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Slowing deforestation in Indonesia follows declining
oil palm expansion and lower oil prices
David Gaveau ( d.gaveau@thetreemap.com )
TheTreeMap https://orcid.org/0000-0003-2671-2113
Bruno Locatelli
CIRAD, Univ Montpellier, CIFOR https://orcid.org/0000-0003-2983-1644
Mohammad Salim
TheTreeMap
Husnayaen Husnayaen
TheTreeMap
Timer Manurung
AURIGA
Adrià Descals
Centre de Recerca Ecològica i Aplicacions Forestals
Arild Angelsen
Norwegian University of Life Sciences
Erik Meijaard
Borneo Futures
Douglas Sheil
Norwegian University of Life Science
Article
Keywords: Annual Time-Series, CPO prices, Deforestation, Indonesia, Industrial, Oil Palm, Smallholder,
Plantations, Satellite.
DOI: https://doi.org/10.21203/rs.3.rs-143515/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full
License
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Abstract
Much concern about tropical deforestation focuses on oil palm plantations, but their impacts remain poorly
quantied. Using satellites, we estimated annual expansion of large-scale (industrial) and smallholder oil palm
plantations and their overlap with forest loss from 2001 to 2019 in Indonesia, the world’s largest palm oil
producer.
Over nineteen years, the area under oil palm doubled, reaching 16.24 million hectares (Mha) in 2019 (64%
industrial; 36% smallholder), more than ocial estimates of 14.72 Mha. This expansion was responsible for
nearly one-third (2.85 Mha) of Indonesia’s loss of old-growth forests (9.79 Mha). Industrial plantations were
associated with three times as much forest conversion as smallholder plantings (2.13 Mha vs 0.72 Mha). New
plantations peaked in 2009 and 2012 and declined thereafter.Deforestation peaked in 2016 and fell below pre-
2004 levels in 2017-2019. Expansion of industrial plantations and forest loss were correlated with palm oil
prices. A price decline of 1% was associated with a 1.08% decrease in new industrial plantations and with a
0.68% decrease of forest loss.This slow-down provides an opportunity for the Indonesian government to focus
on details of sustainable oil palm management. If prices rise, effective regulations will remain key to
minimising deforestation.
Introduction
Concern for Indonesia’s remarkable rain forests and their species-rich communities, including charismatic
animals such as orangutans, tigers, and elephants is nothing new1 but in recent decades this has increasingly
focused on the palm oil industry2. This multi-billion dollar industry is based on cultivation of the African oil
palm (
Elaeis guineensis
Jacq.) and conversion to oil palm plantations has been highlighted as a major cause
of deforestation and biodiversity loss3. In Indonesia, where half of global palm oil production occurs4,
expansion of oil palm plantations has often replaced forests. Indonesia is a focus of conservation efforts
because it has some of the world’s richest forests with the most rapid deforestation5.
A growing number of consumers are demanding palm oil-based products that are not associated with forest
loss. The European Union has also become increasingly concerned about avoiding deforestation-tainted
imports, especially for biofuel6. Other nations, in tandem with environmental NGOs, have also made efforts to
eliminate either all palm oil or deforestation-linked palm oil from consumer goods and other imports. Many of
the world’s largest traders and producers of palm oil have made “
No Deforestation”
commitments in which they
guarantee to eliminate deforestation from their supply chain by a stated date7. Furthermore, in 2011, the
Indonesian Government instituted a nationwide moratorium on developing new concessions on peatlands and
“primary” forests, e.g. excluding natural forests impacted by selective timber harvesting, and reclassied as
“secondary” forest by the Indonesian Ministry of Environment and Forestry8. This moratorium was extended
indenitely in 2019.
While many have blamed oil palm expansion for Indonesia’s deforestation, this is contested by other scholars
and by the industry and the government9. One analysis estimated that between 2001 and 2016 industrial oil
palm plantations (i.e. large-scale intensively managed plantations owned and managed by companies)
accounted for 23% of total Indonesia-wide deforestation10. Taken over a longer period, 1972-2015, a regional
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study found that in Kalimantan (Indonesian Borneo), industrial oil palm accounted for just 15% of total
deforestation because most new plantations made use of land cleared decades before11. However, from 2001
to 2017 conversion increased, accounting for 36% of total deforestation in Kalimantan12. These studies
demonstrate that the impacts of oil palm on forests clearly vary by region and period13. Several recent studies
have demonstrated that industrial plantation expansion and associated forest conversion had slowed10,12
though not everyone agrees14. One reason for the slow-down might be, as indicated in a previous study from
Kalimantan, that expansion of plantations is linked to the price of palm oil which has declined in recent years12.
There are also concerns that even if expansion of industrial plantations slows this may be replaced by less
readily observed growth among smallholders15. Due to problems of detection previous studies omitted
smallholder plantings. The Indonesian government estimates that these constitute 40% of the total area under
oil palm16.
This article describes recent trends in Indonesia’s oil palm expansion and links with forest loss. For the rst
time, we present an annual time-series showing the expansion for industrial and smallholder plantations, forest
loss, and their overlap, from 2001 to 2019. These data derive from complete annual maps created by
interpretation of annual cloud-free LANDSAT composites, SPOT-6 and UAV imagery17, combined with
previously published sources of forest cover5 and tree loss18. We separate results by regions (Sumatra,
Kalimantan, Papua, Sulawesi, Java and Maluku) to allow for different contexts. We compare our results
against two previously published studies10,19 and against statistics from the Government of Indonesia16 to
determine similarities and differences. We also examine the links with annual prices of crude palm oil and
discuss the implications.
Results
Summary 2001-2019
We estimated that 82.59 Mha, or 44% of Indonesia’s landmass was forest in 2019. Lowland forests (<500 asl),
among the richest in the world20 extended 55.59 Mha. These “forests” comprise old-growth natural forests,
including those impacted by selective timber harvesting (reclassied as “secondary” forest by the Indonesian
Ministry of Forestry and Environment). By comparison, the Ministry reported 82.5 Mha of “primary and
secondary” forest in 201721. The area of forest declined by 9.79 Mha (11%) from 2001 to 2019, representing an
average annual deforestation rate of 0.51 Mha yr-1. Sumatra and Kalimantan lost more forest than other
regions with 4.08 Mha (25%) and 4.02 Mha (14%), respectively. A quarter (12.06 Mha) of Sumatra, and nearly
half (25.74 Mha) of Kalimantan were forest in 2019. Papua (Indonesian New Guinea) lost the least amount of
forest (0.75 Mha; 2%) and retained the largest area (34.29 Mha, 83% of its landmass, or 41% of Indonesia’s
remaining forests). Sulawesi experienced similar losses to Papua (0.72 Mha; 7%) but retained less forest (9.11
Mha; 49% of its landmass). See Table 1 for a breakdown by regions considered.
Table 1.Oil palm plantation, forest loss, and share of forest loss caused by oil palm 2001-2019
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Areas (in Ha) Indonesia Sumatra Kalimantan Papua Sulawesi Java
Maluku
Landmass 189,130,128 47,467,842 53,498,290 41,227,232 18,627,593 21,135,660
2019 Forest area 82,590,327
(44%)
12,063,230
(25%)
25,742,162
(48%)
34,289,462
(83%)
9,114,005
(49%)
5,658,137
(27%)*
2019 forest area (<500 asl) 55,724,906 5,961,949 17,266,990 25,165,882 3,130,233 3,920,071
Forest loss
2001-2019
9,789,448
(11%)
4,075,312
(25%)
4,023,971
(14%)
748,640
(2%)
715,737
(7%)
213,487
(4%)
Forest converted to Oil
Palm
3,094,882
(32%)
1,242,345
(31%)
1,593,260
(40%)
200,161
(27%)
46,782
(7%)
12,629
(6%)
Rapid conversion§2,849,796
(29%)
1,166,806
(29%)
1,434,493
(36%)
194,996
(26%)
43,319
(6%)
10,181
(5%)
Rapid conversion to
industrial
2,129,301
(22%)
553,480
(14%)
1,341,610
(33%)
194,671
(26%)
29,807
(4%)
9,733
(4.5%)
Rapid conversion to
smallholder
720,495
(7%)
613,326
(15%)
92,884
(3%)
325
(0.0004%)
13,512
(2%)
448
(0.002%)
We used a sinusoidal projection to calculate areas.
(%) of landmass.
(%)of 2000 forest area.
(%)of forest loss.
The area of forest that existed in year 2000 and became converted to oil palm plantation in 2019. Here, we cannot assume
that all 3.09 Mha forest cleared were all caused by oil palm. The forest may have been cleared for other reasons well before
being planted with oil palm.
§ The area of forest that was cleared and converted to oil palm in the same year. We can assert that all 2.85 Mha were cleared
for oil palm.
* Maluku lost 201,081 ha of forest between 2001 to 2019. It had 5,167,788 ha forest left in 2019, or 66% of its landmass
(7,876,562 ha). Java lost 12,406 ha. It had 703,836 ha forest left, or 5% of its landmass (13,259,098 ha)
The provinces of Bali and East and West Nusa Tenggara (landmass=7,173,511 ha) lost 12,301 ha of forest between 2001 and
2019, representing 2% loss. In 2019, there were 677,631 ha of forest and no oil palm in these three provinces.
From 2001 to 2019 Indonesia gained 8.48 Mha of oil palm plantations (6.19 Mha industrial; 2.28 Mha
smallholder) reaching a total of 16.24 Mha in 2019, with 64% industrial and 36% smallholder. The estimated
overall accuracy of the 2019 oil palm extent is 96% (see Supplementary Table S1 for full accuracy report). In
this assessment, smallholder plantations developed in patterns that look like industrial plantations in satellite
images (e.g., plasma schemes22) were counted as “industrial”. We note that our total estimate includes
immature, damaged, and failed plantations and thus surpasses estimates that include only closed-canopy
mature plantations19 (e.g., 11.5 Mha). The Government of Indonesia’s estimates based on company reports and
interview with smallholders (14.72 Mha), include mature and damaged plantations16, but likely omit some
illegal plantations that go unreported. We estimate that oil palm plantations in the State Forest Zone (
Kawasan
Hutan
), where oil palm is prohibited, covered 3.13 Mha in 2019, i.e., 19% of total oil palm area. See Table 2 for a
comparison of datasets, and breakdown by regions considered.
Table 2. Oil palm expansion 2001-2019, and planted area based on three different sources: this
study, a global study18 and Government statistics16
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Areas (in
Ha)
Indonesia Sumatra Kalimantan Papua Sulawesi Java
Maluku
Oil palm
expansion
(2001-2019)
8,477,253 3,457,500 4,598,415 221,117 164,471 35,749
Oil palm
area, 2019
(This study)
16.237,047 9.486,516 6.044,517 272,808 374,686 58,520
Industrial 10,316,986(64%) 4,684,385(49%) 5,105,427(84%) 271,486(99.5%) 207,165(55%) 48,522
(83%)
Smallholder 5,920,061
(36%)
4,802,130(51%) 939,091(16%) 1,322(0.5%) 167,520(45%) 9,998
(17%)
Oil palm
area, 2019
(Des cals et al.
2020)18*
11,531,006 6,770,223 4,259,152 175,803 304,442 36,379
Industrial 7,706,254
(67%)
3,692,628
(55%)
3,682,299
(86%)
169,880
(97%)
144,787
(48%)
27,556
(76%)
Smallholder
3.828,849
(33%)
3,077,595 (45%) 576,853
(14%)
5,923
(3%)
159,655
(52%)
8,823
(24%)
Oil palm
area, 2019
(Ministry of
Agriculture
2020)16
14,724,420 8,299,729 5,713,504 213,359 450,499 47,328
Industrial
8,688,678
(59%)
3,560,687
(43%)
4,670,281
(82%)
180,685
(85%)
238,498
(53%)
38,527
(81%)
Smallholder
6,035,742
(41%)
4,739,042
(57%)
1,043,223
(18%)
32,674
(15%)
212,001
(47%)
8,801
(19%)
*Area of plantations extracted from a global oil palm map derived by based on radar data18. This dataset only includes mature
(closed-canopy) plantations
Area of plantation extracted from 2019 statistics of the Directorate General of Plantation Estates Crops of the Indonesian
Ministry of Agriculture16. This dataset includes immature (open-canopy), mature (closed-canopy) and damaged plantations.
The area that was forest in 2000 and oil palm in 2019 is 3.09 Mha (32% of total forest loss: 9.79 Mha), with
2.85 Mha (29%) cleared and converted in the same year (termed “rapid conversion” in Table 1): 2.13 Mha (22%)
by industry and 0.72 Mha (7%) by smallholders. In general, more plantations were established in areas cleared
of forest before 2000 (5.39 Mha; black and white bars in Figure 1). Only in Papua did most new plantations
replace forests (Figure 2).
Comparing regions shows that Kalimantan experienced the highest share of both total and rapid (same year)
forest conversion to oil palm (40% and 36% respectively), followed by Sumatra (31% and 29%), Papua (27%
and 26%) and Sulawesi (6% and 5%). In Sumatra and Sulawesi, industrial and smallholder driven conversion
were similar in magnitude while industrial conversion dominated in Kalimantan and Papua (Table 1).
Annual trends
Industrial and smallholder plantations followed similar trends: expansion (black and white bars; Figure 1a,b,c)
and rapid forest conversion to oil palm (white bars only) increased during the 2000s, peaked in 2009 (0.84Mha
added; 0.28 Mha forest converted) and 2012 (0.80 Mha added; 0.31 Mha forest converted) and steadily
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declined thereafter. In 2019, overall plantation expansion had dropped to pre-2004 levels (0.16 Mha added;
0.059 Mha forest converted). The expansion of new oil palm plantings has slowed in all regions (Figure 2, and
Supplementary Figures S1, S2), though this occurred later that elsewhere in Papua where expansion peaked in
2015 rather than 2012. The market price of crude palm oil (CPO) has also risen and then declined over the
period of our study with peaks in 2008 and 2011 (Figure 1e). We note a positive correlation between annual
CPO prices23 and expansion of oil palm plantations (also industrial plantations, but not signicant for
smallholders) as well as with forest loss (Figure 1f). A decrease/increase in CPO prices by 1% was associated
with a decrease/increase of new industrial plantations by 1.08% and with a 0.68% decrease/increase of forest
loss (Figure 1g). Annual forest loss climbed in 2004, followed by variable but high rates that reached a
maximum in 2016 (0.90 Mha cleared) before falling to pre-2004 levels (<0.34 Mha cleared) for three
consecutive years (Figure 1d). This 2016 maximum is evident in Kalimantan and Sulawesi (Figure 3), but not in
Sumatra where forest loss peaked in 2012. In Papua, forest loss peaked in 2015.
Discussion
We estimated the annual expansion of industrial and smallholder oil palm plantations and their overlap with
forest loss from 2001 to 2019. Industrial plantations expanded faster than smallholder plantations (6.19 Mha
added vs 2.28 Mha) and caused almost three times as much rapid forest conversion (2.13 Mha vs 0.72 Mha).
We nd an increase in plantations expansion and rapid forest conversion during the 2000s, followed by a
decline after 2012 (Figure 1a,b,c). This decline was gradual for industrial plantations, and more abrupt for
smallholders (Figure 1b,c). The industrial trend is consistent with other evaluations10 (Supplementary Figure
S3), though Xu et al. (2020)14 reported a 2016 peak in expansion but discussions with those authors suggested
an artefact caused by different data sources (Xu et al. pers. com.). We also observed an abrupt decrease of
deforestation in 2017, 2018 and 2019. Our data show that expansion of plantations directly explained 29%-32%
of total forest loss observed between 2001 and 2019. We conclude that oil palm was responsible for one-third
of Indonesia’s loss of old-growth forests over the last two decades. If we include impacts of industrial pulp and
paper plantations (most commonly Acacia mangium Willd., and Acacia crassicarpa A.Cunn ex Benth), the
direct conversion due to expansion of plantations directly explained 39%-42% of total forest loss observed
between 2001 and 2019 (Supplementary Table S2). We underline that these estimates are conservative
because they omit the indirect effects of plantations on forest loss through associated road expansion and
resulting in-migration and associated forest conversion. They also exclude conversion of young forest re-
growth, agroforests, and other mixed gardens. For evaluations of impacts of oil palm on regrowth forests more
complex remote sensing assessments and eld measurements will be necessary. Nevertheless, our results
conrm oil palm’s major role as a direct driver of old-growth forest loss, but also reveal that recent expansion
and associated forest conversion have declined. Our data also shows that industrial plantations caused more
deforestation than smallholders and contrary to expectations15, smallholder plantations have followed a
similar, and somewhat more abrupt, recent decline indicating that similar factors were at play, although this
might change because smallholder oil palm is expected to grow from 40% (we nd 36%) of the total national
planted area to over 60% by 203015.
Past warnings regarding the fate of Indonesia’s lowland forests were justied1,20. In Western Indonesia, and
Sumatra in particular, but also Kalimantan to a lesser extent, remaining lowland forests are fragmented and
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scarce (see Figure 3). These forests have high conservation value but remain vulnerable to various threats
including re, conversion to plantations, hydropower dams and road developments24-27. Many also occur in a
matrix of degraded forest and regrowth that has a potentially higher conservation value than is often
acknowledged and should be included in conservation planning28. In Western Indonesia strong conservation
action is needed to manage and restore connectivity among forest areas. In contrast to Western Indonesia,
Eastern Indonesia, and Maluku and Papua in particular, retain large unbroken tracts of relatively pristine forests
offering development trajectories that should include forest protection as a core value. Given the protability of
the crop the oversight of further oil palm plantings is likely to remain contentious, though efforts to increase
transparency over sourcing have increased.
Why did plantation expansion slow after 2012? The positive correlation with Crude Palm Oil (CPO) prices
suggests that these were inuential. The economies of China and India ourished from 2000 and 2011 and the
price of CPO quadrupled (annual mean from USD 261 to USD 1077). This accelerated investment in new
plantings. Around 2011-12, as the economies of China and India slowed, the market could not absorb the high
increases in supply and prices began to decline. Subsequently, between 2011 and 2019, the annual price of
CPO halved (USD 523 by 2019). Another reason for this price decline may be the inuence of the crude oil price
(i.e., “mineral oil”) on the palm oil price29, with the former reducing by nearly half from 2012 to 201930. Palm oil
planting remains a risky investment due to the upfront expenses and the substantial time required to recoup
costs. New investments became less attractive when the Indonesian government introduced the deforestation
moratoria in 2011 (extended in 2019) and the government and others emphasising the need for regulations,
including certication8.
Why has forest loss peaked in 2016 and slowed from 2017 to 2019? One factor is clearly the growth and
decline in plantations already described. Another is re. The 2016 peak (Figure 1d) reects the El Niño-induced
drought of 2015, when re burned large areas of forest in Central Kalimantan31. Much of these losses were
recorded only the following year by the tree loss dataset17 that we used in this study to calculate forest loss
(see Methods). One study estimated that forest conversion to grasslands due to re explained 20% of total
forest loss in Indonesia between 2001 and 201610. 2017 and 2018 were generally wetter resulting in less
ammable landscapes. In contrast, 2019 was again a dry re-prone year, though less forest was burned than in
201532.
Might Indonesia have already reached the slowdown in forest loss expected for a forest transition? Despite the
positive trends we believe that the common drivers described for forest transitions have not played any major
role in the observed rise-and-fall patterns i.e., forest scarcity and economic development33. The are of forest
remains abundant overall (43% of Indonesia’s landmass) and the impact of economic development in slowing
forest loss would not be expected to emerge over such a short period34.
Various other factors have likely inuenced the declining trends. For example, in many regions remaining
forests are often inaccessible or formally protected, and the improved legal basis for community-based land
claims have likely further curtailed companies’ access to land35. Furthermore, an increasing number of
consumers seek products that they consider ethical. This has generated various initiatives aimed at
distinguishing and certifying products that avoid deforestation, and companies seeking to be associated with
pledging to avoid forest clearing with “no- deforestation commitments”13. This interest has led to wide scrutiny
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of the palm oil industry using data that now include publicly available satellite imagery in near-real time36.
Taken over a longer period, we note that the average rate of deforestation experienced during the period
considered (2001-2019), when Indonesia became a democracy was three times slower than during the
dictatorship of the Suharto regime in 1980s and 1990s (0.51 Mha against 1.67 Mha)1, also explaining why so
many plantations were able to expand without replacing forests.
While the slowing in deforestation and the many commitments from industrial commodity producers to avoid
forest loss justify cautious optimism, forest loss has not ceased and there is no guarantee that the low levels of
conversion seen in 2017-2019 will remain. CPO prices might rise, increasing protability of palm oil again,
potentially driving further expansion. Demand driven by Indonesia’s biodiesel program could stimulate
expansion, particularly at the expense of forests that are excluded from the Moratorium (i.e., old growth forests
impacted by selective timber harvesting, and reclassied as “secondary”). Palm oil buyers regularly breach their
“
No Deforestation”
commitments because of incomplete transparency 37. Political changes may reverse forest
policies with dramatic implications, as seen in Brazil. In response to the covid-19 pandemic the Indonesian
government has relaxed or removed several forest regulations. These include removing licenses certifying that
the wood comes from legal sources for timber export38, allowing cleared lands within “protection forest” zones
to be converted to food estates39. The Indonesian government also amended a host of other environmental and
labour regulations in the so-called “Omnibus Bill” of October 2020, which affects 79 existing laws40.
On the positive side, deforestation has declined dramatically over the last half decade, the REDD+ agreements
with Norway and with the Green Climate Fund are now rewarding the country for reduced emissions from the
forest sector. Steps have also been taken to protect forests, including through increased community
management41 and are gaining support and momentum. Transparency has improved, partly because of the
growing availability of real-time deforestation monitoring tools37, and independently veried certication
criteria13. The slow-down in expansion (now at pre-2004 levels) also provides an opportunity for the Indonesian
government to focus more on details of sustainable oil palm planning and management42. Nevertheless, the
demand for palm oil is expected to increase in the future4, and drivers of expansion may reverse recent trends.
In the meantime, we must collectively invest in encouraging the good practice and transparency that serves
conservation as well as local and global needs.
Methods
Annual loss of forest
Annual forest loss represents the area of old-growth forest that has been cleared each calendar year from 2001
until 2019. This measurement is based on the most recent annual Tree Loss dataset (v1.7) developed at
University of Maryland with Landsat time-series imagery18. This dataset measures the removal of tree (tree
height >5m) if the canopy cover of a 30 m x 30 m land unit (one Landsat pixel) falls below 30%. The latest tree
loss map (version 1.7) has an improved detection of tree loss since 2011. However, the years preceding 2011
have not yet been reprocessed, so there may be inconsistencies.We also corrected several
Tree Loss
commission and omission errors by scanning a sequence of twenty annual cloud-free LANDSAT composites
developed in Google Earth Engine (see last paragraph)43.
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The tree loss dataset does not distinguish between removal of natural forests (tree cover >90%) and planted
trees (where canopy cover can also be >90% and tree height > 5m). To reduce any error resulting from this
ambiguity, we excluded
Tree Loss
pixels outside of the area occupied by natural forests in year 2000, to
determine losses in natural forest area rather than losses in planted trees. We used a natural evergreen
“primary” forest area mask for year 2000 developed previously5. These dense forests usually have closed
canopies (>90% cover) and high carbon stock (Above Ground carbon: 150 - 310 Mg C/Ha). They consist of tall
evergreendipterocarpsgrowing on drylands or swamps (including peat-swamps). Here, “Forests” include intact
and selectively harvested forests. Intact forests have never been disturbed by humans, or disturbances were too
localized to be detected by the satellites. Selectively harvested forests have been subjected to industrial scale
mechanized selective timber cutting and extraction. Intact and selectively logged forests are like “primary” and
“secondary” forests on the Indonesian Ministry of Forestry and Environment’s forest maps21 . They exclude
young forest regrowth, agro-forests, mixed gardens, scrublands, tree plantations, agricultural land, and non-
vegetated areas.
Annual expansion of oil palm plantations
We dene an oil palm plantation as an area of land planted with oil palm trees
(Elaeis guineensis
Jacq
.).
An
industrial oil palm plantation is owned and managed by a company. It typically covers several thousand
hectares of land. It is an area bounded by long straight lines, often forming rectangular boundaries. On level
land, plantings and harvesting trails are usually developed in straight lines forming a rectilinear grid
(Supplementary Figure S4a). In contrast, on steep terrain, plantings and trails follow a distinctive curved pattern
that follows contours (Supplementary Figure S4b). Smallholder plantations are smaller, less structured, and
more heterogeneous than industrial plantations. Smallholder plantations often form a mosaic, with other types
of landcover (Supplementary Figure S4c,d,e).
We used a government-sanctioned “oil palm” base map developed by interpreters from the NGO AURIGA
covering the entire Indonesia-wide extent of all oil palm plantations (small and large) as our starting point to
map the expansion of all plantations. This map was created by visual interpretation of high resolution (1.5 m)
SPOT 6 satellite imagery acquired between 2014 and 2018, complemented by photography (0.2-0.5 m) taken
from an Unmanned Aerial vehicle in 2018 and Landsat imagery (15-30 m)17. We made some corrections to this
base map to improve its quality. We removed coconut plantations misclassied as oil palm in the coastal
southeastern district of Indragili Hilir, Riau Province, where Indonesia’s largest coconut plantations are found,
using a land cover map from the provincial government (Supplementary Figure S5). We updated the plantation
dataset with a 2019 radar composite developed previously19 (Supplementary Figure S6).
To map the expansion of industrial plantations in time we scanned our sequence of annual cloud-free Landsat
composites from 2000 to 2019. We declared an area “converted to industrial oil palm” the year an area that
presented the characteristics of industrial oil palm plantations appeared on our sequence of imagery
(Supplementary Figure S7) and was within the extent of the “oil palm” base map. We delineated the boundaries
of plantations in 1:50,000 using a visual, expert-based interpretation method. We also mapped the expansion of
industrial pulp&paper plantations, as planting patterns and spectral colors of these plantations are clearly
discernible from industrial oil palm (Supplementary Figure S8). We also employed indicative maps of oil-palm
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and pulp&paper concessions, reviewed several online and press reports, and spoke to many experts to further
identify the location plantations.
We declared “smallholder oil palm” those areas classied as “oil palm” on the base map but that were not
included in our draft-industrial plantations expansion map, because they lacked the patterns characteristic of
large plantations. To estimate the expansion of smallholder plantations over time, we used the annual Tree
Loss Dataset described above17. We assumed that the timing of tree loss indicated the year areas were
developed into smallholder oil palm. Areas detected as “oil palm” by the base map that did not experience any
tree loss during the 2001-2019 period were automatically classied as smallholder oil palm plantations that
existed in year 2000.
We determined the area of forest converted to oil palm in the same year by measuring the overlap between the
annual plantation map and the annual forest loss map. We declared an area of forest rapidly converted to
plantations, if it became a plantation in the same year that it lost forest cover.
Map Validation
We validated the 2019 oil palm map using checks of 3209 points (620 industrial oil palm, 386 smallholder oil
palm; 2203 involved other land uses). We placed the points randomly in non-forest areas below 500 asl and
interpreted them using very-high resolution (< 1m) imagery extracted from Google Earth where individual oil
palm trees can be seen.
Developing composite images.
We generated annual cloud-free Landsat composites for each year from 2000 to 2019withGoogle Earth Engine
(Supplementary Figure S9). The cloud observations in the Landsat images were rstly masked with the quality
band ‘pixel_qa’, which is generated from the CFMASK algorithm and included in the Surface Reectance
products 44.Then, for each year, we created the annual composites using two criterions: 1) the median pixel-
wise value of the Red, Near Infrared (NIR), and Shortwave Infrared (SWIR) bands of the images acquired
between 1 January and 31 December, and 2) the minimum pixel-wise normalized burned ratio (NBR) of the
images taken in the same given year. The composite image based on the median produces clean cloud-free
mosaics but tends to omit new plantations developed at the end of the year. The second approach, based on
the minimum NBR, produces noisier composites (residual clouds and shadows may persist), but it presents the
advantage to capture the plantations that were developed at the end of the year.
Declarations
Supplementary Information is available in the online version of the paper.
Acknowledgement
This work was funded by the WWF-US and Global Environment Facility (GEF) under the Good Growth
Partnership, and in collaboration with the Trase Initiative. DS’s time was covered by NMBU.
Page 11/14
Author Contributions D.L.A.G., D. S designed the study. D.L.A.G., H.Y., M.A.S. created and analysed the maps.
D.L.A.G, B.L. M.A.S and A.A. analysed the oil-palm and deforestation datasets. T. M; E.M., and A. A contributed
information. D.L.A.G., B.L. and D.S. wrote the manuscript and produced the gures, with feedback from all
authors.
Additional Information The authors declare no competing nancial interests. Readers are welcome to comment
on the online version of the paper.
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