001431114 000__ 05118cam\a2200529\i\4500
001431114 001__ 1431114
001431114 003__ OCoLC
001431114 005__ 20230308003221.0
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001431114 020__ $$a9783030710699$$q(electronic bk.)
001431114 020__ $$a3030710696$$q(electronic bk.)
001431114 020__ $$z9783030710682$$q(print)
001431114 0247_ $$a10.1007/978-3-030-71069-9$$2doi
001431114 035__ $$aSP(OCoLC)1264407940
001431114 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCO$$dYDX$$dOCLCF$$dOCLCQ$$dOCLCO$$dOCLCQ$$dEBLCP$$dOCLCQ
001431114 049__ $$aISEA
001431114 050_4 $$aQH705
001431114 08204 $$a333.95$$223
001431114 24500 $$aBig data in bioeconomy :$$bresults from the European DataBio Project /$$cCaj Södergård, Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Jose A. Fernandes, Christian Zinke-Wehlmann, editors.
001431114 264_1 $$aCham, Switzerland :$$bSpringer,$$c2021.
001431114 300__ $$a1 online resource (xv, 423 pages) :$$billustrations (some color)
001431114 336__ $$atext$$btxt$$2rdacontent
001431114 337__ $$acomputer$$bc$$2rdamedia
001431114 338__ $$aonline resource$$bcr$$2rdacarrier
001431114 5050_ $$aPart 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 Metsään.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.
001431114 5060_ $$aOpen access.$$5GW5XE
001431114 520__ $$aThis edited open access book presents the comprehensive outcome of The European DataBio Project, which examined new data-driven methods to shape a bioeconomy. These methods are used to develop new and sustainable ways to use forest, farm and fishery resources. As a European initiative, the goal is to use these new findings to support decision-makers and producers -- meaning farmers, land and forest owners and fishermen. With their 27 pilot projects from 17 countries, the authors examine important sectors and highlight examples where modern data-driven methods were used to increase sustainability. How can farmers, foresters or fishermen use these insights in their daily lives? The authors answer this and other questions for our readers. The first four parts of this book give an overview of the big data technologies relevant for optimal raw material gathering. The next three parts put these technologies into perspective, by showing useable applications from farming, forestry and fishery. The final part of this book gives a summary and a view on the future. With its broad outlook and variety of topics, this book is an enrichment for students and scientists in bioeconomy, biodiversity and renewable resources.
001431114 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 20, 2021).
001431114 650_0 $$aBiology, Economic$$xData processing.
001431114 650_0 $$aBig data.
001431114 650_6 $$aBiologie économique$$xInformatique.
001431114 650_6 $$aDonnées volumineuses.
001431114 655_0 $$aElectronic books.
001431114 7001_ $$aSödergård, Caj,$$eeditor.
001431114 7001_ $$aMildorf, Tomas,$$eeditor.
001431114 7001_ $$aHabyarimana, Ephrem,$$eeditor.
001431114 7001_ $$aBerre, Arne J.,$$eeditor.
001431114 7001_ $$aFernandes, Jose A.,$$eeditor.
001431114 7001_ $$aZinke-Wehlmann, Christian,$$eeditor$$0(orcid)0000-0002-7440-3270$$1https://orcid.org/0000-0002-7440-3270
001431114 852__ $$bebk
001431114 85640 $$3Springer Nature$$uhttps://link.springer.com/10.1007/978-3-030-71069-9$$zOnline Access$$91397441.2
001431114 909CO $$ooai:library.usi.edu:1431114$$pGLOBAL_SET
001431114 980__ $$aBIB
001431114 980__ $$aEBOOK
001431114 982__ $$aEbook
001431114 983__ $$aOnline
001431114 994__ $$a92$$bISE