LEADER 05700nam 22008055 450 001 9910494568803321 005 20250628110031.0 010 $a3-030-71069-6 024 7 $a10.1007/978-3-030-71069-9 035 $a(CKB)5590000000549845 035 $aEBL6700223 035 $a(OCoLC)1264407940 035 $a(AU-PeEL)EBL6700223 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/72050 035 $a(MiAaPQ)EBC6700223 035 $a(PPN)257355405 035 $a(DE-He213)978-3-030-71069-9 035 $a(Au-PeEL)EBL6700223 035 $a(ODN)ODN0010067374 035 $a(oapen)doab72050 035 $a(EXLCZ)995590000000549845 100 $a20210813d2021 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data in Bioeconomy $eResults from the European DataBio Project /$fedited by Caj Södergård, Tomas Mildorf, Ephrem Habyarimana, Arne J. Berre, Jose A. Fernandes, Christian Zinke-Wehlmann 205 $a1st ed. 2021. 210 $d2021 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (416 p.) 300 $aDescription based upon print version of record. 311 08$a3-030-71068-8 327 $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. 330 $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. 606 $aForests and forestry 606 $aAgriculture$xEconomic aspects 606 $aBig data 606 $aPower resources 606 $aEnvironmental economics 606 $aForestry 606 $aAgricultural Economics 606 $aBig Data 606 $aResource and Environmental Economics 615 0$aForests and forestry. 615 0$aAgriculture$xEconomic aspects. 615 0$aBig data. 615 0$aPower resources. 615 0$aEnvironmental economics. 615 14$aForestry. 615 24$aAgricultural Economics. 615 24$aBig Data. 615 24$aResource and Environmental Economics. 676 $a634.9 676 $a577.3 686 $aBUS069000$aBUS070010$aCOM021000$aTEC003040$2bisacsh 700 $aSo?derga?rd$b Caj$01237368 701 $aMildorf$b Tomas$01237369 701 $aHabyarimana$b Ephrem$01069595 701 $aBerre$b Arne J$01237370 701 $aFernandes$b Jose A$01237371 701 $aZinke-Wehlmann$b Christian$01237372 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910494568803321 996 $aBig Data in Bioeconomy$92872421 997 $aUNINA