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Big data in bioeconomy = results fro...
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Sodergard, Caj.
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Big data in bioeconomy = results from the European DataBio Project /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Big data in bioeconomy/ edited by Caj Sodergard ... [et al.].
其他題名:
results from the European DataBio Project /
其他作者:
Sodergard, Caj.
出版者:
Cham :Springer International Publishing : : 2021.,
面頁冊數:
xv, 423 p. :ill. (some col.), digital ;24 cm.
內容註:
Part I - Technological Foundation: Big Data Technologies for BioIndustries: Big Data Technologies in DataBio -- Standards and EO data platforms -- Data Types: Sensor Data -- Remote sensing -- Crowdsourced Data -- Genomics Data -- Data Integration and Modelling: Linked Data and Metadata -- Linked Data usages in Databio -- Data Pipelines: Modeling and Evaluation of models -- Analytics and visualization: Data Analytics and Machine Learning -- Real-time Data Processing -- Privacy Preserving Analytics, Processing and Data Management -- Data Visualisation -- Part II - Applications in Agriculture: Introduction Smart Agriculture -- Smart farming for sustainable agricultural production -- Genomics Biomass pilots -- Yield Prediction in Sorghum (Sorghum bicolor (L.) Moench) and Cultivated Potato (Solanum tuberosum L.) -- Delineation of management zones using satellite imageries -- Farm Weather Insurance Assessment -- Copernicus Data and CAP Subsidies Control -- Future vision, Summary and Outlook -- Part III Applications in Forestry: Introduction - state of the art of technology and market potential for Big Data in forestry -- Finnish Forest Data based Metsaan.fi-services -- Forest variable estimation and change monitoring solutions based on remote sensing Big Data -- Monitoring Forest Health: Big Data applied to diseases and plagues control -- Forest damage monitoring for the bark beetle -- Conclusions and Outlook - Summary of Big Data in forestry -- Part IV Applications in Fishery: The potential of Big data for improving pelagic fisheries sustainability -- Tuna fisheries fuel consumption reduction and safer operations -- Sustainable and added value small pelagic fisheries pilots -- Conclusion and future vision -- Part V - Summary and Outlook: Summary of experiences of the potential and Exploitation of Big Data and AI in Bioeconomy -- Glossary - Terminology, acronyms, abbreviations.
Contained By:
Springer Nature eBook
標題:
Biology, Economic - Data processing. -
電子資源:
https://doi.org/10.1007/978-3-030-71069-9
ISBN:
9783030710699
Big data in bioeconomy = results from the European DataBio Project /
Big data in bioeconomy
results from the European DataBio Project /[electronic resource] :edited by Caj Sodergard ... [et al.]. - Cham :Springer International Publishing :2021. - xv, 423 p. :ill. (some col.), digital ;24 cm.
Part I - Technological Foundation: Big Data Technologies for BioIndustries: Big Data Technologies in DataBio -- Standards and EO data platforms -- Data Types: Sensor Data -- Remote sensing -- Crowdsourced Data -- Genomics Data -- Data Integration and Modelling: Linked Data and Metadata -- Linked Data usages in Databio -- Data Pipelines: Modeling and Evaluation of models -- Analytics and visualization: Data Analytics and Machine Learning -- Real-time Data Processing -- Privacy Preserving Analytics, Processing and Data Management -- Data Visualisation -- Part II - Applications in Agriculture: Introduction Smart Agriculture -- Smart farming for sustainable agricultural production -- Genomics Biomass pilots -- Yield Prediction in Sorghum (Sorghum bicolor (L.) Moench) and Cultivated Potato (Solanum tuberosum L.) -- Delineation of management zones using satellite imageries -- Farm Weather Insurance Assessment -- Copernicus Data and CAP Subsidies Control -- Future vision, Summary and Outlook -- Part III Applications in Forestry: Introduction - state of the art of technology and market potential for Big Data in forestry -- Finnish Forest Data based Metsaan.fi-services -- Forest variable estimation and change monitoring solutions based on remote sensing Big Data -- Monitoring Forest Health: Big Data applied to diseases and plagues control -- Forest damage monitoring for the bark beetle -- Conclusions and Outlook - Summary of Big Data in forestry -- Part IV Applications in Fishery: The potential of Big data for improving pelagic fisheries sustainability -- Tuna fisheries fuel consumption reduction and safer operations -- Sustainable and added value small pelagic fisheries pilots -- Conclusion and future vision -- Part V - Summary and Outlook: Summary of experiences of the potential and Exploitation of Big Data and AI in Bioeconomy -- Glossary - Terminology, acronyms, abbreviations.
Open access.
This edited open access book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources. As a European initiative, the goal is to use these new findings to support decision-makers and producers - meaning farmers, land and forest owners and fishermen. With their 27 pilot projects from 17 countries, the authors examine important sectors and highlight examples where modern data-driven methods were used to increase sustainability. How can farmers, foresters or fishermen use these insights in their daily lives? The authors answer this and other questions for our readers. The first four parts of this book give an overview of the big data technologies relevant for optimal raw material gathering. The next three parts put these technologies into perspective, by showing useable applications from farming, forestry and fishery. The final part of this book gives a summary and a view on the future. With its broad outlook and variety of topics, this book is an enrichment for students and scientists in bioeconomy, biodiversity and renewable resources.
ISBN: 9783030710699
Standard No.: 10.1007/978-3-030-71069-9doiSubjects--Topical Terms:
3513809
Biology, Economic
--Data processing.
LC Class. No.: QH705
Dewey Class. No.: 333.95
Big data in bioeconomy = results from the European DataBio Project /
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