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| Measuring and evaluating SDG indicators with Big Earth Data | |
| Guo, Huadong1,2; Liang, Dong1,2; Sun, Zhongchang1; Chen, Fang1,2; Wang, Xinyuan1,2; Li, Junsheng1,2; Zhu, Li3; Bian, Jinhu4; Wei, Yanqiang5; Huang, Lei1; Chen, Yu1; Peng, Dailiang1; Li, Xiaosong1,2; Lu, Shanlong1,2; Liu, Jie; Shirazi, Zeeshan1 | |
| 2022 | |
| 发表期刊 | SCIENCE BULLETIN
 |
| ISSN | 2095-9273 |
| 卷号 | 67期号:17页码:1792-1801 |
| 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/). |
| 关键词 | Big Earth Data Big data Sustainable Development Goals (SDGs) Decision support CASEarth Digital Earth |
| 学科领域 | Multidisciplinary Sciences |
| DOI | 10.1016/j.scib.2022.07.015 |
| 收录类别 | SCI |
| 语种 | 英语 |
| 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) |
| WOS记录号 | WOS:000862291100016 |
| 出版者 | ELSEVIER |
| 文献子类 | Article |
| 出版地 | AMSTERDAM |
| EISSN | 2095-9281 |
| 资助机构 | Big Earth Data Science Engi- neering Program of the Chinese Academy of Sciences [XDA19090000, XDA19030000] |
| 作者邮箱 | hdguo@radi.ac.cn |
| 作品OA属性 | hybrid |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | 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.Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China 2.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China 5.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 6.Chinese Acad Sci, Northwest Inst Eco Environm & Resources, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, 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. |
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| Measuring_and_evalua（3382KB） | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 | |
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