Related items
Showing items related by metadata.
-
ArticleUsing Standardized Time Series Land Cover Maps to Monitor the SDG Indicator “Mountain Green Cover Index” and Assess Its Sensitivity to Vegetation Dynamics 2021
Also available in:
No results found.SDG indicators are instrumental for the monitoring of countries’ progress towards sustainability goals as set out by the UN Agenda 2030. Earth observation data can facilitate such monitoring and reporting processes, thanks to their intrinsic characteristics of spatial extensive coverage, high spatial, spectral, and temporal resolution, and low costs. EO data can hence be used to regularly assess specific SDG indicators over very large areas, and to extract statistics at any given subnational level. The Food and Agriculture Organization of the United Nations (FAO) is the custodian agency for 21 out of the 231 SDG indicators. To fulfill this responsibility, it has invested in EO data from the outset, among others, by developing a new SDG indicator directly monitored with EO data: SDG indicator 15.4.2, the Mountain Green Cover Index (MGCI), for which the FAO produced initial baseline estimates in 2017. The MGCI is a very important indicator, allowing the monitoring of the health of mountain ecosystems. The initial FAO methodology involved visual interpretation of land cover types at sample locations defined by a global regular grid that was superimposed on satellite images. While this solution allowed the FAO to establish a first global MGCI baseline and produce MGCI estimates for the large majority of countries, several reporting countries raised concerns regarding: (i) the objectivity of the method; (ii) the difficulty in validating FAO estimates; (iii) the limited involvement of countries in estimating the MGCI; and (iv) the indicator’s limited capacity to account for forest encroachment due to agricultural expansion as well as the undesired expansion of green vegetation in mountain areas, resulting from the effect of global warming. To address such concerns, in 2020, the FAO introduced a new data collection approach that directly measures the indicator through a quantitative analysis of standardized land cover maps (European Space Agency Climate Change Initiative Land Cover maps—ESA CCI-LC). In so doing, this new approach addresses the first three of the four issues, while it also provides stronger grounds to develop a solution for the fourth issue—a solution that the FAO plans to present to the Interagency and Expert Group on SDG Indicators (IAEG-SDG) at its autumn 2021 session. -
Brochure, flyer, fact-sheetSupporting Sustainable Development Goal SDG 2.1 Monitoring by Strengthening Food Security and Nutrition Information in Africa GCP/GLO/943/JP
Improving data collection and analysis to monitor progress towards the SDG targets using robust, statistically sound indicators for food and nutrition security
2022Also available in:
No results found.As African countries race against time to end hunger by 2030, improved country data is critical in tracking progress toward achieving Sustainable Development Goals 2 on zero hunger, nutrition and promote sustainable agriculture. The indicators used to monitor progress towards achievement of SDG 2 is the Prevalence of Undernourishment (PoU) and the Prevalence of moderate and severe food insecurity based on the Food Insecurity Experience Scale (FIES). However, the quality of data produced by countries that is necessary to produce these indicators has historically been limited. FAO is enhancing national capacities to collect, analyze and monitor data on food and nutrition security using standardized tools that are internationally comparable to guide policies to end hunger and malnutrition. -
No Thumbnail AvailableBook (stand-alone)Land quality indicators and their use in sustainable agriculture and rural development 1997
Also available in:
Users also downloaded
Showing related downloaded files
No results found.