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Big Earth Data in support of the Sustainable Development Goals (2022) - China

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Big Earth Data in support of the Sustainable Development Goals (2022) - China/ by Huadong Guo.
作者:	Guo, Huadong.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xvii, 301 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Spatial data mining. -
電子資源:	https://doi.org/10.1007/978-981-97-4231-8
ISBN:	9789819742318

Big Earth Data in support of the Sustainable Development Goals (2022) - China
Guo, Huadong.

Big Earth Data in support of the Sustainable Development Goals (2022) - China[electronic resource] /by Huadong Guo. - Singapore :Springer Nature Singapore :2024. - xvii, 301 p. :ill. (chiefly color), digital ;24 cm. - Sustainable development goals series,2523-3092. - Sustainable development goals series..

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. -- SDG 15 Life on Land. -- Interactions Among the SDGs and Integrated Evaluations. -- Summary and Prospects.

Open access.

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.

ISBN: 9789819742318

Standard No.: 10.1007/978-981-97-4231-8doiSubjects--Topical Terms:

1482392
Spatial data mining.

LC Class. No.: G70.217.G46

Dewey Class. No.: 910.285

Big Earth Data in support of the Sustainable Development Goals (2022) - China
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