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Measuring and evaluating SDG indicators with Big Earth Data

文献类型：期刊论文

作者Guo, Huadong2,3; Liang, Dong2,3; Sun, Zhongchang3; Chen, Fang2,3; Wang, Xinyuan2,3; Li, Junsheng2,3; Zhu, Li1; Bian, Jinhu6; Wei, Yanqiang5; Huang, Lei3
刊名SCIENCE BULLETIN
出版日期2022
卷号67期号:17页码:1792-1801
关键词Big Earth Data Big data Sustainable Development Goals (SDGs) Decision support CASEarth Digital Earth
ISSN号2095-9273
DOI10.1016/j.scib.2022.07.015
文献子类Article
英文摘要The United Nations 2030 Agenda for Sustainable Development provides an important framework for eco-nomic, social, and environmental action. A comprehensive indicator system to aid in the systematic implementation and monitoring of progress toward the Sustainable Development Goals (SDGs) is unfortunately limited in many countries due to lack of data. The availability of a growing amount of multi-source data and rapid advancements in big data methods and infrastructure provide unique oppor-tunities to mitigate these data shortages and develop innovative methodologies for comparatively mon-itoring SDGs. Big Earth Data, a special class of big data with spatial attributes, holds tremendous potential to facilitate science, technology, and innovation toward implementing SDGs around the world. Several programs and initiatives in China have invested in Big Earth Data infrastructure and capabilities, and have successfully carried out case studies to demonstrate their utility in sustainability science. This paper pre-sents implementations of Big Earth Data in evaluating SDG indicators, including the development of new algorithms, indicator expansion (for SDG 11.4.1) and indicator extension (for SDG 11.3.1), introduction of a biodiversity risk index as a more effective analysis method for SDG 15.5.1, and several new high-quality data products, such as global net ecosystem productivity, high-resolution global mountain green cover index, and endangered species richness. These innovations are used to present a comprehensive analysis of SDGs 2, 6,11,13, 14, and 15 from 2010 to 2020 in China utilizing Big Earth Data, concluding that all six SDGs are on schedule to be achieved by 2030.(c) 2022 Science China Press. Published by Elsevier B.V. and Science China Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
学科主题Multidisciplinary Sciences
出版地AMSTERDAM
电子版国际标准刊号2095-9281
WOS关键词SUSTAINABLE DEVELOPMENT GOALS ; CONSERVATION STATUS ; CLIMATE-CHANGE ; RED LIST ; INDEX ; SUPPORT ; ENGINE
WOS研究方向Science Citation Index Expanded (SCI-EXPANDED)
语种英语
WOS记录号WOS:000862291100016
出版者ELSEVIER
资助机构Big Earth Data Science Engi- neering Program of the Chinese Academy of Sciences [XDA19090000, XDA19030000]
源URL[http://ir.ibcas.ac.cn/handle/2S10CLM1/28524]  
专题植被与环境变化国家重点实验室
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
3.Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China
4.Chinese Acad Sci, Northwest Inst Eco Environm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China
5.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
6.Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Huadong,Liang, Dong,Sun, Zhongchang,et al. Measuring and evaluating SDG indicators with Big Earth Data[J]. SCIENCE BULLETIN,2022,67(17):1792-1801.
APA Guo, Huadong.,Liang, Dong.,Sun, Zhongchang.,Chen, Fang.,Wang, Xinyuan.,...&Shirazi, Zeeshan.(2022).Measuring and evaluating SDG indicators with Big Earth Data.SCIENCE BULLETIN,67(17),1792-1801.
MLA Guo, Huadong,et al."Measuring and evaluating SDG indicators with Big Earth Data".SCIENCE BULLETIN 67.17(2022):1792-1801.

入库方式： OAI收割

来源：植物研究所

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