Harnessing Big Earth Data to Facilitate Land Degradation Neutrality Goals—Practices and Prospects

Authors

Xiaosong LI, International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaFollow
Qi LU, Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China Experimental Center of Desert Forestry, Chinese Academy of Forestry, Bayannur 015200, China
Xiaoxia JIA, United Nations Convention to Combat Desertification, Bonn 57173, Germany

Keywords

land degradation neutrality (LDN), Big Earth Data, reference baseline, progress monitoring

Document Type

Strategy & Practice

Abstract

In 2015, the United Nations adopted the Transforming Our World:The 2030 Agenda for Sustainable Development, in which land degradation neutrality (LDN) is one of the important targets of the Sustainable Development Goal (SDG 15.3). However, due to varies indicative symptoms of land degradation in different climatic/geographical zones and land use types, the complexity of factors affecting land degradation or improvement, and the limits of spatial and temporal scope to define land degradation, for a long time, there was lack of common accepted methodology to identify land degradation, and short of key data set to establish reference baselines, and measure progress of SDG 15.3, which hinders the realization of SDG 15.3 by 2030. As a typical representative of a data-intensive scientific paradigm, Big Earth Data provides the possibility to solve this data gap. Focusing on two important aspects of SDG 15.3 reporting, namely baseline determination and progress monitoring, this article introduces the key challenges we faced, the potential of Big Earth Data and the practices we have taken. Finally, the prospects for harnessing Big Earth Data to facilitate SDG 15.3 in the future are outlined.

First page

896

Last Page

903

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1 Lal R, Safriel U, Boer B. Zero Net Land Degradation:A New Sustainable Development Goal for Rio+20. Bonn:United Nations Convention to Combat Desertification, 2012.

2 Safriel U. Land Degradation Neutrality (LDN) in drylands and beyond-Where has it come from and where does it go. Silva Fennica, 2017, 51(1B):20-24.

3 Akhtar-Schuster M, Stringer L C, Erlewein A, et al. Unpacking the concept of land degradation neutrality and addressing its operation through the Rio Conventions. Journal of Environmental Management, 2017, 195:4-15.

4 Cowie A L, Orr B J, Sanchez V M C, et al. Land in balance:The scientific conceptual framework for land degradation neutrality. Environmental Science & Policy, 2018, 79:25-35.

5 Gibbs H K, Salmon J M. Mapping the world's degraded lands. Applied geography, 2015, 57:12-21.

6 Diouf A, Lambin E F. Monitoring land-cover changes in semi-arid regions:Remote sensing data and field observations in the Ferlo, Senegal. Journal of Arid Environments, 2001, 48(2):129-148.

7 Briske D D, Fuhlendorf S D, Smeins F E. Vegetation dynamics on rangelands:A critique of the current paradigms. Journal of Applied Ecology, 2003:40(4):601-614.

8 Bai Z G, Dent D L, Olsson L, et al. Proxy global assessment of land degradation. Soil Use and Management, 2008, 24(3):223-234.

9 Fensholt R, Rasmussen K, Nielsen T T, et al. Evaluation of earth observation based long term vegetation trends-Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data. Remote Sensing of Environment, 2009, 113(9):1886-1898.

10 Prince S D, de Colstoun E B, Kravitz L L. Evidence from rain-use efficiencies does not indicate extensive Sahelian desertification. Global Change Biology, 1998, 4(4):359-374.

11 Wessels K J, Prince S D, Malherbe J, et al. Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. Journal of Arid Environments, 2007, 68(2):271-297.

12 del Barrio G, Puigdefabregas J, Sanjuan M E, et al. Assessment and monitoring of land condition in the Iberian Peninsula, 1989-2000. Remote Sensing of Environment, 2010, 114(8):1817-1832.

13 郭华东. 地球大数据科学工程. 中国科学院院刊, 2018, 33(8):818-824.

14 郭华东, 梁栋, 陈方, 等. 地球大数据促进联合国可持续发展目标实现. 中国科学院院刊, 2021, 36(8):874-884.

15 Prince S D. Challenges for remote sensing of the Sustainable Development Goal SDG 15.3.1 productivity indicator. Remote Sensing of Environment, 2019, 234:111428.

16 Guo H D. Big Earth Data in Support of the Sustainable Develop ment Goals (2019). Beijing:Sciences Press, 2021.

17 邵京, 李晓松, 杨珺婷, 等. 光学与雷达遥感协同的大尺度草地灌丛化监测研究. 干旱区资源与环境, 2021, 35(2):130-135.

18 Yang J T, Li X S, Wang B, et al. High spatial resolution topsoil organic matter content mapping across desertified land in northern China. Frontiers of Environmental Science & Engineering, 2021, 9:668912.

Recommended Citation

LI, Xiaosong; LU, Qi; and JIA, Xiaoxia (2021) "Harnessing Big Earth Data to Facilitate Land Degradation Neutrality Goals—Practices and Prospects," Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 36 : Iss. 8 , Article 4.
DOI: https://doi.org/10.16418/j.issn.1000-3045.20210705002
Available at: https://bulletinofcas.researchcommons.org/journal/vol36/iss8/4