000 05788nam a22006735i 4500
001 978-3-030-71069-9
003 DE-He213
005 20250526092116.0
007 cr nn 008mamaa
008 210813s2021 sz | s |||| 0|eng d
020 _a9783030710699
_9978-3-030-71069-9
024 7 _a10.1007/978-3-030-71069-9
_2doi
050 4 _aSD1-668
050 4 _aQH541.5.F6
072 7 _aPSAF
_2bicssc
072 7 _aTVR
_2bicssc
072 7 _aTEC003040
_2bisacsh
072 7 _aPSAF
_2thema
072 7 _aTVR
_2thema
082 0 4 _a634.9
_223
082 0 4 _a577.3
_223
245 1 0 _aBig Data in Bioeconomy
_h[electronic resource] :
_bResults from the European DataBio Project /
_cedited by Caj Södergård, Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Jose A. Fernandes, Christian Zinke-Wehlmann.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXVI, 423 p. 192 illus., 183 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _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.
506 0 _aOpen Access
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 andfishery. 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.
650 0 _aForestry.
650 0 _aAgriculture
_xEconomic aspects.
650 0 _aBig data.
650 0 _aPower resources.
650 0 _aEnvironmental economics.
650 1 4 _aForestry.
650 2 4 _aAgricultural Economics.
650 2 4 _aBig Data.
650 2 4 _aResource and Environmental Economics.
700 1 _aSödergård, Caj.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aMildorf, Tomas.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aHabyarimana, Ephrem.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aBerre, Arne J.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFernandes, Jose A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZinke-Wehlmann, Christian.
_eeditor.
_0(orcid)0000-0002-7440-3270
_1https://orcid.org/0000-0002-7440-3270
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030710682
776 0 8 _iPrinted edition:
_z9783030710705
776 0 8 _iPrinted edition:
_z9783030710712
856 4 0 _uhttps://doi.org/10.1007/978-3-030-71069-9
912 _aZDB-2-SBL
912 _aZDB-2-SXB
912 _aZDB-2-SOB
999 _c68
_d68