Big Earth Data in Support of the Sustainable Development Goals (2021): The Belt and Road
Big Earth Data in Support of the Sustainable Development Goals (2021): The Belt and Road showcases the innovative practice of applying Big Earth Data to the monitoring and evaluating indicators for six SDGs,i.c., SDG 2 Zero Hunger, SDG 6 Clean Water and Sanitation, SDG 11 Sustainable Cities and Comm...
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| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Les Ulis
EDP Sciences
[2022]
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| Schlagworte: | |
| Online-Zugang: | FAW01 FAB01 FCO01 FHA01 FKE01 FLA01 UPA01 Volltext |
| Zusammenfassung: | Big Earth Data in Support of the Sustainable Development Goals (2021): The Belt and Road showcases the innovative practice of applying Big Earth Data to the monitoring and evaluating indicators for six SDGs,i.c., SDG 2 Zero Hunger, SDG 6 Clean Water and Sanitation, SDG 11 Sustainable Cities and Communities, SDG 13 Climate Action, SDG14 Life below Water, SDG 15 Life on Land, and the analysis of the interactions among multiple SDG indicators. It presents 42 case studies on 22 targets relevant to countries and regions involved in the Belt and Road Initiative. The report showcases the results of research, monitoring, and evaluation of SDGs and their indicators at four scales--local, national, regional, and global--totalling 37 data products, 19 methods and models, and 32 decision-support recommendations. These research results demonstrate China's exploration and practice in promoting the implementation of the UN 2030 Agenda for Sustainable Development through scientific and technological innovation, fully reveal the application value and broad prospects of Earth's big data technology in monitoring and evaluating the sustainable development goals, and open up new ways and methods to support the implementation of the UN 2030 Agenda for Sustainable Development through the use of advanced technologies and methods such as big data and artificial intelligence under the framework of the UN technology promotion mechanism. It can provide reference for countries to strengthen the implementation monitoring and evaluation of the agenda.This report can be read by researchers in related fields and decision makers in relevant national departments |
| Beschreibung: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 27. Jan 2023) |
| Beschreibung: | 1 Online-Ressource (390 pages) |
| ISBN: | 9782759829378 |
| DOI: | 10.1051/978-2-7598-2937-8 |
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| isbn | 9782759829378 |
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| spelling | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road ed. by Guo Huadong Les Ulis EDP Sciences [2022] © 2022 1 Online-Ressource (390 pages) txt rdacontent c rdamedia cr rdacarrier Description based on online resource; title from PDF title page (publisher's Web site, viewed 27. Jan 2023) Big Earth Data in Support of the Sustainable Development Goals (2021): The Belt and Road showcases the innovative practice of applying Big Earth Data to the monitoring and evaluating indicators for six SDGs,i.c., SDG 2 Zero Hunger, SDG 6 Clean Water and Sanitation, SDG 11 Sustainable Cities and Communities, SDG 13 Climate Action, SDG14 Life below Water, SDG 15 Life on Land, and the analysis of the interactions among multiple SDG indicators. It presents 42 case studies on 22 targets relevant to countries and regions involved in the Belt and Road Initiative. The report showcases the results of research, monitoring, and evaluation of SDGs and their indicators at four scales--local, national, regional, and global--totalling 37 data products, 19 methods and models, and 32 decision-support recommendations. These research results demonstrate China's exploration and practice in promoting the implementation of the UN 2030 Agenda for Sustainable Development through scientific and technological innovation, fully reveal the application value and broad prospects of Earth's big data technology in monitoring and evaluating the sustainable development goals, and open up new ways and methods to support the implementation of the UN 2030 Agenda for Sustainable Development through the use of advanced technologies and methods such as big data and artificial intelligence under the framework of the UN technology promotion mechanism. It can provide reference for countries to strengthen the implementation monitoring and evaluation of the agenda.This report can be read by researchers in related fields and decision makers in relevant national departments In English SCIENCE / Environmental Science (see also Chemistry / Environmental) bisacsh Huadong, Guo Sonstige oth https://doi.org/10.1051/978-2-7598-2937-8 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road SCIENCE / Environmental Science (see also Chemistry / Environmental) bisacsh |
| title | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road |
| title_auth | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road |
| title_exact_search | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road |
| title_exact_search_txtP | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road |
| title_full | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road ed. by Guo Huadong |
| title_fullStr | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road ed. by Guo Huadong |
| title_full_unstemmed | Big Earth Data in Support of the Sustainable Development Goals (2021) The Belt and Road ed. by Guo Huadong |
| title_short | Big Earth Data in Support of the Sustainable Development Goals (2021) |
| title_sort | big earth data in support of the sustainable development goals 2021 the belt and road |
| title_sub | The Belt and Road |
| topic | SCIENCE / Environmental Science (see also Chemistry / Environmental) bisacsh |
| topic_facet | SCIENCE / Environmental Science (see also Chemistry / Environmental) |
| url | https://doi.org/10.1051/978-2-7598-2937-8 |
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