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Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

Big Earth Data, Sustainable Development Goals (SDGs), SDG indicators monitoring, International Research Center of Big Data for Sustainable Development Goals

Document Type

Overview

Abstract

In 2015, the United Nations adopted 17 sustainable development goals (SDGs) to guide the economic, social, and environmental aspects of development. However, several factors have constrained the implementation of the SDGs, including uneven development, lack of data, and the interconnection and mutual restriction between the goals. In particular, the outbreak of COVID-19 pandemic in 2020 exacerbated the challenges faced by countries in implementing SDGs. This study focuses on the need to improve data services for SDGs in order to strengthen scientific research on monitoring and evaluating SDG indicators. We advocate for a scientific think tank that guides technological innovation for sustainable development and provides suggestions on education and training for developing countries that warrant serious consideration for rapid and meaningful sustained progress in the future. This paper highlights research on improving SDG monitoring and evaluation of SDGs carried out under the Big Earth Data Science Engineering Program of Chinese Academy of Sciences, the progress made in the development of the big data information platform for SDGs, and the monitoring and evaluation of SDG indicators. Further, the paper introduces the sustainable development scientific satellite due to launch in October 2021, a first of its kind in a series of satellites and the International Research Center of Big Data for Sustainable Development Goals (CBAS), which is being established to strengthen national and international efforts through improved scientific support driven by innovative big data solutions for SDGs.

First page

874

Last Page

884

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1 Meadows D H, Meadows D L, Randers J, et al. The Limits to Growth:A Report for the Club of Rome's Project on the Predicament of Mankind. New Haven:Universe Books, 1972.

2 WCED. Report of the World Commission on Environment and Development:Our Common Future. (1987-03-20)[2021-07-31]. http://www.un-documents.net/wced-ocf.htm.

3 UN. Millennium Development Goals. (2001-09-06)[2021-07-31]. https://www.un.org/millenniumgoals/. https://www.un.org/millenniumgoals/.

4 UN. Transforming Our World:The 2030 Agenda for Sustainable Development. (2015-09-02)[2021-07-20]. https://sdgs.un.org/2030agenda.

5 UN. The Sustainable Development Goals Report 2020. New York:United Nations, 2020.

6 IAEG-SDGS. Tier Classification for Global SDG Indicators. New York:Interagency andExpert Group on SDG Indicators, 2021.

7 Guo H D, Chen F, Sun Z C, et al. Big Earth Data:A practice of sustainability science to achieve the Sustainable Development Goals. Science Bulletin, 2021, 66(11):1050-1053.

8 Campbell J, Sahou J, Sebukeera C, et al. Measuring Progress:Towards Achieving the Environmental Dimension of the SDGs. Nairobi:United Nations Environment Programme, 2019.

9 Guo H D. Big Earth Data in Support of the Sustainable Development Goals. Beijing:Science Press, EDP Sciences, 2020.

10 Sachs J, Kroll C, Lafortune G, et al. The Decade of Action for the Sustainable Development Goals:Sustainable Development Report 2021. Cambridge:Cambridge University Press, 2021.

11 ElMassah S, Mohieldin M. Digital transformation and localizing the sustainable development goals (SDGs). Ecological Economics, 2020, 169:106490.

12 Nature Editorial. Time to revise the Sustainable Development Goals. Nature, 2020, 583:331-332.

13 Gandomi A, Haider M. Beyond the hype:Big data concepts, methods, and analytics. International Journal of Information Management, 2015, 35(2):137-144.

14 Guo H D, Wang L Z, Liang D. Big Earth Data from space:A new engine for Earth science. Science Bulletin, 2016, 61(7):505-513.

15 Guo H D. Big Earth data:A new frontier in Earth and information sciences. Big Earth Data, 2017, 1(1/2):4-20.

16 Ferreira B, Iten M, Silva R G. Monitoring sustainable development by means of earth observation data and machine learning:A review. Environmental Sciences Europe, 2020, 32:120.

17 Runting R K, Phinn S, Xie Z Y, et al. Opportunities for big data in conservation and sustainability. Nature Communications, 2020, 11:2003. 18 Allen C, Smith M, Rabiee M, et al. A review of scientific advancements in datasets derived from big data for monitoring the Sustainable Development Goals. Sustainability Science, 2021, 16(5):1701-1716.

19 Guo H D, Nativi S, Liang D, et al. Big Earth Data science:An information framework for a sustainable planet. International Journal of Digital Earth, 2020, 13(7):743-767.

20 郭华东. 地球大数据支撑可持续发展目标报告(2019). 北京:科学出版社, 2019.

21 Messerli P, Murniningtyas E. Global Sustainable Development Report 2019:The Future is Now-Science for Achieving Sustainable Development. New York:United Nations, 2019.

22 Zuo L J, Zhang Z X, Carlson K M, et al. Progress towards sustainable intensification in China challenged by land-use change. Nature Sustainability, 2018, 1(6):304-313.

23 Cheng Z F, Wang J H, Ge Y. Mapping monthly population distribution and variation at 1-km resolution across China. International Journal of Geographical Information Science, 2020, doi:10.1080/13658816.2020.1854767.

24 Sun Z C, Xu R, Du W J, et al. High-resolution urban land mapping in China from Sentinel 1A/2 imagery based on Google Earth Engine. Remote Sensing, 2019, 11(7):752. 25 Jiang H, Sun Z, Guo H, et al. A standardized dataset of builtup areas of China's cities with populations over 300,000 for the period 1990-2015. Big Earth Data, 2021, doi:10.1080/20964471.2021.1950351.

26 Jiang H P, Sun Z C, Guo H D, et al. An assessment of urbanization sustainability in China between 1990 and 2015 using land use efficiency indicators. npj Urban Sustainability, 2021, 1:34.

27 Wang S L, Li J S, Zhang W Z, et al. A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000-2018. Scientific Data, 2021, 8:26.

28 Zhang Y, Wang C Y, Ji Y, et al. Combining segmentation network and nonsubsampled contourlet transform for automatic marine raft aquaculture area extraction from Sentinel-1 images. Remote Sensing, 2020, 12(24):4182.

29 Guo H D. Steps to the Digital Silk Road. Nature, 2018, 554:25-27.

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