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Global oil palm map

Cite this dataset

Meijaard, Erik; Gaveau, David (2021). Global oil palm map [Dataset]. Dryad.


This report has been written by the IUCN Oil Palm Task Force in response to IUCN Resolution WCC-2016-Res-061-EN requesting “a situation analysis of the implications for biodiversity conservation from the expansion of oil palm, and to review and define best practices in the industry”. The Situation Analysis primarily focuses on oil palm in the context of biodiversity conservation based on literature published before 31 January 2018, and aims to provide a more constructive pathway to addressing sustainability challenges in the palm oil industry. A draft version of this report was reviewed by 43 external reviewers from non-governmental organizations, academic institutions and people working in the palm oil industry, who provided some 600 comments that were then incorporated into a revised version.

This report does not assess the social and economic implications of palm oil production and expansion but will refer to these when they are likely to have an impact on biodiversity conservation. Through identification of key knowledge gaps, the Situation Analysis will also provide direction to the Oil Palm Task Force in terms of seeking to address these knowledge gaps in the remainder of the 2017-2020 Quadrennium.


We developed a map showing the global extent of industrial oil palm plantations following a three-steps procedure. First, we identified the top 29 palm oil producer countries based on FAO statistics of harvested area. Second, we carried out a literature review of published studies that have mapped industrial oil palm plantations, and compiled this information into a Geographic Information System. Third, we complemented this analysis for 13 countries, where no maps were available. For these thirteen countries, we delineated the boundaries of industrial using cloud-free LANDSAT mosaics acquired in 2017, created in Google Earth Engine.  

We declared an area planted (the land is either already planted or under development), the moment we observed large rectangular elements, long linear boundaries, and distinctive grid- or contour-planting patterns appear on our images. These planting patterns characterize industrial plantations. They are easily detected by the human eye, but are difficult to capture with computer codes. Therefore, we delineated the boundaries of the planted areas (or under development) using a visual, expert-based interpretation method. We also employed maps of oil-palm concessions that have entered the public sphere to distinguish young oil-palm from other types of industrial plantations.


Global Environment Facility, Award: IUCN project ‘Global Commons: Solutions for a Crowded Planet’