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Record Nr. |
UNINA9910898593503321 |
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Autore |
Guo Huadong |
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Titolo |
Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road / / by Huadong Guo |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (XVIII, 207 p. 117 illus., 114 illus. in color.) |
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Collana |
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Sustainable Development Goals Series, , 2523-3092 |
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Disciplina |
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Soggetti |
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Sustainability |
Energy policy |
Energy and state |
Physical geography |
Geographic information systems |
Energy Policy, Economics and Management |
Earth System Sciences |
Geographical Information System |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction. -- SDG 2 Zero Hunger -- SDG 6 Clean Water and Sanitation -- SDG 7 Affordable and Clean Energy -- SDG 11 Sustainable Cities and Communities -- SDG 13 Climate Action -- SDG 14 Life Below Water -- Chapter 8 SDG 15 Life on Land -- Interactions Among SDGs and Integrated Evaluations -- Summary and Prospects. |
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Sommario/riassunto |
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This open access book showcases the innovative practices of Big Earth Data methods through a collection of global comprehensive case studies to monitor and evaluate indicators for seven SDGs, i.e., zero hunger (SDG 2), clean water and sanitation (SDG 6), affordable and clean energy (SDG 7), sustainable cities and communities (SDG 11), climate action (SDG 13), life below water (SDG 14), life on land (SDG 15), and to analyzes the interactions among multiple SDGs indicators. The emphasis on Big Earth Data is highly relevant within the context of growing global challenges. Disaster risk mitigation, climate change, global food security, resource management, and environmental |
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challenges all are interlinked through earth systems and processes that are independent of human constructs. Therefore these case studies highlight methods and practices of spatial information mining and integrated SDG evaluation, which include evaluating the synergy and trade-off relationships among the SDGs in the context of their correlations; simulating multiple indicators’ interactions in environmental, economic, and social scenarios in the context of their temporal variations; designing integrated evaluations of regional SDGs in the context of experience with the study of multiple indicators. Big Earth Data therefore has the potential to support informed policy and decision support at global, regional, and local scales. |
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