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标题：Mapping the World’s Intact Forest Landscapes by Remote Sensing
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作者：Peter Potapov ; Aleksey Yaroshenko ; Svetlana Turubanova 等
期刊名称：Ecology and Society
印刷版ISSN：1708-3087
电子版ISSN：1708-3087
出版年度：2008
卷号：13
期号：2
出版社：The Resilience Alliance
摘要：Protection of large natural forest landscapes is a highly important task to help fulfill different international strategic initiatives to protect forest biodiversity, to reduce carbon emissions from deforestation and forest degradation, and to stimulate sustainable forest management practices. This paper introduces a new approach for mapping large intact forest landscapes (IFL), defined as an unbroken expanse of natural ecosystems within areas of current forest extent, without signs of significant human activity, and having an area of at least 500 km2. We have created a global IFL map using existing fine-scale maps and a global coverage of high spatial resolution satellite imagery. We estimate the global area of IFL within the current extent of forest ecosystems (forest zone) to be 13.1 million km2 or 23.5% of the forest zone. The vast majority of IFL are found in two biomes: Dense Tropical and Subtropical Forests (45.3%) and Boreal Forests (43.8%). The lowest proportion of IFL is found in Temperate Broadleaf and Mixed Forests. The IFL exist in 66 of the 149 countries that together make up the forest zone. Three of them—Canada, Russia, and Brazil—contain 63.8% of the total IFL area. Of the world’s IFL area, 18.9% has some form of protection, but only 9.7% is strictly protected, i.e., belongs to IUCN protected areas categories I–III. The world IFL map presented here is intended to underpin the development of a general strategy for nature conservation at the global and regional scales. It also defines a baseline for monitoring deforestation and forest degradation that is well suited for use with operational and cost-effective satellite data. All project results and IFL maps are available on a dedicated web site (http://www.intactforests.org).
关键词：Forest degradation; Global forest assessment; Intactness; Landsat; Remote sensing; Wilderness