Intact Forest Landscapes

An Intact Forest Landscape (IFL) is an unbroken expanse of natural ecosystems within the zone of current forest extent, showing no signs of significant human activity, and large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained.

The IFL concept and its technical definition were introduced to help create, implement, and monitor policies concerning the forest degradation at the regional-to-global levels. The essence of the IFL method is to use freely available medium spatial resolution satellite imagery to establish the boundaries of large undeveloped forest areas, so called Intact Forest Landscapes (IFL), and to use these boundaries as a baseline for forest degradation monitoring. Developed by a group of non-governmental environmental organizations (Greenpeace, World Resources Institute, and Transparent World), the IFL concept, mapping and monitoring algorithms have been used both in regional and global forest monitoring projects and in scientific research. The IFL method could be used for fast and cost-effective assessment and monitoring of forest degradation in the context of REDD+ initiative.

The first global IFL map was prepared in 2005-2006 under the leadership of Greenpeace, with contributions from: Biodiversity Conservation Center, International Socio-Ecological Union, and Transparent World (Russia), Luonto Liitto (Finnish Nature League), Forest Watch Indonesia, and Global Forest Watch, a network initiated by the World Resources Institute. The map showed IFL extent for year 2000 and enabled measuring of forest degradation (understood as a reduction in ecological integrity across a forest landscape) at the global, biome and national levels.

The global IFL map update was performed in 2014 by Greenpeace, The University of Maryland and Transparent World, with support from the World Resources Institute and WWF Russia. The new analysis shows extent of IFL by the end of year 2013, and their degradation since year 2000. The IFL map update based on the same data source and methodology as year 2000 mapping to ensure globally consistent dataset. The 13-years monitoring results revealed the alarming speed at which the world’s intact forests are being degraded. These results were confirmed by regional studies in Indonesia, Democratic Republic of the Congo, and elsewhere (see Publications).

The significance of the IFL analysis method and map lies in its power to enable and catalyze practical conservation planning and action with regard to large undeveloped forest landscapes. Protection of large natural forest landscapes is a highly important task to help fulfill different international strategic initiatives to protect forest biodiversity (CBD), to reduce carbon emissions from deforestation and forest degradation (IGBP, REDD) and to stimulate sustainable forestry management practice use (FSC). Mapping, conservation and monitoring of Intact Forest Landscapes is a therefore a task of great global significance.

All up-to-date IFL maps and IFL monitoring results are available online on this website in formats suitable for use in professional GIS as well as in freeware GIS browsers. The IFL map can be viewed on-line on our website as well as on Global Forest Watch platform and on the Global Forest Change web-map supported by the Google Earth Engine. On the Global Forest Change map you may overlay IFL with the 2014 forest cover loss dataset to identify recent changes, and with year 2000 forest cover to separate forest and non-forest ecosystems within IFL areas. The IFL Mapping Team is deeply grateful to Global Forest Watch and Google Earth Engine teams for their support with IFL visualization.

The IFL Mapping Team is continuing to improve the IFL base map and to provide periodically updates as new data, technologies, and more sophisticated sources of information appears. Please check News & Updates for information about the latest map release.

News & Updates

IFL 2000 and 2013 are available for download.
IFL on Google Earth Engine.

Mapping Team

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