Earth Observation Open Science and Innovation.

Earth Observation Open Science and Innovation.

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Bibliographic Details
Superior document:ISSI Scientific Report Series ; v.15
:
Mathieu, Pierre-Philippe.
TeilnehmendeR:
Aubrecht, Christoph.
Place / Publishing House:Cham : : Springer International Publishing AG,, 2018.
©2018.
Year of Publication:2018
Edition:1st ed.
Language:English
Series:ISSI Scientific Report Series
Online Access:
Physical Description:1 online resource (328 pages)
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Table of Contents:
  • Intro
  • Foreword
  • Contents
  • Part I Join the Geo Revolution
  • The Changing Landscape of Geospatial Information Markets
  • Introduction
  • Rise of the Platforms
  • Data as a Service
  • Open Data Policies
  • New Business Models
  • Sensor Use Growing
  • Crowdsourcing
  • Disruptive Innovation
  • Cloud Computing
  • Business Models in Cloud Computing
  • Microsoft Azure
  • Amazon Web Services (AWS)
  • Google Cloud Platform
  • Conclusion
  • References
  • The Digital Transformation of Education
  • Case Study: How the World Bank Group's Open Learning Campus is Partnering with Earth Observation Satellite Data to Enrich the Learning Experience
  • Learning as an Accelerator to Achieve Development Goals
  • Progress of the OLC so Far
  • Flexible Pathways to Learning
  • Increasing Importance of Geospatial Data
  • Examples of How the OLC is Incorporating Spatial Data
  • Issues Relevant to This Experience for the Earth Observation Community
  • Case Study Conclusion
  • References
  • The Open Science Commons for the European Research Area
  • Creating the European Research Area: The "Open" Approach
  • Problems to Solve
  • Lack and/or Incomplete Roadmaps for Research- and e-Infrastructures
  • Fragmented Solutions and Policies for Access to Data and Knowledge
  • Insufficient Cooperation Between Public and Private Sector
  • Lack of National and European Organization Between All Stakeholders
  • Many Providers Without a Single Market
  • The Open Science Commons
  • The European Open Science Cloud
  • Open Science Commons for the EOSC
  • EOSC Architecture and Services
  • Realizing a Federated Approach to Research Data
  • Offering of Scalable Access to and Analysis of Research Data for Reuse
  • Integrating (Shared) Tools and Applications
  • Provisioning of Services for Depositing Data for Resource-Bound Users
  • EOSC Service Integration and Management.
  • EOSC Governance
  • EOSC and the e-Infrastructure Commons
  • The EGI Blueprint
  • Core Infrastructure Platform
  • Collaborative Platform
  • The EGI Federated Cloud
  • The Data Hub and the Open Data Platform
  • EO Data Exploitation via the e-Infrastructures and EOSC
  • Infrastructure Services for EO Data Exploitation
  • An Example: e-Infrastructure Services to Implement the ESA Generic Exploitation Platform Open Architecture
  • An Example: Integration of the Geohazard Exploitation Platform Within the EGI Infrastructure
  • Conclusions
  • References
  • Citizen Science for Observing and Understanding the Earth
  • Introduction
  • Societal and Technological Trends
  • Citizen Science Today: Main Areas of Activity
  • Citizen Science Across Domains: Long-Running Citizen Science
  • The Impact of Technology: Citizen Cyberscience
  • Depth of Participation: Community Science
  • Citizen Science and Earth Observation: Technical, Societal, Ethical and Policy Aspects
  • Technical Aspects
  • Societal and Ethical Aspects
  • Citizen Science Integration into Policy
  • Conclusions
  • References
  • Part II Enabling Data Intensive Science
  • Fostering Cross-Disciplinary Earth Science Through DatacubeAnalytics
  • Introduction
  • Standards-Based Modelling of Datacubes
  • Coverage Data Model
  • Web Coverage Service
  • Web Coverage Processing Service
  • The Role of Standards
  • Science Data Services
  • Earth Observation Data Services
  • Marine Science Data Service
  • Climate Science Data Service
  • Planetary Science Data Service
  • Cross-Service Federation Queries
  • Datacube Analytics Technology
  • Array Databases as Datacube Platform
  • Array Storage
  • Array Processing
  • Tool Integration
  • The Role and Handling of Metadata
  • Virtual Globes as Datacube Interfaces
  • Related Work
  • Conclusion and Outlook
  • References.
  • Mind the Gap: Big Data vs. Interoperability and Reproducibility of Science
  • Introduction: the Big Data Paradox
  • It's All in the Framing!
  • Towards Open (Shared) Knowledge
  • The GEOSS Case
  • Big Data Infrastructure Services: The GEOSS Common Infrastructure (GCI) Big Data Strategy
  • Content Harmonization and Information/Knowledge Generation: The Brokering Framework
  • The Brokering framework
  • The DAB
  • More (Value) knowledge to reduce Volume
  • From Data to Knowledge: the GEOSS Knowledge Base and High-Performance Data Analytics
  • The DIKW pattern
  • The GEOSS Knowledge Base
  • High-Performance Analytics and GEOSS
  • Conclusions
  • References
  • Cyber-Infrastructure for Data-Intensive Geospatial Computing
  • Introduction
  • Settlement Mapping Tool (SMTOOL)
  • Toolbox for Urban Mobility Simulations (TUMS)
  • Global Dataset
  • Framework
  • OD Tables
  • Resolution
  • Unified Network and Population Database
  • Big Data
  • Urban Information System (UrbIS)
  • Leveraging Big Data to Understand Urban Impact on Environment and Climate
  • Conclusions
  • References
  • Machine Learning Applications for Earth Observation
  • Introduction
  • What Is Machine Learning?
  • Some Existing Machine Learning Applications
  • Machine Learning for Bias Correction and Cross Calibration
  • Vegetation Indices
  • Space-Based Measurements of HCl Relevant for Ozone Depletion
  • HCl and Cly Time Series
  • Bias Correction of MODIS Aerosol Optical Depth
  • Data Description
  • Machine Learning AOD Bias Correction
  • Machine Learning for New Product Creation
  • Airborne Particulates
  • Tracer Correlations
  • Reconstructing CH4-N2O Correlations
  • Pollen Estimation
  • Predicting Pollen Abundance
  • Using Machine Learning for Ocean Data Products
  • Dust Source Identification Using Unsupervised Classification
  • Bolivia and Chile Salt Flats Dust Event.
  • Bodélé Depression Dust Event
  • Characterizing Pelagic Habitats Within Coastal Waters
  • Fish Catch and SOM Classes
  • Some Likely Future Machine Learning Applications
  • Hyper-Spectral Imaging and Machine Learning for Real Time Embedded Processing and Decision Support
  • Oil Spills
  • Summary
  • References
  • New Generation Platforms for Exploration of CrowdsourcedGeo-Data
  • Introduction
  • Virtual Globes as the New Generation Visualization Platforms
  • Virtual Globes for the Exploration of Crowdsourced Geo-Data
  • Applications
  • PoliCrowd
  • Open Data Kit (ODK)
  • NASA World Wind Java SDK
  • System Architecture
  • Overview of Functionalities
  • Telecommunication Data Viewer
  • The netCDF Data Format
  • EST-WA: A Multidimensional Data Viewer
  • Application of EST-WA to Explore Geo-Crowdsourced Data
  • Conclusions
  • References
  • Part III Use Cases Open Science and Innovation
  • Mapping Land Use Dynamics Using the Collective Powerof the Crowd
  • Concept and Context
  • The Collective Power of the Crowd
  • VGDI Access and Integration: The Foursquare Use Case
  • What Is Next and Where Are We Headed?
  • References
  • The Emergence of the GeoSharing Economy
  • GeoSharing Platform Requirements
  • Technical Access
  • Commercial and Legal Access
  • Reference
  • Sustainable Agriculture and Smart Farming
  • Multi-Year Site-Characterization of Fields Using Advanced Data Harvesting Techniques
  • Up-to-Date Crop Status Using Access to Satellite Data in Near-Real-Time
  • Conclusions and Outlook
  • References
  • Earth Observation Data for Enterprise Business Applications
  • Development of an Earth Observation Cloud Platform in Support to Water Resources Monitoring
  • Introduction
  • EODC: The Earth Observation Data Centre for Water Resources Management
  • Pilot Services
  • Closing Remarks
  • References
  • Putting Big Data Innovation into Action for Development.
  • Tracking Light from the Sky: Monitoring Rural Electrification from Space
  • Tracking Poverty from Space
  • Satellite-Based Yield Measurement
  • Conclusion
  • Mapping Floods and Assessing Flood Vulnerability for Disaster Decision-Making: A Case Study Remote Sensing Applicationin Senegal
  • Introduction
  • Why Senegal? An Example of the Critical Information Gap in Disaster Management
  • Socio-Physical Vulnerability to Flooding to Senegal
  • Using Big Data Information in Disaster Management
  • The Future of This Approach Globally and Locally as a Practical Tool
  • Conclusion
  • References
  • Earth Observation and Geospatial Implementation: Fueling Innovation in a Changing World
  • Earth Observation Scientific Data Access, Discovery, and Challenges
  • How Are Maps and Earth Observation Data Transforming Our World?
  • Delivering Geospatial Data and Information Products with Web GIS
  • Esri and Big Data
  • Notable Solutions and Capabilities
  • Conclusion
  • References
  • Artificial Intelligence and Earth Observation to Explore Water Quality in the Wadden Sea
  • Introduction
  • Inductive Learning
  • Data Description
  • Methods
  • Results and Discussion
  • Conclusions
  • References
  • Erratum to: Citizen Science for Observing and Understanding the Earth
  • Index.

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