Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road
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), sustaina...
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| Үндсэн зохиолч: | |
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| Формат: | Online |
| Хэл сонгох: | англи |
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Springer Nature
2024
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| Нөхцлүүд: | |
| Онлайн хандалт: | ONIX_20241113_9789819732784_45 |
| Шошгууд: |
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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| _version_ | 1869524480773062656 |
|---|---|
| author | Guo, Huadong |
| author_browse | Guo, Huadong |
| author_facet | Guo, Huadong |
| author_sort | Guo, Huadong |
| collection | Directory of Open Access Books |
| description | 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 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. |
| format | Online |
| id | doab-20.500.12854ir-147865 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1478652024-11-14T04:35:24Z Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road Guo, Huadong Big data Earth observation Decision support Zero hunger Clean water Climate action Sustainable cities Life below water Life on land Affordable and Clean Energy thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing 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 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. 2024-11-14T04:35:22Z 2024-11-14T04:35:22Z 2024-11-13T12:48:25Z 2024 book ONIX_20241113_9789819732784_45 https://library.oapen.org/handle/20.500.12657/94649 9789819732784 9789819732777 https://directory.doabooks.org/handle/20.500.12854/147865 eng Sustainable Development Goals Series open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/94649/1/978-981-97-3278-4.pdf Springer Nature Springer Nature Singapore 10.1007/978-981-97-3278-4 10.1007/978-981-97-3278-4 9fa3421d-f917-4153-b9ab-fc337c396b5a 77aa78dc-7806-4172-b35f-4ce141d3da17 9789819732784 9789819732777 Springer Nature Singapore 207 Singapore [...] open access |
| spellingShingle | Big data Earth observation Decision support Zero hunger Clean water Climate action Sustainable cities Life below water Life on land Affordable and Clean Energy thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing Guo, Huadong Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title | Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title_full | Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title_fullStr | Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title_full_unstemmed | Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title_short | Big Earth Data in Support of the Sustainable Development Goals (2022)—The Belt and Road |
| title_sort | big earth data in support of the sustainable development goals 2022 the belt and road |
| topic | Big data Earth observation Decision support Zero hunger Clean water Climate action Sustainable cities Life below water Life on land Affordable and Clean Energy thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing |
| topic_facet | Big data Earth observation Decision support Zero hunger Clean water Climate action Sustainable cities Life below water Life on land Affordable and Clean Energy thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography::RGW Geographical information systems, geodata and remote sensing |
| url | ONIX_20241113_9789819732784_45 |
| work_keys_str_mv | AT guohuadong bigearthdatainsupportofthesustainabledevelopmentgoals2022thebeltandroad |