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 ...

Palm Oil fell to 4,251 MYR/T on August 1, 2025, down 0.61% from the previous day. Over the past month, Palm Oil's price has risen 4.63%, and is up 8.53% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Palm Oil - values, historical data, forecasts and news - updated on August of 2025.

This data set shows Roundtable on Sustainable Palm Oil (RSPO)-certified grower supply bases in Indonesia, though supply bases digitized by the RSPO are not available for download. A supply base consists of all lands that produce or support the production of palm oil processed at an RSPO-certified mill, and may include planted palm, nurseries, riparian buffers, HCV set-asides, palm oil mills and supporting infrastructure, certified smallholder oil palm lands, and roads. The data providers first compiled a list of all grower and group certifications conferred by the RSPO. As of March 30, 2017, about 400 palm oil mills and 20 smallholders’ groups had been certified by the RSPO globally. Polygons were digitized from maps available from audit reports hosted on the RSPO website, supplemented by spatial data on plantation boundaries provided by companies as part of the 2014 RSPO Annual Communication of Parties (ACOP), as well as plantations identified from Greenpeace and Sawit Watch concession data sets. Ancillary information was collected from audit reports including the dates of RSPO certification and letters of intent notifying stakeholders of the intent to pursue RSPO certification. The data were subset to plantations within Indonesia.

The dataset contains 634 100x100 km tiles, covering areas where oil palm plantations were detected. The file 'grid.shp' contains the grid that covers the potential distribution of oil palm. The file 'grid_withOP.shp' shows the 100x100 grid squares with presence of oil palm plantations. The classified images (‘oil_palm_map’ folder, in geotiff format) are the output of the convolutional neural network based on Sentinel-1 and Sentinel-2 half-year composites. The images have a spatial resolution of 10 meters and contain three classes: [1] Industrial closed-canopy oil palm plantations, [2] Smallholder closed-canopy oil palm plantations, and [3] other land covers/uses that are not closed canopy oil palm. The file ‘Validation_points_GlobalOilPalmLayer_2019.shp’ includes the 13,495 points that were used to validate the product. Each point includes the attribute ‘Class’, which is the labelled class assigned by visual interpretation, and the attribute ‘predClass, which reflects the predicted class by the convolutional neural network. The ‘Class’ and ‘predClass’ values are the same as the raster files: [1] Industrial closed-canopy oil palm plantations, [2] Smallholder closed-canopy oil palm plantations, and [3] other land covers/uses that are not closed canopy oil palm.

See article for additional information:

Descals, Adrià, et al. "High-resolution global map of smallholder and industrial closed-canopy oil palm plantations." Earth System Science Data 13.3 (2021): 1211-1231.

Changelog v1:

- The analysis was extended to Sri Lanka, South India, and countries in Eastern Africa where oil palm can potentially grow.

- The validation dataset only includes the points drawn by simple random sampling and stratified random sampling in the grid cells where the IUCN industrial layer detected oil palm.

- The 'Class' and 'predClass' values in the validation dataset were reclassified with the same values as the raster images: [1] Industrial plantations, [2] Smallholder plantations, and [3] Other land covers/uses.

A story map to show that were palm oil production is increasing, the deforestation Rate is also increasingData source: FAO

Indonesia Exports of palm oil and its fractions, not chemically modified to India was US$4.52 Billion during 2023, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to India - data, historical chart and statistics - was last updated on August of 2025.

Conservationists lament the loss of rainforests in Borneo, and charge plantation companies for their destruction. Those on the plantation side argue that planting is done on already deforested land. This study reveals that the plantation industry is the principle driver of the loss of old-growth forest in Malaysian Borneo. In Indonesian Borneo (Kalimantan), considerably more oil palm has been developed on already deforested lands. This is what the conservation community has promoted for decades. Development on degraded lands is a cornerstone of sustainable palm oil development, compatible with certification schemes and with recent zero-deforestation pledges. Seen from that perspective, Indonesia seems to have done much better than Malaysia, than has been widely assumed – though since 2005 the sharp increase in oil-palm driven deforestation gives little room for complacency. Despite planting on degraded lands, deforestation remains very high in Borneo, and does not appear to be slowing. This atlas helps distinguish plantation companies who practiced deforestation from those who avoided it, for more effective oversight of certification bodies and governments, and to allow companies that are doing the right thing, avoid the bad reputation of those who actually deserve it.View the extent of the forest area in 1973, before extractive industries beganView forty-two years (1973-2015) of forest degradation by the logging industry, and conversion to industrial oil palm and pulpwood plantationsTrack the history of the type of vegetation present before plantations became establishedDetermine the area of forest currently remaining in concessions of oil palm and pulpwood Determine the area developed by companies in concessionsDetermine the total area of forest that has been cleared since 1973 in concessionsDetermine the area of forest that has been actively cleared by companies to develop plantations in concessions (company-driven deforestation)Determine the area of non-forest that has been developed into plantation (avoided deforestation)For more information on results, methods, definitions and caveats, readers should consult this scientific publication: Gaveau et al. (2016) Rapid conversions and avoided deforestation: examining four decades of industrial plantation expansion in Borneo. Scientific Reports (2016)

Under the GCRF Trade, Development and the Environment Hub (TRADE Hub), the author conducted big data and media analysis to identify relevant actors and analyze their social network, as well as power constellation on the palm oil, coffee, and wildlife trade in Indonesia. This study important is to improve governance towards sustainable trade of palm oil, coffee, and wildlife trade. Interactive actors’ map is provided using KUMU platform (https://kumu.io).

Afghanistan Imports of palm oil and its fractions, not chemically modified from Ukraine was US$189.85 Thousand during 2019, according to the United Nations COMTRADE database on international trade. Afghanistan Imports of palm oil and its fractions, not chemically modified from Ukraine - data, historical chart and statistics - was last updated on August of 2025.

A new initiative from the World Resources Institute (WRI) and the Roundtable on Sustainable Palm Oil (RSPO) aims to shed light on how individual oil palm concessions affect forest information that can empower companies to manage their forests and supply chains more sustainably. Global Forest Watch-Commodities (GFW-Commodities), a new platform produced by Blue Raster combines the RSPO’s maps of certified sustainable palm oil production sites with global forest data like tree cover loss, forest clearance, locations of primary forests and legal land classifications. Armed with these new maps and knowledge, companies can reduce the risk that the palm oil they purchase contributes to deforestation.WRI analysis has shown that companies, communities, NGOs and different levels of government often have different information about forest use. These maps will act as a universally available, coherent and current source of information for any of these above groups to utilize in their work to make palm oil production sustainable for the environment and the communities that rely on it.GFW-Commodities was built on Esri’s ArcGIS Server and ArcGIS API for JavaScript. It leverages the Image Extension for ArcGIS Server, to compute, analyze and provide statistics on tree cover loss over time, near real time forest clearing and fires within selected areas of interest. The analysis features come out-of-the-box with Esri’s Image Extension for ArcGIS Server. Satellite data including Landsat and MODIS are mosaiced and allow for analysis on-the-fly as users explore their areas of interest. The Global Forest Watch platform is at the forefront in its field and will continue to grow and evolve with its use, applying technology for a sustainable world. Read more about the project and WRI’s efforts towards sustainability in Wired magazine – “How a New Map of Palm Oil Plantations Could Help Save Rainforests.”

DescriptionPalm oil mills: The data comes from FoodReg’s Known Sources palm oil mill database and directly from palm oil traders and buyers. The data represents the mills within the supply chain of at least three major palm oil buyers who wish to remain anonymous. The data does not represent the entire universe of mills, and is only representative of the mills within the supply chains of companies submitting mill data to WRI or Known Sources. The location of mills was self-reported by mill owners. All mill locations were manually verified by WRI using Google Earth imagery according to criteria for mill infrastructure including the presence of buildings, settling ponds, and nearby palm oil plantations. Mills may have duplicate names when site-level name data is missing and group name information is included. The data will be updated as new data becomes available to WRI or Known Sources.Oil palm concessions (select countries): refers to an area allocated by a government or other body for industrial-scale oil palm plantations.The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations. Includes:Liberia oil palm concessions: refers to an area allocated by a government or other body for industrial-scale oil palm plantations.The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources.Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations. This data set provides the boundaries of known oil palm plantations for Liberia and was compiled by Global Witness from available government maps. Information provided with this data set includes company, ownership group, and land area.Cameroon agro-industrial zones: This data layer shows the boundaries of agro-industrial zones, where oil palm and rubber tree plantations, as well as other crops, may be established. In Cameroon, industrial agriculture falls outside of the National Forest Estate. Agricultural plantations are allocated by the Ministry of Economy and Planning to private entities under long-term, renewable contracts, which are then monitored by the Ministry of Agriculture. The agro-industrial data set was mapped using satellite imagery, with ground-truthing to determine the crop type and operating company. Official documentation was often lacking, so boundaries should be considered approximate and nonexhaustive.Republic of the Congo oil palm concessions: This data set provides the boundaries for oil palm plantations according to the Republic of the Congo Ministry of Agriculture. Indonesia oil palm concessions: Oil palm concession refers to an area allocated by a government or other body for industrial-scale oil palm plantations. The oil palm concession data on GFW, while displayed as a single layer, is assembled on a country-by-country basis from multiple sources. Oil palm concession data displayed on the GFW website vary from country to country by date and data sources. Data may come from government agencies, NGOs, or other organizations.This data set, produced by the Indonesia Ministry of Forestry, provides the boundaries of current or planned oil palm plantations in Indonesia. This data set is known to be incomplete, but it is currently the best available. RSPO palm oil mills: this data layer displays plantation management units (PMU) certified under RSPO through May, 2013. These data are arranged by company group holding the majority shareholding in each unit.RSPO oil palm concessions (Brazil, Indonesia, Cambodia, Malaysia, Papua New Guinea and Thailand): The RSPO concession boundaries were produced by member companies and compiled by Aidenvironment.org. Other data is included from Annual Surveillance Assessments provided by the RSPO as well as third-party audit reports screened by Aidenvironment.org. SPOTT featured company concessions: SPOTT-Sustainability Policy Transparency Toolkit is an online platform supporting sustainable commodity production and trade. This database summarizes some assessments of palm oil producers and traders in relation to its operations and commitments related to environmental, social and governance (ESG) issues. RTRS Guides for Responsible Soy Expansion: The Round Table on Responsible Soy (RTRS) is a civil society organization that promotes the production, processing and marketing of responsible soy globally. It aims to promote sustainable production to reduce the social and environmental impacts of soybeans. The RTRS Responsible Soy Production Map is created based on RTRS Standards, and is intended to guide responsible expansion of soybean production for RTRS certification. The RTRS committed to create macro-scale maps for Argentina, Brazil, Bolivia, and Paraguay to identify and preserve critical ecosystems and High Conservation Value Areas (HCVAs), as well as identify opportunities for responsible expansion of soy with low levels of environmental impact. The process began in Brazil in 2012, followed by Paraguay in 2013. Additional national level maps (e.g. Argentina) are in development. These national maps are created by RTRS National Technical Groups in each country, with experts representing all levels of the supply chain to interpret the global methodology at the national level. Each group was led by local coordinators and supported by GIS companies and consultative groups, as well as BACP (IFC), IDH, 3Fi, WWF and The Gordon and Betty Moore Foundation, the principal funders of this project. The guides were developed according to Annex 4: RTRS approach to responsible conversion, page 20, of the RTRS Production Standard. The macro-scale maps show the four different categories described in Guide 4 of the Standard, and the High Conservation Value Areas assessment guides for determination and management of HCVAs. Date of update and consistency on attributes might differ as the layer is a compilation of concession data from various countries and sources. LimitationsDate of update and consistency on attributes might differ as the layers are a compilation of data from various countries and sources. CreditsPalm Oil Mills, RSPO Palm Oil Mills and Oil Palm ConcessionsGlobal Forest Watch - Data may come from government agencies, NGOs or other organizations. Accessed through GFW portal http://data.globalforestwatch.org/datasetsSPOTT featured company concessions Zoological Society of London - using data provided by Global Forest Watch from the World Resources Institute (WRI). Accessed through GFW portal http://data.globalforestwatch.org/datasetsRSTRS Guides for Responsible Soy ExpansionRound Table on Responsible Soy (RTRS). Accessed through GFW portal http://data.globalforestwatch.org/datasetsAttributesPalm Oil Millsobjectid: Assigned by WWF. Unique identifierwri_id: World Resources Institute identifiermill_name_: Name of the assetgroup_name: Name of the company operating the palm oil milliso: ISO-Alpha 3 code for the country where the mill is located. Cross-reference herecertificat: Indicates if the mill has RSPO certificationcompany_na: Name of the company operating the millglobalid: Global Forest Watch identifierx: X location in the original coordinate system of the database (WGS 1984)y: Y location in the original coordinate system of the database (WGS 1984)Oil Palm ConcessionsOBJECTID: Assigned by WWF. Unique identifierCountry: Country where the oil palm concession is locatedName: Local name of the company operating in the concessionCompany: International name of the company operating in the concessionGroup: International name of the companySub Group: Regional name of the company if appliesGroup ID: Assigned by GFW. Identifier for the Group company. Concession Type: Type of permission associated to the concessionGIS Calculated Area (ha): Reported area of the concession in hectaresSource: Original source of the concession dataLast Update: Last update of the information in the original databaseGFW ID: Global Forest Watch identifierRSPO Palm Oil MillsOBJECTID: Assigned by WWF. Unique identifierlongitude: Longitude in the original coordinate system of the database (WGS 1984)audit_stat: State of the certification process (Initial, renewal)legal_radi: Indicates werther the palm oil mill is located within a radius of up to 10 km from the palm oil concessions (Yes: 1, No: 0)illegal_ra: Indicates werther the palm oil mill is located within a radius of up to 10 km from the palm oil concessions (Yes: 0 or 1, Any other number reflects the distance in km*100)radius_umdradius_for: Presumably an indicator of the distance from the mill to the forests in the area of influenceprimary_in: Presumably an indicator of the primary forest in the areaprimary_1: Presumably an indicator of the primary forest in the areacarbon_rad: Presumably an indicator of the amount of carbon storage in the ecosystems in the area of influence (forest, peatlands, etcetera) peat_radiu: Presumably an indicator of the distance from the mill to peat lands in the area of influence peat_area_: Presumably an indicator of the area of the peatlands in the area of influencefires_radi: Presumably an indicator of the distance within the mill and identified fires in the area of influenceillegal_1: Presumably an indicator that classifies qualitatively the attribute fires_radi (low, high, medium)radius_u_1: Presumably an indicator that classifies qualitatively the attribute radius_umd (low, high, medium)radius_f_1: Presumably an indicator that classifies qualitatively the attribute radius_for (low, high, medium)primary_2: Presumably an indicator that classifies qualitatively the attribute primary_in (low, high, medium)primary_3: Presumably

Swaziland Imports of palm oil and its fractions, not chemically modified from Indonesia was US$775 during 2022, according to the United Nations COMTRADE database on international trade. Swaziland Imports of palm oil and its fractions, not chemically modified from Indonesia - data, historical chart and statistics - was last updated on July of 2025.

Indonesia Exports of palm oil and its fractions, not chemically modified to Vietnam was US$577.22 Million during 2023, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to Vietnam - data, historical chart and statistics - was last updated on August of 2025.

Indonesia Exports of palm oil and its fractions, not chemically modified to Benin was US$186.98 Million during 2023, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to Benin - data, historical chart and statistics - was last updated on August of 2025.

Ireland Imports from Malaysia of Palm oil and its fractions, not chemically modified was US$30.89 Million during 2024, according to the United Nations COMTRADE database on international trade. Ireland Imports from Malaysia of Palm oil and its fractions, not chemically modified - data, historical chart and statistics - was last updated on August of 2025.

Nigeria Imports from Indonesia of Palm oil and its fractions, not chemically modified was US$482.11 Thousand during 2023, according to the United Nations COMTRADE database on international trade. Nigeria Imports from Indonesia of Palm oil and its fractions, not chemically modified - data, historical chart and statistics - was last updated on August of 2025.

Indonesia Exports of palm oil and its fractions, not chemically modified to Dominica was US$183.42 Thousand during 2023, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to Dominica - data, historical chart and statistics - was last updated on July of 2025.

Indonesia Exports of palm oil and its fractions, not chemically modified to Brunei was US$3.05 Million during 2023, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to Brunei - data, historical chart and statistics - was last updated on July of 2025.

Nigeria Exports of palm oil and its fractions, not chemically modified to Portugal was US$19.18 Thousand during 2021, according to the United Nations COMTRADE database on international trade. Nigeria Exports of palm oil and its fractions, not chemically modified to Portugal - data, historical chart and statistics - was last updated on August of 2025.

Indonesia Exports of palm oil and its fractions, not chemically modified to Venezuela was US$110.64 Thousand during 2022, according to the United Nations COMTRADE database on international trade. Indonesia Exports of palm oil and its fractions, not chemically modified to Venezuela - data, historical chart and statistics - was last updated on July of 2025.