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  • 1
    Cham : Springer International Publishing AG
    Call number: 978-3-319-65633-5 (e-book)
    Description / Table of Contents: 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.  
    Type of Medium: 12
    Pages: 1 Online-Ressource (VIII, 332 p. 116 illus., 111 illus. in color)
    Edition: Online edition Springer eBook Collection. Physics and Astronomy
    ISBN: 9783319656335 , 9783319656328 (print)
    Series Statement: ISSI Scientific Report Series 15
    Parallel Title: Printed edition
    Language: English
    Branch Library: GFZ Library
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  • 2
    Keywords: Earth sciences ; Remote sensing ; Environmental management ; Earth Sciences ; Earth Sciences, general ; Big Data ; Remote Sensing/Photogrammetry ; Environmental Management ; Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
    Notes: 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.  
    Pages: VIII, 332 pages : 116 illustrations, 111 illustrations in color
    ISBN: 978-3-319-65632-8
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  • 3
    Keywords: Earth sciences ; Remote sensing ; Environmental management ; Earth Sciences ; Earth Sciences, general ; Big Data ; Remote Sensing/Photogrammetry ; Environmental Management ; Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
    Notes: 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.  
    Pages: VIII, 332 pages : 116 illustrations, 111 illustrations in color
    ISBN: 978-3-319-65632-8
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  • 4
    Keywords: Earth sciences ; Remote sensing ; Environmental management ; Earth Sciences ; Earth Sciences, general ; Big Data ; Remote Sensing/Photogrammetry ; Environmental Management ; Space Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics)
    Notes: 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.  
    Pages: VIII, 332 pages : 116 illustrations, 111 illustrations in color
    ISBN: 978-3-319-65632-8
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  • 5
    Publication Date: 2013-08-01
    Description: The assessment of regional climate change impacts combined with the sensitivity of landscape functions by predictive modelling of hazardous landscape processes is a new fundamental field of research. In particular, this study investigates the effects of changing weather extremes on meso-regional-scale landscape vulnerability. Climatic-exposure parameter analysis was performed on a predicted climate change scenario. The exposure to climate change was analysed on the basis of the original data of the meso-scale IPCC A1B climate scenario from the REMO and ALADIN regional models for the periods of 2021–2050 and 2071–2100, and the regional types of climate change impacts were calculated by using cluster analysis. Selected climate exposure parameters of the REMO and ALADIN models were analysed, in particular, for extreme events (days with precipitation greater than 30 mm, heat waves, dry periods, wet periods) and for daily temperature and precipitation. The landscape functions impacted by climate change are proxies for the main recent and future problematic processes in Hungary. Soil erosion caused by water, drought, soil erosion caused by wind, mass movement and flash floods were analysed for the time periods of 1961–1990, 2021–2050 and 2071–2100. Based on the sensitivity thresholds for the impact assessments, the landscape functional sensitivity indicators were interpreted, and an integrative summary of the five indicators was made, differentiating the regions facing only a few or multiple sensitivities. In Central Hungary, the increasing exposure and sensitivity to droughts will be a serious problem when following the REMO scenario. In several regions, most indicators will change the sensitivity threshold from a tolerable risk to an increased or very high risk. ©2012 Springer-Verlag
    Print ISSN: 1436-3798
    Electronic ISSN: 1436-378X
    Topics: Biology , Energy, Environment Protection, Nuclear Power Engineering
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  • 6
    Publication Date: 2013-09-01
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 7
    Publication Date: 2015-06-09
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 8
    Publication Date: 2013-09-01
    Description: Tsunamis are among the most destructive and lethal of coastal hazards. These are time-specific events, and despite directly affecting a narrow strip of coastline, a single occurrence can have devastating effects and cause massive loss of life, especially in urbanized coastal areas. In this work, in order to consider the time dependence of population exposure to tsunami threat, the variation of spatio-temporal population distribution in the daily cycle is mapped and analyzed in the Lisbon Metropolitan Area. High-resolution daytime and nighttime population distribution maps are developed using ‘intelligent dasymetric mapping,’ that is, applying areal interpolation to combine best-available census data and statistics with land use and land cover data. Workplace information and mobility statistics are considered for mapping daytime distribution. In combination with a tsunami hazard map, information on infrastructure, land use and terrain slope, the modeled population distribution is used to assess people’s evacuation speed, applying a geospatial evacuation modeling approach to the city of Lisbon. The detailed dynamic population exposure assessment allows producing both daytime and nighttime evacuation time maps, which provide valuable input for evacuation planning and management. Results show that a significant amount of population is at risk, and its numbers increase dramatically from nighttime to daytime, especially in the zones of high tsunami flooding susceptibility. Also, full evacuation can be problematic in the daytime period, even if initiated immediately after a major tsunami-triggering earthquake. The presented approach greatly improves tsunami risk assessment and can benefit all phases of the disaster management process. ©2013 Springer Science+Business Media Dordrecht
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 9
    Publication Date: 2013-09-01
    Description: For assessing the social dimension of vulnerability, population exposure mapping is usually considered the essential starting point. Integration of social structure then further differentiates situation-specific vulnerability patterns on a local scale. Census data available in heterogeneous spatial reference units are still considered the standard information input for assessing potentially affected people, for example, in case of an emergency. There is a strong demand for population data in homogeneous spatial units that are independent from administrative areas. Raster representations meet this demand but are not yet available for all European countries. In this paper, we present an approach of spatial disaggregation of population data for a European transect referring to current population statistics and anticipated future prospects. Recently published data providing the degree of soil sealing are applied as basic proxy for population density in the spatial disaggregation model. In order to assess future patterns of climate change-related vulnerability, results of a European regional climate model are considered for projecting the situation in the 2030s. “Heat wave frequency” is accounted for as climate variable featuring conditions regarded as especially strenuous for elderly or physically weak persons. Integrated analysis of the population and climate prospects enables identification of hot spots in the European transect examined, that is, regions of particularly demanding projected climatic patterns as well as high population density and case-specific vulnerable structure (elderly people). Integrated and consistent spatial analyses on European scale are essential for decision support in the context of climate change impact mitigation as well as for risk communication and future safety and security considerations. ©2012 Springer Science+Business Media B.V.
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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  • 10
    Publication Date: 2013-08-01
    Description: In the context of disaster risk management and in particular for improving preparedness and mitigation of potential impacts, information on socioeconomic characteristics including aspects of situation-specific human exposure and vulnerability is considered vital. This paper provides an overview on available multi-level geospatial information and modeling approaches from global to local scales that could serve as inventory for people involved in disaster-related areas. Concepts and applications related to the human exposure and social vulnerability domains are addressed by illustrating the varying dimensions and contextual implications. Datasets and methods are highlighted that can be applied to assess earthquake-related population exposure, ranging from global and continental-scale population grids (with a focus on recent developments for Europe) to high-resolution functional urban system models and space–time variation aspects. In a further step, the paper elaborates on the integration of social structure on regional scale and the development of aggregative social and economic vulnerability indicators which would eventually enable the differentiation of situation-specific risk patterns. The presented studies cover social vulnerability mapping for selected US federal states in the New Madrid seismic zone as well as the advancement of social vulnerability analysis through integration of additional economic features in the index construction by means of a case study for Turkey’s provinces. ©2012 Springer Science+Business Media B.V.
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
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