The Mountain Green Cover Index (MGCI) is designed to measure the extent and the changes of green vegetation in mountain areas - i.e. forest, shrubs, trees, pasture land, crop land, etc. – in order to monitor progress towards the mountain target. MGCI is defined as the percentage of green cover over the total surface of the mountain region of a given country and for given reporting year. The aim of the index is to monitor the evolution of the green cover and thus assess the status of conservation of mountain ecosystems.
Please see the full metadata here for further information about the indicator.
The purpose of this document is explain the workflow and provide countries with detailed technical guidance on how to develop a nationally relevant mountain layer using the Kapos mountain method, use a nationally relevant landcover map and compute the MGCI to standard reporting tables required for the submission to FAO for this indicator. and as well as providing some best practice in combining layers at different resolutions. The standardisation of the guidance will also help enable consistency of reporting between countries and enable FAO to make the necessary regional and global summaries.
The workflow and guidance are provided to enable users to choose from 3 different software:
- Step-by-Step instructions in QGIS (with R integration)
- Step-by-Step instruction in R (plus and R-Script)
- SEPAL app: Users can register and log into the SEPAL data portal where a user-friendly interface will guide
- technicians through a series of menu-driven steps to prepare the mountain and vegetation descriptor layers before running the MGCI calculations. Users will be given the choice to upload their own data or choose from data already uploaded to the tool. The MGCI will be computed and outputs formatted to standard reporting tables.
Figure X: Simplified Workflow
Mountains can be defined with reference to a variety of parameters, such as climate, elevation, ecology (Körner, Paulsen, & Spehn, 2011) (Karagulle, et al., 2017). This methodology adheres to the UNEP- WCMC mountain definition, relying in turn on the mountain description proposed by (Kapos, Rhind, Edwards, Prince, & Ravilious, 2000). This description classifies mountains according to altitude, slope and elevation range into 6 categories.
| Mountain Class | Description |
|---|---|
| 1 | Elevation > 4.500 meters |
| 2 | Elevation 3.500–4.500 meters |
| 3 | Elevation 2.500–3.500 meters |
| 4 | Elevation 1.500–2.500 meters and slope > 2 |
| 5 | Elevation 1.000–1.500 meters and slope > 5 or local elevation range (LER 7 kilometer radius) > 300 meters |
| 6 | Elevation 300–1.000 meters and local elevation range (7 kilometer radius) > 300 meters |
Please note that (as per the methodology description in Kapos et. al. 2000), Inner isolated areas (<=25km2 in size) that don't meet criteria but are surrounded by mountains are identified and merged into whichever class they are surrounded by.
The vegetation descriptor layer categorizes land cover into green and non-green areas. Green vegetation includes both natural vegetation and vegetation resulting from anthropic activity (e.g. crops, afforestation, etc.). Non-green areas include very sparsely vegetated areas, bare land, water, permanent ice/snow and urban areas. The vegetation description layer can be derived in different ways, but remote sensing based land cover maps are the most convenient data source for this purpose, as they provide the required information on green and non-green areas in a spatially explicit manner and allow for comparison over time through land cover change analysis. Currently, FAO uses land cover time series produced by the European Space Agency (ESA) under the Climate Change Initiative (CCI) as a general solution. The original CCI classes are re-classified into six IPCC classes and further into binary green/non-green cover classes as follows:
| ESA CCI class | IPCC class | Green / Non green |
|---|---|---|
| 50, 60, 61, 62, 70, 71, 72, 80, 81, 82, 90, 100 | Forest1 | Green |
| 110, 120, 121, 122, 130, 140, | Grassland | Green |
| 10,11, 12, 20, 30, 40 | Cropland | Green |
| 160, 170, 180 | Wetland | Non Green |
| 190 | Settlement | Non Green |
| 150, 151, 152, 153, 200, 201, 202, 210, 220 | Other land | Non Green |
1 Please note, that here the term “Forest” refers to land cover, not necessarily land use
To improve the accuracy of the mountain green cover index calculation a decision has been made by FAO to calculate area using the standard planimetric area and an additional real surface area. The real surface area takes into account the third dimension of mountain surfaces (Jenness 2004), giving a better and more accurate estimate of the true mountain area in a country (Bian et al., 2020). For the purposes of the MGCI, elevation data is used to calculate the real surface area following the triangulation method developed by Jenness (2004).
The results of the MGCI are output to standard reporting tables in tables using the following fields:
Three levels of reporting are required
- Aggregated mountain green cover Index by Kapos mountain class
- Area of mountain and area of green cover area within each Kapos
- mountain class
- Area of mountain and green cover within each LULC class area and
- Kapos mountain class
The indicator can be calculated using freely available Earth Observation data and simple GIS operations that can be processed in free and open source software (FOSS) GIS. Potential limitations of the above described methodology are related mainly to the quality of the land cover data. The ESA CCI land cover maps are currently available at 300 meter resolution which limits their applicability in the monitoring of small and highly heterogeneous landscapes. Therefore, if countries have national land cover maps of higher spatial resolution and comparable or better quality, FAO advises using them, following the same methodology presented here, for the generation of MGCI values.
Regarding the interpretation of the indicator, although in the great majority of cases the desired direction is an increase in green mountain cover which reflects restriction of damage to natural ecosystems and possibly even the expansion of forest, shrubland and grasslands through conservation efforts, in more limited cases, an increase in the indicator value in high elevation classes may also signify the encroachment of vegetation on areas previously covered by glaciers or other permanent or semi-permanent ice or snow layers, as a result of global warming due to climate change. Such a change can be tracked with the current methodology and flagged accordingly at the level of disaggregated data by land cover type and elevation class, to distinguish this case from the general desired trend of increasing mountain green cover.