Big Earth Data in Support of the Sustainable Development Goals (2022) - China
dc.contributor.author | Guo, Huadong | |
dc.date.accessioned | 2024-10-25T12:03:02Z | |
dc.date.available | 2024-10-25T12:03:02Z | |
dc.date.issued | 2024 | |
dc.identifier | ONIX_20241025_9789819742318_5 | |
dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/93982 | |
dc.description.abstract | This open access book showcases the innovative practices of Big Earth Data methods through a collection of comprehensive case studies from China 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 analyze 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 future 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. | |
dc.language | English | |
dc.relation.ispartofseries | Sustainable Development Goals Series | |
dc.subject.classification | thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability | |
dc.subject.classification | thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment | |
dc.subject.classification | thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences | |
dc.subject.classification | thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing | |
dc.subject.other | Big data | |
dc.subject.other | Earth observation | |
dc.subject.other | Decision support | |
dc.subject.other | Zero hunger | |
dc.subject.other | Clean water | |
dc.subject.other | Sustainable cities | |
dc.subject.other | Climate action | |
dc.subject.other | Life below water | |
dc.subject.other | Life on land | |
dc.subject.other | Affordable and Clean Energy | |
dc.title | Big Earth Data in Support of the Sustainable Development Goals (2022) - China | |
dc.type | book | |
oapen.identifier.doi | 10.1007/978-981-97-4231-8 | |
oapen.relation.isPublishedBy | 6c6992af-b843-4f46-859c-f6e9998e40d5 | |
oapen.relation.isFundedBy | e00b434e-32b7-4991-a148-e3649398a8f7 | |
oapen.relation.isbn | 9789819742318 | |
oapen.relation.isbn | 9789819742301 | |
oapen.imprint | Springer Nature Singapore | |
oapen.pages | 301 | |
oapen.place.publication | Singapore | |
oapen.grant.number | [...] |