Developing good practice guidance for estimating land degradation in the context of the United Nations Sustainable Development Goals. Issue 92 (February 2019)

• Record Type: Journal Article
• Authors: Sims, Neil C.; England, Jacqueline R.; Newnham, Glenn J.; Alexander, Sasha; Green, Carly; Minelli, Sara; Held, Alex
• Is Part Of: Environmental science & policy. Issue 92(2019)
• Page Start: 349
• Page End: 355
• Publication Date: 2019-02
• Subjects: Land degradation neutrality -- Land use change -- Land productivity -- Carbon stocks -- Earth observation -- 2030 agenda for sustainable development; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2018.10.014
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: Degradation is identified by changes in land cover, productivity and soil organic C. A one-out-all-out method combines sub-indicators to calculate the Indicator. Aggregation using other spatial data can increase relevance to national policies. These methods underpin initiatives and tools to assess LDN and SDG Indicator 15.3.1. Abstract: In recent decades there have been numerous global and regional targets and initiatives to halt and reverse land degradation. The land degradation neutrality (LDN) target, embedded in the United Nations Sustainable Development Goals (SDGs), provides a framework for countries to avoid or reduce degradation through sustainable land management, coupled with efforts to restore or rehabilitate degraded land. Here we present the key recommendations from the Good Practice Guidance (GPG) for monitoring and reporting on SDG indicator 15.3.1 ("proportion of land that is degraded over total land area") and discuss how it could be used in the context of implementing the LDN target. SDG indicator 15.3.1 is assessed in terms of change in three sub-indicators: land cover, land productivity and carbon stocks. Each of these sub-indicators represents a unique perspective on the manifestation and assessment of land degradation. Global time-series datasets are a valuable recent development for monitoring landscape-scale changes, but variations in land conditions between countries, and differences in the sensitivities of these time-series datasets, present challenges in the selection of the most appropriate methods and datasets. Methods to combine the three sub-indicators for SDG indicator 15.3.1 need to account for variations in conditions over space and time, and potential differences in the representation of degradation among the sub-indicators and between countries. Without being prescriptive about the sources of data, the GPG aims to ensure technical soundness and consistency in estimation methods as well as comparability of results across countries and over time. The information provided by the three sub-indicators will assist countries to better understand their distribution and types of land degradation, and support countries to achieve their LDN targets. This paper presents some of the key methodological details of the GPG and describes how they can be used in the context of LDN implementation.