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024 7 $a10.1007/978-981-97-3278-4
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035   $a(DE-He213)978-981-97-3278-4
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100   $a20241030d2024      u|         0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aBig Earth Data in Support of the Sustainable Development Goals (2022)?The Belt and Road /$fby Huadong Guo
205   $a1st ed. 2024.
210  1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024.
215   $a1 online resource (XVIII, 207 p. 117 illus., 114 illus. in color.) 
225 1 $aSustainable Development Goals Series,$x2523-3092
311 08$a9789819732777 
311 08$a9819732778 
327   $aIntroduction. -- 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.
330   $aThis open access book showcases the innovative practices of Big Earth Data methods through a collection of global comprehensive case studies to monitor and evaluate indicators for seven SDGs, i.e., zero hunger (SDG 2), clean water and sanitation (SDG 6), affordable and clean energy (SDG 7), sustainable cities and communities (SDG 11), climate action (SDG 13), life below water (SDG 14), life on land (SDG 15), and to analyzes the interactions among multiple SDGs indicators. The emphasis on Big Earth Data is highly relevant within the context of growing global challenges. Disaster risk mitigation, climate change, global food security, resource management, and environmental challenges all are interlinked through earth systems and processes that are independent of human constructs. Therefore these case studies highlight methods and practices of spatial information mining and integrated SDG evaluation, which include evaluating the synergy and trade-off relationships among the SDGs in the context of their correlations; simulating multiple indicators? interactions in environmental, economic, and social scenarios in the context of their temporal variations; designing integrated evaluations of regional SDGs in the context of experience with the study of multiple indicators. Big Earth Data therefore has the potential to support informed policy and decision support at global, regional, and local scales.
410  0$aSustainable Development Goals Series,$x2523-3092
606   $aSustainability
606   $aEnergy policy
606   $aEnergy and state
606   $aPhysical geography
606   $aGeographic information systems
606   $aSustainability
606   $aEnergy Policy, Economics and Management
606   $aEarth System Sciences
606   $aGeographical Information System
615  0$aSustainability.
615  0$aEnergy policy.
615  0$aEnergy and state.
615  0$aPhysical geography.
615  0$aGeographic information systems.
615 14$aSustainability.
615 24$aEnergy Policy, Economics and Management.
615 24$aEarth System Sciences.
615 24$aGeographical Information System.
676   $a304.2
700   $aGuo$b Huadong$4aut$4http://id.loc.gov/vocabulary/relators/aut$0993478
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910898593503321
996   $aBig Earth Data in Support of the Sustainable Development Goals (2022)?The Belt and Road$94212874
997   $aUNINA