities.
Although GIS has been in existence for over 20 years, the systems have only recently matured to the point where they have become accessible to geographers, planners, environmental scientists and others as an affordable and practical tool for spatial analysis. Much of the GIS literature is scattered over the journals and technical reports of a number of disciplines. These sources are often not widely available especially to the newcomer to the field. This text was assembled to bring together what we believe is a balanced sampling of written works that cover important aspects of the basic principles involved in GIS, as well as to provide some examples of GIS applications.
This book explores the applicability of multiple remote sensors to acquire information relevant to restoration and conservation efforts in wetlands using data collected from airborne and space multispectral/hyperspectral sensors, light detection and ranging (LiDAR), Unmanned Aircraft Systems (UAS), and a hand-held spectroradiometer. This book also examines digital data processing techniques such as object-based image analysis, machine learning, texture analysis, and data fusion. After an introduction to the Everglades and to remote sensing, the book is divided into four parts based on the sensor systems used. There are chapters on vegetation mapping, biomass and water quality modeling, applications of hyperspectral data for plant stress analysis and coral reef mapping, studies of airborne LiDAR data for coastal vulnerability analysis and DEM improvement, as well as chapters that explore a fusion of multiple sensors for different datasets. Features Introduces concepts, theories, and advanced processing techniques A complete introduction of machine learning, object-based image analysis, data fusion, and ensemble analysis techniques in processing data from multiple remote sensors Explains how multiple remote sensing systems are applied in the wetland ecosystems of Florida The author had been teaching and using both systems and her research is widely recognized Multi-sensor System Applications in the Everglades Ecosystems provides a comprehensive application of remote sensing techniques in the Florida Everglades and its coastal ecosystems. It will prove an invaluable resource for the restoration and conservation of the Florida Everglades and beyond, for global wetlands in general. Any professional, scientist, engineer, or student working with remote sensing and wetland ecosystems will reap enormous benefits from this book.
Building on its heritage in planetary science, remote sensing of the Earth's at- sphere and ionosphere with occultation methods has undergone remarkable dev- opments since the rst GPS/Met 'proof of concept' mission in 1995. Signals of Global Navigation Satellite Systems (GNSS) satellites are exploited by radio occ- tation while natural signal sources are used in solar, lunar, and stellar occultations. A range of atmospheric variables is provided reaching from fundamental atmospheric parameters such as density, pressure, and temperature to water vapor, ozone, and othertracegasspecies. Theutilityforatmosphereandclimatearisesfromtheunique properties of self-calibration, high accuracy and vertical resolution, global coverage, and (if using radio signals) all-weather capability. Occultations have become a va- able data source for atmospheric physics and chemistry, operational meteorology, climate research as well as for space weather and planetary science. The 3rd International Workshop on Occultations for Probing Atmosphere and Climate (OPAC-3) was held September 17-21, 2007, in Graz, Austria. OPAC-3 aimed at providing a casual forum and stimulating atmosphere for scienti c disc- sion, co-operation initiatives, and mutual learning and support amongst members of alldifferentoccultationcommunities. Theworkshopwasattendedby40participants from 14 different countries who actively contributed to a scienti c programme of high quality and to an excellent workshop atmosphere. The programme included 6 invited keynote presentations and 16 invited pres- tations, complemented by about 20 contributed ones including 8 posters.
Provide the applications of remote sensing in all fields through varied case studies and spatial data analysis Includes soil and land degradation, micro climates, watershed management and planning Covers remote sensing applications in broad areas of agriculture, hydrology, land use, resource analysis and urban problems Discusses usage of GPS enabled smart phones and digital gadgets used for mapping and spatial analysis Explores applications of remote sensing in disaster management and planning
This is a comprehensive guide to the characteristics and use of high resolution optical images from satellite-borne sensors, concentrating on sensors designed for mapping. It considers in detail the SPOT series of satellites and sensors with a ground sample distance (GSD) of less than 15m, operational since SPOT 1 and particularly the commercial sensors launched since 1999 with GSD of less than 1m The book explains to students, anyone working in map production and scientists working in fields other than mapping, the way in which high resolution imagery is obtained and the issues which surround its collection and use. It deals progressively with the fundamentals of mapping from imagery, followed by the key features in the design of sensors and methods of data storage and transmission, including data compression. Subsequent chapters cover the sensors, calibration, sensor models and the methods of determining the orientation elements and extracting coordinates from the images. Rigorous orientation, use of rational polynomial coefficients (RPCs) and approximate methods are covered.Results from tests showing the accuracy which can be obtained, generation of digital elevations models, their accuracy and the production of orthoimages are included, as are image processing and data fusion. Finally, future missions and the issues which face further development are discussed. High Resolution Optical Satellite Imagery is written by a team of acknowledged international experts and is the only comprehensive text on the subject.
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing stateof- the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Hyperspectral remote sensing or imaging spectroscopy data has been increasingly used in studying and assessing the biophysical and biochemical properties of agricultural crops and natural vegetation. Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume III through the editors' perspective. Key Features of Volume III: Covers recent abilities to better quantify, model, and map plant biophysical, biochemical water, and structural properties. Demonstrates characteristic hyperspectral properties through plant diagnostics or throughput phenotyping of plant biophysical, biochemical, water, and structural properties. Establishes plant traits through hyperspectral imaging spectroscopy data as well as its integration with other data, such as LiDAR, using data from various platforms (ground-based, UAVs, and earth-observing satellites). Studies photosynthetic efficiency and plant health and stress through hyperspectral narrowband vegetation indices. Uses hyperspectral data to discriminate plant species and\or their types as well as their characteristics, such as growth stages. Compares studies of plant species of agriculture, forests, and other land use\land cover as established by hyperspectral narrowband data versus multispectral broadband data. Discusses complete solutions from methods to applications, inventory, and modeling considering various platform (e.g., earth-observing satellites, UAVs, handheld spectroradiometers) from where the data is gathered. Dwells on specific applications to detect and map invasive species by using hyperspectral data.
Topographic Laser Ranging and Scanning, Second Edition, provides a comprehensive discussion of topographic LiDAR principles, systems, data acquisition, and data processing techniques. This edition presents an introduction and summary of various LiDAR systems and their principles and addresses the operational principles of the different components and ranging methods of LiDAR systems. It discusses the subsequent geometric processing of LiDAR data, with particular attention to quality, accuracy, and meeting standards and addresses the theories and practices of information extraction from LiDAR data, including terrain surface generation, forest inventory, orthoimage generation, building reconstruction, and road extraction. Written by leaders in the field, this comprehensive compilation is a must-have reference book for senior undergraduate and graduate students majoring or working in diverse disciplines, such as geomatics, geodesy, natural resources, urban planning, computer vision, and computer graphics. It is also vital resource for researchers who are interested in developing new methods and need in-depth knowledge of laser scanning and data processing and other professionals may gain the same from the broad topics addressed in this book. New in the Second Edition: A comprehensive array of new laser ranging and scanning technologies. Developments in LiDAR data format and processing techniques. Regrouping of surface modeling, representations and reconstruction. Enhanced discussions on the principles and fundamentals beyond small-footprint pulsed laser systems and new application examples. Many new examples and illustrations.
In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions. Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python. This book helps you: Understand the importance of applying spatial relationships in data science Select and apply data layering of both raster and vector graphics Apply location data to leverage spatial analytics Design informative and accurate maps Automate geographic data with Python scripts Explore Python packages for additional functionality Work with atypical data types such as polygons, shape files, and projections Understand the graphical syntax of spatial data science to stimulate curiosity
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors' perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS. |
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