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  • UdK Berlin
  • Filmuniversität Babelsberg
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  • 1
    UID:
    almahu_9949616271002882
    Format: 1 online resource (1210 pages)
    Edition: 1st ed.
    ISBN: 9783031265884
    Note: Intro -- Foreword -- Introduction -- Fundamentals -- Part I: Programming and Remote Sensing Basics -- Part II: Interpreting Images -- Part III: Advanced Image Processing -- Part IV: Interpreting Image Series -- Part V: Vectors and Tables -- Part VI: Advanced Topics -- Applications -- Part VII: Human Applications -- Part VIII: Aquatic and Hydrological Applications -- Part IX: Terrestrial Applications -- Uses of This Book -- We Want Your Feedback -- Acknowledgements -- Other Sources -- Contents -- Part IProgramming and Remote Sensing Basics -- 1 JavaScript and the Earth Engine API -- 1.1 Introduction to Theory -- 1.2 Practicum -- 1.2.1 Section 1: Getting Started in the Code Editor -- 1.2.2 Section 2: JavaScript Basics -- 1.2.3 Section 3: Earth Engine API Basics -- 1.3 Synthesis -- 1.4 Conclusion -- 2 Exploring Images -- 2.1 Practicum -- 2.1.1 Section 1: Accessing an Image -- 2.1.2 Section 2: Visualizing an Image -- 2.1.3 Section 3: True-Color Composites -- 2.1.4 Section 4: False-Color Composites -- 2.1.5 Section 5: Additive Color System -- 2.1.6 Section 6: Attributes of Locations -- 2.1.7 Section 7: Abstract RGB Composites -- 2.2 Synthesis -- 2.3 Conclusion -- 3 Survey of Raster Datasets -- 3.1 Introduction to Theory -- 3.2 Practicum -- 3.2.1 Section 1: Image Collections: An Organized Set of Images -- 3.2.2 Section 2: Collections of Single Images -- 3.2.3 Section 3: Pre-made Composites -- 3.2.4 Section 4: Other Satellite Products -- 3.2.5 Section 5: Pre-classified Land Use and Land Cover -- 3.2.6 Section 6: Other Datasets -- 3.3 Synthesis -- 3.4 Conclusion -- References -- 4 The Remote Sensing Vocabulary -- 4.1 Introduction to Theory -- 4.2 Practicum -- 4.2.1 Section 1: Searching for and Viewing Image Collection Information -- 4.2.2 Section 2: Spatial Resolution -- 4.2.3 Section 3: Temporal Resolution -- 4.2.4 Section 4: Spectral Resolution. , 4.2.5 Section 5: Per-Pixel Quality -- 4.2.6 Section 6: Metadata -- 4.3 Synthesis -- 4.4 Conclusion -- Reference -- Part IIInterpreting Images -- 5 Image Manipulation: Bands, Arithmetic, Thresholds, and Masks -- 5.1 Introduction to Theory -- 5.2 Practicum -- 5.2.1 Section 1: Band Arithmetic in Earth Engine -- 5.2.2 Section 2: Thresholding, Masking, and Remapping Images -- 5.3 Synthesis -- 5.4 Conclusion -- References -- 6 Interpreting an Image: Classification -- 6.1 Introduction to Theory -- 6.2 Practicum -- 6.2.1 Section 1: Supervised Classification -- 6.2.2 Section 2: Unsupervised Classification -- 6.3 Synthesis -- 6.4 Conclusion -- References -- 7 Accuracy Assessment: Quantifying Classification Quality -- 7.1 Introduction to Theory -- 7.2 Practicum -- 7.2.1 Quantifying Classification Accuracy Through a Confusion Matrix -- 7.2.2 Hyperparameter Tuning -- 7.2.3 Spatial Autocorrelation -- 7.3 Synthesis -- 7.4 Conclusion -- References -- Part IIIAdvanced Image Processing -- 8 Interpreting an Image: Regression -- 8.1 Introduction to Theory -- 8.2 Practicum -- 8.2.1 Reducers -- 8.3 Section 1: Linear Fit -- 8.3.1 Section 2: Linear Regression -- 8.3.2 Section 3: Nonlinear Regression -- 8.3.3 Section 4: Assessing Regression Performance Through RMSE -- 8.4 Synthesis -- 8.5 Conclusion -- References -- 9 Advanced Pixel-Based Image Transformations -- 9.1 Introduction to Theory -- 9.2 Practicum -- 9.2.1 Section 1: Manipulating Images with Expressions -- 9.2.2 Section 2: Manipulating Images with Matrix Algebra -- 9.2.3 Section 3: Spectral Unmixing -- 9.2.4 Section 4: The Hue, Saturation, Value Transform -- 9.3 Synthesis -- 9.4 Conclusion -- References -- 10 Neighborhood-Based Image Transformation -- 10.1 Introduction to Theory -- 10.2 Practicum -- 10.2.1 Section 1: Linear Convolution -- 10.2.2 Section 2: Nonlinear Convolution. , 10.2.3 Section 3: Morphological Processing -- 10.2.4 Section 4: Texture -- 10.3 Synthesis -- 10.4 Conclusion -- References -- 11 Object-Based Image Analysis -- 11.1 Introduction to Theory -- 11.2 Practicum -- 11.2.1 Section 1: Unsupervised Classification -- 11.2.2 Section 2: Detecting Objects in Imagery with the SNIC Algorithm -- 11.2.3 Section 3: Object-Based Unsupervised Classification -- 11.2.4 Section 4: Classifications with More or Less Categorical Detail -- 11.2.5 Section 5: Effects of SNIC Parameters -- 11.3 Synthesis -- 11.4 Conclusion -- References -- Part IVInterpreting Image Series -- 12 Filter, Map, Reduce -- 12.1 Introduction to Theory -- 12.2 Practicum -- 12.2.1 Section 1: Filtering Image Collections in Earth Engine -- 12.2.2 Section 2: Mapping over Image Collections in Earth Engine -- 12.2.3 Section 3: Reducing an Image Collection -- 12.3 Synthesis -- 12.4 Conclusion -- 13 Exploring Image Collections -- 13.1 Practicum -- 13.1.1 Section 1: Filtering and Inspecting an Image Collection -- 13.1.2 Section 2: How Many Images Are There, Everywhere on Earth? -- 13.1.3 Section 3: Reducing Image Collections to Understand Band Values -- 13.1.4 Section 4: Compute Multiple Percentile Images for an Image Collection -- 13.2 Synthesis -- 13.3 Conclusion -- Reference -- 14 Aggregating Images for Time Series -- 14.1 Introduction to Theory -- 14.2 Practicum -- 14.2.1 Section 1: Filtering an Image Collection -- 14.2.2 Section 2: Working with Dates -- 14.2.3 Section 3: Aggregating Images -- 14.2.4 Section 4: Plotting Time Series -- 14.3 Synthesis -- 14.4 Conclusion -- References -- 15 Clouds and Image Compositing -- 15.1 Introduction to Theory -- 15.2 Practicum -- 15.2.1 Section 1: Cloud Filter and Cloud Mask -- 15.2.2 Section 2: Incorporating Data from Other Satellites -- 15.2.3 Section 3: Best-Available-Pixel Compositing Earth Engine Application. , 15.3 Synthesis -- 15.4 Conclusion -- References -- 16 Change Detection -- 16.1 Introduction to Theory -- 16.2 Practicum -- 16.2.1 Section 1: Preparing Imagery -- 16.2.2 Section 2: Creating False-Color Composites -- 16.2.3 Section 3: Calculating NBR -- 16.2.4 Section 4: Single Date Transformation -- 16.2.5 Section 5: Classifying Change -- 16.3 Synthesis -- 16.4 Conclusion -- References -- 17 Interpreting Annual Time Series with LandTrendr -- 17.1 Introduction to Theory -- 17.2 Practicum -- 17.2.1 Section 1: Pixel Time Series -- 17.2.2 Section 2: Translating Pixels to Maps -- 17.3 Synthesis -- 17.4 Conclusion -- References -- 18 Fitting Functions to Time Series -- 18.1 Introduction to Theory -- 18.2 Practicum -- 18.2.1 Section 1: Multi-temporal Data in Earth Engine -- 18.2.2 Section 2: Data Preparation and Preprocessing -- 18.2.3 Section 3: Estimating Linear Trend Over Time -- 18.2.4 Section 4: Estimating Seasonality with a Harmonic Model -- 18.2.5 Section 5: An Application of Curve Fitting -- 18.2.6 Section 6: Higher-Order Harmonic Models -- 18.3 Synthesis -- 18.4 Conclusion -- References -- 19 Interpreting Time Series with CCDC -- 19.1 Introduction to Theory -- 19.2 Practicum -- 19.2.1 Section 1: Understanding Temporal Segmentation with CCDC -- 19.2.2 Section 2: Running CCDC -- 19.2.3 Section 3: Extracting Break Information -- 19.2.4 Section 4: Extracting Coefficients Manually -- 19.2.5 Section 5: Extracting Coefficients Using External Functions -- 19.3 Synthesis -- 19.4 Conclusion -- References -- 20 Data Fusion: Merging Classification Streams -- 20.1 Introduction to Theory -- 20.2 Practicum -- 20.2.1 Section 1: Imagery and Classifications of the Roosevelt River -- 20.2.2 Section 2: Basics of the BULC Interface -- 20.2.3 Section 3: Detailed LULC Inspection with BULC -- 20.2.4 Section 4: Change Detection with BULC-D. , 20.2.5 Section 5: Change Detection with BULC and Dynamic World -- 20.3 Synthesis -- 20.4 Conclusion -- References -- 21 Exploring Lagged Effects in Time Series -- 21.1 Introduction to Theory -- 21.2 Practicum -- 21.2.1 Section 1: Autocovariance and Autocorrelation -- 21.2.2 Section 2: Cross-Covariance and Cross-Correlation -- 21.2.3 Section 3: Auto-Regressive Models -- 21.3 Synthesis -- 21.4 Conclusion -- References -- Part VVectors and Tables -- 22 Exploring Vectors -- 22.1 Introduction to Theory -- 22.2 Practicum -- 22.2.1 Section 1: Using Geometry Tools to Create Features in Earth Engine -- 22.2.2 Section 2: Loading Existing Features and Feature Collections in Earth Engine -- 22.2.3 Section 3: Importing Features into Earth Engine -- 22.2.4 Section 4: Filtering Feature Collections by Attributes -- 22.2.5 Section 5: Reducing Images Using Feature Geometry -- 22.2.6 Section 6: Identifying the Block in the Neighborhood Surrounding USF with the Highest NDVI -- 22.3 Synthesis -- 22.4 Conclusion -- 23 Raster/Vector Conversions -- 23.1 Introduction to Theory -- 23.2 Practicum -- 23.2.1 Section 1: Raster to Vector Conversion -- 23.2.2 Section 2: Vector-To-Raster Conversion -- 23.3 Synthesis -- 23.4 Conclusion -- 24 Zonal Statistics -- 24.1 Introduction to Theory -- 24.2 Practicum -- 24.2.1 Section 1: Functions -- 24.2.2 Section 2: Point Collection Creation -- 24.2.3 Section 3: Neighborhood Statistic Examples -- 24.2.4 Section 4: Additional Notes -- 24.3 Synthesis -- 24.4 Conclusion -- References -- 25 Advanced Vector Operations -- 25.1 Practicum -- 25.1.1 Section 1: Visualizing Feature Collections -- 25.1.2 Section 2: Joins with Feature Collections -- 25.2 Synthesis -- 25.3 Conclusion -- 26 GEEDiT-Digitizing from Satellite Imagery -- 26.1 Introduction to Theory -- 26.2 Practicum. , 26.2.1 Section 1: Loading GEEDiT and Selecting Imagery Options and a Location.
    Additional Edition: Print version: Cardille, Jeffrey A. Cloud-Based Remote Sensing with Google Earth Engine Cham : Springer International Publishing AG,c2023 ISBN 9783031265877
    Language: English
    Keywords: Electronic books. ; Electronic books.
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  • 2
    UID:
    almahu_9949707963102882
    Format: 1 online resource (147 pages)
    Edition: 1st ed.
    ISBN: 9783031445460
    Series Statement: The European Union in International Affairs Series
    Additional Edition: Print version: Rieker, Pernille European Actorness in a Shifting Geopolitical Order Cham : Palgrave Macmillan,c2024 ISBN 9783031445453
    Language: English
    Keywords: Electronic books. ; Electronic books.
    URL: Volltext  (kostenfrei)
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  • 3
    UID:
    almahu_9949728666702882
    Format: 1 online resource (195 pages)
    Edition: 1st ed.
    ISBN: 9783031493294
    Series Statement: United Nations University Series on Regionalism Series ; v.27
    Additional Edition: Print version: Ribeiro Hoffmann, Andrea Climate Change in Regional Perspective Cham : Springer International Publishing AG,c2024 ISBN 9783031493287
    Language: English
    Keywords: Electronic books. ; Electronic books. ; Aufsatzsammlung
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  • 4
    UID:
    almahu_9949602166002882
    Format: 1 online resource (181 pages)
    Edition: 1st ed.
    ISBN: 9783030104276
    Note: Intro -- Preface -- Why This Book? -- The Goal of This Book -- What's in This Book? -- Acknowledgments -- Contents -- Nomenclature -- List of Figures -- List of Tables -- Executive Summary -- 1 eIoT as a Solution to Energy-Management Change Drivers -- 1.1 Energy-Management Change Drivers -- 1.1.1 Growing Demand for Electricity -- 1.1.2 The Emergence of Renewable Energy Resources -- 1.1.3 The Emergence of Electrified Transportation -- 1.1.4 Deregulation of Electric Power Markets -- 1.1.5 Innovations in Smart Grid Technology -- 1.2 The Need for a Technical Solution -- 1.3 eIoT as an Energy-Management Solution -- 1.4 Scope and Perspective -- 1.5 Book Outline -- 2 eIoT Activates the Grid Periphery -- 2.1 Change Drivers Will Transform Energy Management at the Grid Periphery -- 2.2 The Challenge of Activating the Grid Periphery -- 2.3 Deploying eIoT as a Scalable Energy Management Solution -- 3 The Development of IoT Within Energy Infrastructure -- 3.1 Network-Enabled Physical Devices: Sensors and Actuators -- 3.1.1 Network-Enabled Physical Devices: Overview -- 3.1.2 Sensing and Actuation of Primary Variables in the Transmission System -- 3.1.2.1 Network-Enabled Sensors: SCADA and PMUs -- 3.1.2.2 Network-Enabled Actuators: AGC, AVR, and FACTS -- 3.1.3 Sensing and Actuation of Supply Side SecondaryVariables -- 3.1.3.1 Networked-Enabled Sensors: Wind, Solar, and Natural Gas Resources -- 3.1.3.2 Networked-Enabled Actuators: Wind and Solar Resources -- 3.1.4 Sensing and Actuation of Primary Variables in the Distribution System -- 3.1.4.1 Network-Enabled Sensors: The Emergence of the Smart Meter -- 3.1.4.2 Network-Enabled Actuators: Distribution Automation -- 3.1.5 Sensing and Actuation of Demand-Side SecondaryVariables -- 3.1.5.1 Energy Monitors with Embedded Data Analytics -- 3.1.5.2 Network-Enabled Smart Switches, Outlets, and Lights. , 3.1.5.3 Network-Enabled Heating and Cooling Appliances -- 3.1.5.4 The Electrification Potential of eIoT -- 3.1.5.5 Net-Zero Homes: Electrification of Residential Energy Consumption -- 3.1.5.6 Net-Zero Industry: Electrification of Industrial Energy Consumption -- 3.1.5.7 Connected, Automated, and Electrified Multi-Modal Transportation -- 3.1.6 Network-Enabled Physical Devices: Conclusion -- 3.2 Communication Networks -- 3.2.1 Overview -- 3.2.2 Grid Operator and Utility Networks -- 3.2.2.1 Wired Communications: Power-Line Carriers and Fiber Optics -- 3.2.2.2 SCADA Networks and Wide-Area Monitoring Systems -- 3.2.2.3 LPWAN Commercial Wireless IoT Technologies -- 3.2.2.4 Wireless Smart Utility Network -- 3.2.2.5 eIoT Perspectives on Grid Operator and Utility Networks -- 3.2.3 Commercial Telecommunication Networks -- 3.2.3.1 Cellular Data Networks: 2.5G-GPRS, 3G-GSM, 4G, and LTE -- 3.2.3.2 WiMAX Networks -- 3.2.3.3 eIoT Perspectives on Commercial Telecommunication Networks -- 3.2.4 Local Area Networks -- 3.2.4.1 Wired Ethernet -- 3.2.4.2 WiFi Networks -- 3.2.4.3 Z-Wave Networks -- 3.2.4.4 ZigBee Networks -- 3.2.4.5 Bluetooth Networks -- 3.2.4.6 Industrial Networks -- 3.2.4.7 Perspectives on Local Area Networks -- 3.2.5 IoT Messaging Protocols -- 3.2.5.1 Data Distribution Service (DDS) -- 3.2.5.2 Message Queue Telemetry Transport (MQTT) -- 3.2.5.3 Constrained Application Protocol (CoAP) -- 3.2.5.4 eXtensible Messaging and Presence Protocol (XMPP) -- 3.2.5.5 Advanced Message Queuing Protocol (AMQP) -- 3.3 Distributed Control and Decision Making -- 3.4 Architectures and Standards -- 3.5 Socio-Technical Implications of eIoT -- 3.5.1 eIoT Privacy -- 3.5.2 eIoT Cybersecurity -- 4 Transactive Energy Applications of eIoT -- 4.1 Transactive Energy -- 4.2 Potential eIoT Energy-Management Use Cases -- 4.2.1 An eIoT Transactive Energy Aggregation Use Case. , 4.2.2 An eIoT Economic Demand Response in Wholesale Electricity Markets Use Case -- 4.3 Applications for Utilities and Distribution System Operators -- 4.4 Customer Applications -- 4.4.1 Industrial Applications -- 4.4.2 Commercial Applications -- 4.4.3 Residential Applications -- 5 eIoT Transforms the Future Electric Grid -- 5.1 Conclusions -- 5.1.1 eIoT Will Become Ubiquitous -- 5.1.2 eIoT Will Enable New Automated Energy-Management Platforms -- 5.1.3 eIoT Will Enable Distributed Techno-Economic Decision Making -- 5.2 Challenges and Opportunities -- 5.2.1 The Convergence of Cyber, Physical, and Economic Performance -- 5.2.2 Re-envisioning the Strategic Business Model for the Utility of the Future -- References -- Index.
    Additional Edition: Print version: Muhanji, Steffi O. EIoT Cham : Springer International Publishing AG,c2019 ISBN 9783030104269
    Language: English
    Subjects: Engineering
    RVK:
    Keywords: Electronic books.
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  • 5
    Online Resource
    Online Resource
    Oakland, California : University of California Press
    UID:
    b3kat_BV046170685
    Format: 1 Online-Ressource
    ISBN: 9780520974135
    Note: Erscheint als Open Access bei De Gruyter
    Additional Edition: Erscheint auch als Druck-Ausgabe, paperback ISBN 978-0-520-31608-9
    Language: English
    Keywords: Japan ; Haushalt ; Familie ; Sozialgeschichte 1603-1868 ; Konferenzschrift ; Electronic books. ; Electronic books. ; History.
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    URL: JSTOR
    URL: Cover
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  • 6
    Online Resource
    Online Resource
    Warsaw ; Berlin : De Gruyter Open
    UID:
    b3kat_BV042787345
    Format: X, 177 Seiten
    ISBN: 9783110450569
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-11-045057-6 10.1515/9783110450576
    Language: English
    Subjects: Comparative Studies. Non-European Languages/Literatures
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  • 7
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  • 8
    UID:
    almahu_9949517320402882
    Format: 1 online resource (181 pages)
    ISBN: 9781000515244
    Series Statement: Routledge Focus on Environment and Sustainability Series
    Additional Edition: Print version: Castellanos, Paige Gender, Food and COVID-19 Milton : Taylor & Francis Group,c2021 ISBN 9781032055985
    Language: English
    Keywords: Electronic books. ; Electronic books. ; Electronic books
    URL: FULL  ((OIS Credentials Required))
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  • 9
    UID:
    almahu_9949602156302882
    Format: 1 online resource (408 pages)
    Edition: 1st ed.
    ISBN: 9783030052522
    Note: Intro -- Preface -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 The Need for Considering Uncertainty in Decisionmaking -- 1.2 A Framework for Decision Support -- 1.3 Dealing with Uncertainty in Decisionmaking -- 1.4 Decisionmaking Under Deep Uncertainty -- 1.5 Generic Elements of DMDU Approaches-A Framework -- 1.6 An Introduction to the DMDU Tools and Approaches -- 1.7 Structure of the Book -- References -- DMDU Approaches -- 2 Robust Decision Making (RDM) -- 2.1 Introduction -- 2.2 RDM Foundations -- 2.3 RDM Process -- 2.4 Tools -- 2.5 Example: Carrots and Sticks for New Technology -- 2.5.1 Frame the Analysis -- 2.5.2 Perform Exploratory Uncertainty Analysis -- 2.5.3 Choose Initial Actions and Contingent Actions -- 2.5.4 Iterate and Re-Examine (RDM Steps 2, 3, and 5) -- 2.6 Recent Advances and Future Challenges -- References -- 3 Dynamic Adaptive Planning (DAP) -- 3.1 Introduction -- 3.2 The DAP Approach -- 3.3 A DAP Illustration: Strategic Planning for Schiphol Airport -- 3.4 Implementation and Adaptation -- 3.5 Conclusions -- References -- 4 Dynamic Adaptive Policy Pathways (DAPP) -- 4.1 Introduction -- 4.2 The DAPP Approach -- 4.3 A DAPP Illustration: Navigation along the Waas River -- 4.4 Under What Conditions Is This Approach Useful? -- 4.5 Recent Advances -- 4.6 Links with Other DMDU Approaches -- 4.7 Future Challenges -- References -- 5 Info-Gap Decision Theory (IG) -- 5.1 Info-Gap Theory: A First Look -- 5.2 IG Robustness: Methodological Outline -- 5.2.1 Three Components of IG Robust Satisficing -- 5.2.2 IG Robustness -- 5.2.3 Prioritization of Competing Decisions -- 5.2.4 How to Evaluate Robustness: Qualitative or Quantitative? -- 5.3 IG Robustness: A Qualitative Example -- 5.3.1 Five Conceptual Proxies for Robustness -- 5.3.2 Simple Qualitative Example: Nuclear Weapon Safety. , 5.4 IG Robustness and Opportuneness: A Quantitative Example -- 5.4.1 IG Robustness -- 5.4.2 Discussion of the Robustness Results -- 5.4.3 IG Opportuneness -- 5.4.4 Discussion of Opportuneness Results -- 5.4.5 An Innovation Dilemma -- 5.4.6 Functional Uncertainty -- 5.5 Conclusion and Future Challenges -- References -- 6 Engineering Options Analysis (EOA) -- 6.1 Introduction -- 6.2 Methodology of Engineering Options Analysis -- 6.2.1 Setting the Scene -- 6.2.2 Definition of an Option -- 6.2.3 Main Steps of Analysis -- 6.2.4 Details of Each Step -- 6.3 A Simple Example: A Parking Garage -- 6.4 Contrasting Engineering Options Analysis with Real Options Analysis -- 6.4.1 Different Professional Contexts -- 6.4.2 Some Specific Differences -- 6.5 Contrasting Engineering Options Analysis with Other Approaches in This Book -- 6.5.1 Engineering Options Analysis as a Planning Approach -- 6.5.2 Engineering Options Analysis as a Computational Decision-Support Tool -- 6.6 Conclusions -- References -- DMDU Applications -- 7 Robust Decision Making (RDM): Application to Water Planning and Climate Policy -- 7.1 Long-Term Planning for Water Resources and Global Climate Technology Transfer -- 7.2 Review of Robust Decision Making -- 7.2.1 Summary of Robust Decision Making -- 7.3 Case Study 1: Using RDM to Support Long-Term Water Resources Planning for the Colorado River Basin -- 7.3.1 Decision Framing for Colorado River Basin Analyses -- 7.3.2 Vulnerabilities of Current Colorado River Basin Management -- 7.3.3 Design and Simulation of Adaptive Strategies -- 7.3.4 Evaluating Regret of Strategies Across Futures -- 7.3.5 Updating Beliefs About the Future to Guide Adaptation -- 7.3.6 Robust Adaptive Strategies, and Implementation Pathways -- 7.3.7 Need for Transformative Solutions -- 7.4 Case Study 2: Using RDM to Develop Climate Mitigation Technology Diffusion Policies. , 7.4.1 Decision Framing for Climate Technology Policy Analysis -- 7.4.2 Modeling International Technological Change -- 7.4.3 Evaluating Policies Across a Wide Range of Plausible Futures -- 7.4.4 Key Vulnerabilities of Climate Technology Policies -- 7.4.5 Developing a Robust Adaptive Climate Technology Policy -- 7.5 Reflections -- References -- 8 Dynamic Adaptive Planning (DAP): The Case of Intelligent Speed Adaptation -- 8.1 Introduction to the Approach -- 8.2 Introduction to the Case -- 8.3 Reason for Choosing the DAP Approach -- 8.4 Methods for Applying DAP -- 8.5 Setting up a DAP Workshop on ISA Implementation -- 8.6 Results of the DAP-ISA Workshop -- 8.7 Evaluation of the DAP Approach -- 8.8 Lessons Learned About the Process of Developing Dynamic Adaptive Plans -- 8.9 Conclusions -- References -- 9 Dynamic Adaptive Policy Pathways (DAPP): From Theory to Practice -- 9.1 Introduction to the Case -- 9.2 Reason for Choosing DAPP -- 9.3 Setup of Approach for Case Study in Practice -- 9.4 Applying DAPP in Practice -- 9.5 Results of Applying the Approach -- 9.6 Reflections (Lessons Learned) for Practice and Theory -- References -- 10 Info-Gap (IG): Robust Design of a Mechanical Latch -- 10.1 Introduction -- 10.2 Application of Info-Gap Robustness for Policymaking -- 10.3 Formulation for the Design of a Mechanical Latch -- 10.4 The Info-Gap Robust Design Methodology -- 10.5 Assessment of Two Competing Designs -- 10.6 Concluding Remarks -- References -- 11 Engineering Options Analysis (EOA): Applications -- 11.1 Case Study 1: Liquid Natural Gas in Victoria State, Australia -- 11.2 Setup of the EOA Approach for the LNG Case Study -- 11.2.1 Design Alternatives -- 11.2.2 Parameter Values -- 11.2.3 Characterization of Sources of Uncertainty -- 11.3 Results from Applying the EOA Approach to the LNG Case Study -- 11.3.1 Fixed Design. , 11.3.2 Performance of Fixed Design Under Uncertainty -- 11.3.3 Flexible Strategies -- 11.3.4 Flexible Strategy-Timing (But No Learning) -- 11.3.5 Flexible Strategy-Timing and Location (But No Learning) -- 11.3.6 Flexible Strategy-Learning -- 11.3.7 Learning Combined with Economies of Scale -- 11.3.8 Multi-criteria Comparison of Strategies -- 11.3.9 Guidance from Applying EOA to This Case -- 11.4 Case Study 2: Water Management Infrastructure in the Netherlands: IJmuiden Pumping Station -- 11.5 Setup of the EOA Approach for the IJmuiden Pumping Station -- 11.5.1 Characterization of Sources of Uncertainty -- 11.5.2 Design Alternatives -- 11.5.3 Details of the Analysis -- 11.6 Results from Applying the EOA Approach to the IJmuiden Pumping Station -- 11.6.1 Inland Water Level Regulation Function -- 11.6.2 Flood Defense Function -- 11.6.3 Guidance from Applying EOA to This Case -- 11.7 Conclusions and Reflections for Practice and Theory -- References -- DMDU-Implementation Processes -- 12 Decision Scaling (DS): Decision Support for Climate Change -- 12.1 Introduction -- 12.2 Technical Approach -- 12.2.1 Overview -- 12.2.2 Step 1. Decision Framing -- 12.2.3 Step 2. Climate Stress Test -- 12.2.4 Step 3. Estimation of Climate-Informed Risks -- 12.3 Case Study: Assessing Climate Risks to the Water Supply for Colorado Springs, Colorado, USA -- 12.3.1 Step 1: Decision Framing -- 12.3.2 Step 2: Climate Stress Test -- 12.3.3 Step 3. Estimation of Climate-Informed Risks -- 12.4 Conclusions -- References -- 13 A Conceptual Model of Planned Adaptation (PA) -- 13.1 Introduction -- 13.2 Planned Adaptation Cases -- 13.2.1 Particulate Matter Standards -- 13.2.2 Delta Management in the Netherlands -- 13.2.3 Air Transportation Safety -- 13.2.4 Internet Number Delegation -- 13.3 Generalizing Elements of Planned Adaptation -- 13.3.1 Disentangling Primary and Secondary Rules. , 13.3.2 Triggers and Events -- 13.3.3 Evaluation -- 13.4 Conclusions and Ongoing Work -- 13.4.1 Combinations of Adaptive Capabilities -- 13.4.2 Planning and Designing for Adaptation -- 13.4.3 Implications for Future Study -- References -- 14 DMDU into Practice: Adaptive Delta Management in The Netherlands -- 14.1 Organizational Aspects of Putting a DMDU Approach into Practice -- 14.2 The Case Study: Adaptive Delta Management -- 14.3 Phase I: Prior to the Start of ADM (Politicization and De-politicization) -- 14.3.1 Build a Constituency for Change that Will Allow Political Commitments to Be Made -- 14.3.2 Develop Attractive and Plausible Perspectives: The Second Delta Committee -- 14.3.3 Enhance Public Awareness and Political Commitment -- 14.3.4 Stabilize Processes -- Build Trust and Continuity into the Structure of the programme -- 14.4 Phase II: Developing Strategies and Decisionmaking -- 14.4.1 Create a Narrative that Mobilizes Administrative and Political Decisionmakers -- 14.4.2 Involve All Parties in Developing an Approach for Dealing with Deep Uncertainty -- 14.4.3 Evaluate and Upgrade the Approach Regularly -- 14.4.4 Operationalize the DMDU Approach -- 14.5 Phase III: Elaborating, Implementing, and Adjusting Strategies -- 14.5.1 Plan the Adaptation -- 14.5.2 Organize the Adaptation -- 14.5.3 Rethink Monitoring and Evaluation -- 14.6 Conclusions, Reflections, and Outlook -- References -- DMDU-Synthesis -- 15 Supporting DMDU: A Taxonomy of Approaches and Tools -- 15.1 Introduction -- 15.2 Key Ideas -- 15.2.1 Exploratory Modeling -- 15.2.2 Adaptive Planning -- 15.2.3 Decision Support -- 15.3 A Taxonomy of Approaches and Tools for Supporting Decision Making Under Deep Uncertainty -- 15.3.1 Policy Architecture -- 15.3.2 Generation of Policy Alternatives and Generation of Scenarios -- 15.3.3 Robustness Metrics -- 15.3.4 Vulnerability Analysis. , 15.4 Application of the Taxonomy.
    Additional Edition: Print version: Marchau, Vincent A. W. J. Decision Making under Deep Uncertainty Cham : Springer International Publishing AG,c2019 ISBN 9783030052515
    Language: English
    Keywords: Electronic books. ; Edited volumes ; Handbooks and manuals ; Case studies ; Electronic books
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    UID:
    gbv_832019399
    Format: 1 Online-Ressource (XI, 549 Seiten, 66,5 MB) , Illustrationen
    ISBN: 9783110311198 , 9783110388374
    Series Statement: Topoi volume 28
    Content: "The southeastern Land of Seven Rivers (Kazakhstan)--a small region in the Eurasian steppes--shows an enormous concentration of Bronze and early Iron Age archeological monuments, only a small fraction of which have been described by researchers. This study, the first comprehensive investigation of these monuments, also makes an important contribution to knowledge about the historical-cultural evolution of the region"--From publisher's website
    Note: Erscheint als Open Access bei De Gruyter , Dissertation Freie Universität Berlin 2012
    Additional Edition: ISBN 9783110309232
    Additional Edition: Erscheint auch als Druck-Ausgabe Gass, Anton Das Siebenstromland zwischen Bronze- und Früheisenzeit Berlin : De Gruyter, 2016 ISBN 9783110309232
    Additional Edition: ISBN 3110309238
    Language: German
    Subjects: History
    RVK:
    Keywords: Siebenstromland ; Funde ; Bronzezeit ; Eisenzeit ; Hochschulschrift ; Electronic book. ; Electronic books. ; History.
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: Cover
    URL: Volltext  (kostenfrei)
    URL: Volltext  (Open Access)
    URL: Cover
    URL: Cover
    URL: Cover
    URL: Cover
    Author information: Gresky, Julia
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