Geospatial Analyses of Earth Observation (EO) Data PDF Download
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Author: Antonio Pepe
Publisher:
ISBN: 178984584X
Category :
Languages : en
Pages : 138
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Book Description
Author: Antonio Pepe
Publisher:
ISBN: 178984584X
Category :
Languages : en
Pages : 138
Get Book Here
Book Description
Author: Deren Li
Publisher: Springer Science & Business Media
ISBN: 1441900500
Category : Science
Languages : en
Pages : 555
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Book Description
Earth Observation interacts with space, remote sensing, communication, and information technologies, and plays an increasingly significant role in Earth related scientific studies, resource management, homeland security, topographic mapping, and development of a healthy, sustainable environment and community. Geospatial Technology for Earth Observation provides an in-depth and broad collection of recent progress in Earth observation. Contributed by leading experts in this field, the book covers satellite, airborne and ground remote sensing systems and system integration, sensor orientation, remote sensing physics, image classification and analysis, information extraction, geospatial service, and various application topics, including cadastral mapping, land use change evaluation, water environment monitoring, flood mapping, and decision making support. Geospatial Technology for Earth Observation serves as a valuable training source for researchers, developers, and practitioners in geospatial science and technology industry. It is also suitable as a reference book for upper level college students and graduate students in geospatial technology, geosciences, resource management, and informatics.
Author: Gregory Giuliani
Publisher: MDPI
ISBN: 3039280929
Category : Science
Languages : en
Pages : 302
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Book Description
Satellite Earth observation (EO) data have already exceeded the petabyte scale and are increasingly freely and openly available from different data providers. This poses a number of issues in terms of volume (e.g., data volumes have increased 10× in the last 5 years); velocity (e.g., Sentinel-2 is capturing a new image of any given place every 5 days); and variety (e.g., different types of sensors, spatial/spectral resolutions). Traditional approaches to the acquisition, management, distribution, and analysis of EO data have limitations (e.g., data size, heterogeneity, and complexity) that impede their true information potential to be realized. Addressing these big data challenges requires a change of paradigm and a move away from local processing and data distribution methods to lower the barriers caused by data size and related complications in data management. To tackle these issues, EO data cubes (EODC) are a new paradigm revolutionizing the way users can store, organize, manage, and analyze EO data. This Special Issue is consequently aiming to cover the most recent advances in EODC developments and implementations to broaden the use of EO data to larger communities of users, support decision-makers with timely and actionable information converted into meaningful geophysical variables, and ultimately unlock the information power of EO data.
Author: Daniel McInerney
Publisher: Springer
ISBN: 9783319346250
Category : Science
Languages : en
Pages : 0
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Book Description
This book focuses on the use of open source software for geospatial analysis. It demonstrates the effectiveness of the command line interface for handling both vector, raster and 3D geospatial data. Appropriate open-source tools for data processing are clearly explained and discusses how they can be used to solve everyday tasks. A series of fully worked case studies are presented including vector spatial analysis, remote sensing data analysis, landcover classification and LiDAR processing. A hands-on introduction to the application programming interface (API) of GDAL/OGR in Python/C++ is provided for readers who want to extend existing tools and/or develop their own software.
Author: Jonas Eberle
Publisher:
ISBN:
Category :
Languages : de
Pages : 0
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Book Description
The increasing amount of Earth observation (EO) data requires a tremendous change, in order to property handle the number of observations and storage size thereof. Due to open data strategies and the increasing size of data archives, a new market has been developed to provide analysis and application-ready data, services, and platforms. It is not only scientists and geospatial processing specialists who work with EO data; stakeholders, thematic experts, and software developers do too. There is thus a great demand for improving the discovery, access, and analysis of EO data in line with new possibilities of web-based infrastructures. With the aim of bridging the gap between users and EO data archives, various topics have been researched: 1) user requirements and their relation to web services and output formats; 2) technical requirements for the discovery and access of multi-source EO time-series data, and 3) management of EO time-series data focusing on application-ready data. Web services for EO data discovery and access, time-series data processing, and EO platforms have been reviewed and related to the requirements of users. The diversity of data providers and web services requires specific knowledge of systems and specifications. Although service specifications for the discovery of EO data exist, improvements are still necessary to meet the requirements of different user personas. For the processing of EO time-series data, various data formats and processing steps need to be handled. Still, there remains a gap between EO time-series data access and analysis tools, which needs to be addressed to simplify work with such data. Within this thesis, web services for the discovery, access, and analysis of EO time-series data have been described and evaluated based on different user requirements. Standardized web services specifications, output and data formats are proposed, introduced and described to meet the needs of the different user personas.
Author: Jukka M. Krisp
Publisher: Springer Science & Business Media
ISBN: 3642327141
Category : Science
Languages : en
Pages : 303
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Book Description
This book provides a collection of selected articles that have been submitted to the Earth Observation and Global Changes (EOGC2011) Conference. All articles have been carefully reviewed by an international board of top-level experts. The book covers a wide variety of topics including Physical Geodesy, Photogrammetry & Remote Sensing, High-Resolution and Fast-Revisiting Remote Sensing Satellite Systems, Global Change & Change Detection, Spatial Modelling, GIS & Geovisualization. The articles document concrete results of current studies related to Earth Sciences. The book is intended for researchers and experts working in the area of Spatial Data Analysis, Environmental Monitoring/Analysis, Global Change Monitoring and related fields.
Author: Deren Li
Publisher: Springer
ISBN: 9781441901019
Category : Science
Languages : en
Pages : 556
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Book Description
Earth Observation interacts with space, remote sensing, communication, and information technologies, and plays an increasingly significant role in Earth related scientific studies, resource management, homeland security, topographic mapping, and development of a healthy, sustainable environment and community. Geospatial Technology for Earth Observation provides an in-depth and broad collection of recent progress in Earth observation. Contributed by leading experts in this field, the book covers satellite, airborne and ground remote sensing systems and system integration, sensor orientation, remote sensing physics, image classification and analysis, information extraction, geospatial service, and various application topics, including cadastral mapping, land use change evaluation, water environment monitoring, flood mapping, and decision making support. Geospatial Technology for Earth Observation serves as a valuable training source for researchers, developers, and practitioners in geospatial science and technology industry. It is also suitable as a reference book for upper level college students and graduate students in geospatial technology, geosciences, resource management, and informatics.
Author: Pierre-Philippe Mathieu
Publisher: Springer
ISBN: 3319656333
Category : Science
Languages : en
Pages : 328
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Book Description
This book is published open access under a CC BY 4.0 license. Over the past decades, rapid developments in digital and sensing technologies, such as the Cloud, Web and Internet of Things, have dramatically changed the way we live and work. The digital transformation is revolutionizing our ability to monitor our planet and transforming the way we access, process and exploit Earth Observation data from satellites. This book reviews these megatrends and their implications for the Earth Observation community as well as the wider data economy. It provides insight into new paradigms of Open Science and Innovation applied to space data, which are characterized by openness, access to large volume of complex data, wide availability of new community tools, new techniques for big data analytics such as Artificial Intelligence, unprecedented level of computing power, and new types of collaboration among researchers, innovators, entrepreneurs and citizen scientists. In addition, this book aims to provide readers with some reflections on the future of Earth Observation, highlighting through a series of use cases not just the new opportunities created by the New Space revolution, but also the new challenges that must be addressed in order to make the most of the large volume of complex and diverse data delivered by the new generation of satellites.
Author: Martin Werner
Publisher: Springer Nature
ISBN: 3030554627
Category : Computers
Languages : en
Pages : 641
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Book Description
This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.
Author: Zhe Jiang
Publisher: Springer
ISBN: 3319601954
Category : Computers
Languages : en
Pages : 138
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Book Description
Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book. This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
