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ArticleUsing Standardized Time Series Land Cover Maps to Monitor the SDG Indicator “Mountain Green Cover Index” and Assess Its Sensitivity to Vegetation Dynamics 2021
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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-sheetUsing land-cover information to monitor progress on Sustainable Development Goal 15 2024
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No results found.This course seeks to provide a basic understanding of land-cover data and its use for monitoring progress towards the achievement of international agreed goals, such as Sustainable Development Goal (SDG) 15, with a practical focus on its Indicators 15.3.1 (proportion of land that is degraded over total land area) and 15.4.2 (including its subindicators: mountain green cover Index and proportion of degraded mountain land). -
Book (series)Standardizing land cover mapping for tsetse and trypanosomiasis decision making 2008
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No results found.The habitat of tsetse fly (Glossina spp.) depends upon climatic conditions, host availability and land cover characteristics. In this paper, the Land Cover Classification System (LCCS), developed by the Food and Agriculture Organization (FAO) and the United Nations Environment Programme (UNEP), is proposed as a tool to harmonize land cover mapping exercises carried out in the context of tsetse and trypanosomiasis (T&T) research and control. Habitat modifications are increasingly indu ced by human actions, either at a global scale, as in the case of climatic change, or at a local scale, as in the processes of urbanization and agricultural expansion. The challenges posed in the future by trypanosomiasis are likely to be shaped by those factors to the extent that no appropriate intervention can possibly be contemplated without considering them.
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