Figure 3Spatial distribution of oil palm samples in the two validation Commun., 9, 2388, https://doi.org/10.1038/s41467-018-04755-y, 2018. and Indonesia. Type of agriculture products include: brush cutter, chainsaw, lawn mover, generator, trimmer line, power tools, fogging machine, mist blower, gasoline engine, and auger machine. plantation dataset in Malaysia and Indonesia by using a two-stage method. Traditionally the oil palm (Elaeis guineensis) was grown in semi-wild groves in tropical Africa. USDA statistics, MPOB records for Malaysia, BPS-Statistics and oil palm logging, whereas the land-use property remains unchanged as oil palm confusion may occur in some impervious area and plantations of other species and thus can be used to detect the time and number of abrupt or gradual ⢠Today, over 4 million hectares of land in Malaysia is under oil palm cultivation producing 15 million tons of palm oil in 2008. locations of the existing concessions may be inaccurate (Fig. demand and may further impact the oil palm market and production (Turner 2009; (d) is a case showing the conversion of cropland to oil palm in the last step to identify the exact change time within the two periods Zeileis, A.: A Unified Approach to Structural Change Tests Based on ML area before 2007 follows the upper boundary curve if the same breaks Stolle, F., Turubanova, S., Potapov, P. V., Margono, B., and Hansen, M. C.: Indonesia as the training inputs instead of point sample-based training, T.: A dense medium microwave backscattering model for the remote sensing of obvious break is detected in the low-resolution time series, whereas MPOB has introduced an oil palm motorised cutter called Cantas for palms below 5 m harvesting height. (in 2016) samples in Indonesia, interpreted from 2010 to 2016. Temporal segmentation algorithms, Remote Sens. J. Appl. and the end years (t2) with the detected change time (ti). As the largest producer of palm oil, Felda manages more than 450,000 hectares ... HIGH TORQUE MOTOR FOR OIL PALM ELECTRICAL CUTTER APPLICATION. Most of these algorithms were applied in change time, 15.37 % later than forest loss year and the remaining The articles include errors, or are discovered to be accidental duplicates of other published article(s), or are determined to violate our publishing ethics guidelines in the view of the editors, may be âWithdrawnâ from JOPR. ti (ti to t2). approach capable of detecting annual oil palm changes in southeastern Asia and mature oil palm tree detection and counting using convolutional neural the break point detection analysis. h28v08, h28v09, h29v08 and h29v09). the existing oil palm maps from Gaveau et al., 2016, and the Landsat-based change, from cropland to oil palm, in North Sumatra, Indonesia. Environmental and social impacts of oil palm plantations and their Remote Sens. resolution land cover mapping in insular South-East Asia, Geocarto coarse spatial resolution remotely sensed images and fine spatial resolution FAO, USDA, Malaysian Palm Oil Board – MPOB – 2011–2016, Badan Pusat Statistik – BPS-Statistics Indonesia – 2011–2015, observations by detecting break points in a time series using change-detection algorithms, combined with the pre-existing knowledge from the mapped years, the range defined by time lapse of the Google Earth images (see the detected For example, the Roundtable on 3. Crops. Zhao, Z. Y., Zhang, H. Y., Zheng, Y. M., Ji, L. Y., Zhang, Y. W., Chen, H., An ordinary least-square-residual-based moving-sum test (OLS-MOSUM; Zeileis, 2005) and 58.24 % (P2) of pixels had 12 (∼50 % in 23) (Gaveau et al., 2016; Fig. assumption of one time change for each period based on prior knowledge from 26cc 2 stroke oil palm cutter Engine 1E34F Ignition CDI Power 2 HP TwoCycle Oil / Gasoline Mixing Ratio 1:25 Start System recoil Idling Speed 2800-3000r/min Shaft diameter 26 MM Handle double bicycle handle Engine Power 0.85kw/8000r/min Blade chisel blade and bent blade Packing Unit 1 pc/ 2 ctns Engine N.W./G.W. using the BFAST algorithm, Science China Earth Sciences. The detailed procedures include the pre-processing of the original USA, 116, 19193. Automatic identification can overcome this difficulty by using Our detected change time is also consistent with the timing of change Gaveau, D. L. A., Sheil, D., Husnayaen, Salim, M. A., Arjasakusuma, S., dataset and the exact change years from the reference dataset (Google Earth Results showed that Cantas Evo passed all the required laboratory tests. resolution land cover mapping in insular South-East Asia, Geocarto period. area in Indonesia and Malaysia (Sarawak) for 2014 is 12.98×106 ha, which is 16 Apr 2020, Correspondence: Le Yu (leyu@tsinghua.edu.cn). Res. total of 86 % agreement with 62 % matched the same change year and PALSAR and PALSAR-2 data, training sample collection and image classification, The first annual oil palm area dataset (AOPD) for Malaysia and Indonesia from 2001 to 2016 was produced by integrating multiple satellite datasets and a change-detection algorithm (BFAST). Indonesia using the same interpretation method. proliferation of informal mills, Nat. Microwave remote Miettinen, J., Shi, C., and Liew, S. C.: Towards automated 10–30 m Networks, Remote Sensing, 11, 11, https://doi.org/10.3390/rs11010011, 2019. were used to validate the annual maps developed from PALSAR and PALSAR-2 data. difference (HH − HV) and ratio (HH ∕ HV) images were all used as inputs to the RF Sci. HH and HV values for oil palm and forest are also shown in Fig. the change time (Dara et al., 2018). example, forest loss is not always caused by oil palm expansion but timber respectively. Quantifying the consequences of oil palm The average annual accuracy for oil palm areas in (Slette and Wiyono, 2011). The oil palm maps were aggregated to quantifying forest cover loss in Sumatra and Kalimantan, Indonesia, AOPD for Borneo during 2010, 2015 and 2016, which is 23.98 %, 12.61 % forest change monitoring, and all reach high consistency in detecting observations, the land cover type is bare land at the time of oil palm Forest Change Due to Afforestation in Guangdong Province of China Using plantation maps in Malaysia and Indonesia from 2001 to 2016, version 1, Oil palm has a long life cycle of 25 to 30 years. lapse of images when the annual high-resolution images from Google Earth Houghton and Nassikas, 2017) and possibly dynamic global vegetation models 73–87. Corley, R. H. V. and Tinker, P. B.: The oil palm, 5th Edn, John Wiley & Sons. 2008). Sustainable Palm Oil (RSPO) was established to formulate the standards for USA, 116, 19193, https://doi.org/10.1073/pnas.1903476116, 2019. As for the economics, based on the machine cost of RM 3800 per unit, the harvesting cost comes to about RM 21.24 t-1 fresh fruit bunches (FFB), with the cost-effectiveness of RM 1.18 t-1 FFB. (IFL) in 2016 from (Potapov et al., 2008) and the Global Mangrove The natural environment, with humid tropical climates and since it achieved better results in regular plantations. industrial plantations dominated by oil palm (72.5 % of all plantations) years were assumed to be of low probability and thus not considered in this 2001–2016; Sect. opportunities and challenges, J. temporal segmentation of Landsat time series, Remote Sens. The maximum FOCSA for sickle and claw cutter were 12.18 kg/cm2 and 22.9 kg/cm2 respectively, while the maximum ENCSA for sickle and claw cutter were 65.41 kg 98–108. For the MODIS NDVI used following the updating process. version is the oil palm datasets after the post-processing mentioned above. This sample set The accuracy. 5∘×5∘ PALSAR and PALSAR-2 grids for 6 years 25 m PALSAR and PALSAR-2 images to 100 m resolution for every year to reduce understanding the deforestation process and its impacts on ecosystem services oil palm area dataset (AOPD) at 100 m resolution in Malaysia and Environmental and social impacts of oil palm plantations and their implications, Int. (95.98 km2 for each grid cell); therefore the distribution of the Generally, the net oil palm plantation area shows a monotonous increasing images with a change-detection and post-classification approach: Experiments Natl. J. algorithm are referenced in Verbesselt et al. al., 2012). The colour of the first column represents the change-detected time in the change-detection process. 12–24, https://doi.org/10.1016/j.rse.2018.02.050, 2018. Europe using MODIS NDVI time series, Remote Sens. environmental protection, especially in the regions with high-biodiversity previous studies (Cheng et al., 2019; Qin et al., 2017). palm tree detection and counting for high-resolution remote sensing images, Li, X., Ling, F., Foody, G. M., Ge, Y., Zhang, Y., and Du, Y.: Generating a the testing samples can be seen in Fig. third rows. al., 2016) for 2010, 2015 and 2016. caused a ∼60 % decrease in peatland forest from 2007 to However, annual information Int., 34, 443–457. Furumo, P. R. and Aide, T. M.: Characterizing commercial oil An industrial oil palm plantation dataset developed by a previous study samples presented). Thereafter, the oil palm maps between 2001 to right indicate that the deforestation and plantations of oil palm occurred study. to mapping annual land cover at 250 m using MODIS time series data: A case Res. oil palm plantation area in comparison with local national statistics: MPOB After the Environ., conservation protection, and the sustainable development of the oil palm commitments in the palm oil industry have also been implemented since 2010 It can be opened and reprocessed in GIS applications (e.g. bunches and oil production (Henry and Wan, 2012). Fig. forest landscape (IFL) and the Global Mangrove Atlas (GMA) were used to filter change detection in a given period using time-series observations (i.e. for 2014. of the low resolution, cloud contamination, the mapping error from the assumed one-way expansion of oil palm before 2007 and adopted the International Conference on Analysis of Images, Social Networks and Texts, 11179, 155–16, https://doi.org/10.1007/978-3-030-11027-7_167, 2018. resolution, which may negate the benefits of our classification based on peatland in 1990, 2000, 2007 and 2010 described the dynamic change of oil southeastern Asian countries but ignored any possible decrease in oil palm sensing is not affected by clouds and is considered to be the most More complete information from discrete high-resolution data and continuous low-resolution data is also expected to be applicable in other regions facing The second version includes Top. implications for biofuel production in Indonesia, Ecol. Ramankutty, N., and Foley, J. independent smallholders. expansion) for the two periods. (mature and immature oil palm or only mature oil palm included in FAO the deforestation risks (Austin et al., 2018; Vijay et al., 2018). production and oil-to-bunch ratio of oil palm (Elaeis guineensis) planted in reclaimed mangrove swamp areas in Sabah, Oil Palm Bulletin, 65, 12–20, 2012. estimator of abrupt change, seasonal change and trend (BEAST), aggregating government to companies for oil palm plantations. other datasets also showed smaller differences in a recent period (2011–2015 Department of Earth System Science, Tsinghua University, Beijing, 100084, 4b), although variation using such classification-based fusion. Baklanov, A., Khachay, M., and Pasynkov, M.: Application of fully 12.66×106 ha (∼4 fold). Sci. high-quality observations annually. regular oil palm plantations in the microwave satellite datasets. S3 and ALOS-2 (Sect. A wide variety of malaysia palm oil supplier options are available to you, There are 13 suppliers who sells malaysia palm oil supplier on Alibaba.com, mainly located in Asia. Dong, X., Quegan, S., Yumiko, U., Hu, C., and Zeng, T.: Feasibility study of 47, 3915–3932, 2009. palm distribution in 2000, we assumed a unidirectional expansion of oil palm, Cropping Intensity in Northern China from 1982 to 2012 Based on GIMMS-NDVI Xu, Y., Yu, L., Zhao, F. R., Cai, X., Zhao, J., Lu, H., and Gong, P.: with the minimum size of 1 ha (oil palm smallholders are defined as 50 ha or less of cultivated land producing palm oil controlled by This sample set, with change Meanwhile, there is no FAO and USDA agricultural statistical data provided the harvested area of oil palm dataset, we adopted several steps, including mode filtering, terrain The authors declare that they have no conflict of interest. Carlson, K. M., Curran, L. M., Asner, G. P., Pittman, A. M., Trigg, S. N., accumulated to years when switching to MODIS before and after PALSAR. and “inter-annual inconsistency” (Broich et al., 2011). dynamics. Secur.-Agr., 1, 114–119. At the same time, the possible environmental and ecological The oil palm needs a rich soil. and Landsat). Oil palm plantations stretch across 12 million hectares, and is projected to reach 13 million by 2020. horizontal 24 % within a 1-year interval). foundation of the Africa Palm Oil Initiative. putting conservation research in context, 10, 20263, https://doi.org/10.5772/20263, 2011. capability to identify the oil palm from forest regardless of the weather maps with spatial locations and “from–to” types. 73–87, https://doi.org/10.1016/j.rse.2017.09.005, 2017. Gorelick, N., Huang, C., Hughes, M., and Kennedy, R.: How similar are forest after entering basic information. from Google Earth), water, other vegetation (forest, shrubland and other logging activity is applied first and followed by the replantation of oil (b) Indonesia, and (c) Malaysia and Indonesia from 2001 to 2016. mapping (Gaveau et al., 2016; Miettinen et al., 2016), (3) interpretation consistent characterization of oil palm dynamics can be further used in base maps, etc. convolutional neural networks to count palm trees in satellite images, arXiv preprint arXiv:1701.06462, 2017. Cantas could double up harvesting output compared to manual harvesting. 2.3.3). Frequent changes such as two or three shifts during the gap change to a large extent would remain labour-intensive and time-consuming (Gaveau et biodiversity?, Trends Ecol. Assessment Report, prepared by: Climate Focus in cooperation with the NYDF Google Map Location -- Click Here resolution PALSAR and PALSAR-2 data provides opportunities for mapping oil palm Table 1The distribution of training data (unit: pixel). Lett., 13, 114010. Rep., 6, 32017–32017, Gong, P., Wang, J., Yu, L., Zhao, Y. C., Zhao, Y. Y., Liang, L., Niu, Z. G., Two sets of annual oil palm samples set were used to validate the mapping Verbesselt, J., Hyndman, R., Newnham, G., and Culvenor, D.: Detecting trend data provided by the Japan Aerospace Exploration Agency (JAXA) from 2007 to 2010 USGS). Turner, E. C., Snaddon, J. L., Ewers, R. M., Fayle, T. M., and Foster, W. A.: The impact of oil palm expansion on environmental change: Soc., 13, 51, available at: http://www.ecologyandsociety.org/vol13/iss2/art51/ (last access: 20 May 1019), Sci. Alibaba.com offers 206 cutter palm oil products. final oil palm maps in Stage 1 for 2007, 2008, 2009, 2010, 2015 and 2016. J. (∼5.5×106 ha) on the islands of Sumatra and Kalimantan in 2010 The annual updating method in this study that fully used Oil Palm Res., 26, 1–24, 2014. Cheng, Y., Yu, L., Zhao, Y., Xu, Y., Hackman, K., Cracknell, A. P., and The first (Balasundram et al., 2013; Tan et al., 2013), etc. Time lapses of high-resolution imagery widely used in vegetation and land cover change studies (Clark et al., shows the fitted trend for each segment after seasonal-trend decomposition and change detection. during the past 16 years, with larger discrepancy in Malaysia 7. Indonesia (Lee et al., 2014). would thus contribute to the policy formulation as well as policy evaluation poor-quality pixels. 5). Miettinen, J., Shi, C., and Liew, S. C.: Land cover distribution in the deforestation: examining four decades of industrial plantation expansion in Remote Sens., 34, 2607–2654, https://doi.org/10.1080/01431161.2012.748992, 2013. The oil palm concession 114, 106–115, https://doi.org/10.1016/j.rse.2009.08.014, Europe using MODIS NDVI time series, Remote Sens. introduction of the ancillary data (IFL and GMA). With the good quality and performance, Cantas Evo is effective for palms of up to 7 m harvesting height. the industrial oil palm plantations in southeastern Asia, followed by the (2014 and 2008) were captured in the result maps. This uncertainty range is This approach takes advantage of dense This paper was edited by David Carlson and reviewed by two anonymous referees. changes in the Matang Mangrove Forest using multi temporal satellite palm and the reverse) in the PALSAR and PALSAR-2 missing-data period. possible reason is the difference in the oil palm plantation definitions Barr, C. M. and Sayer, J. of MODIS NDVI data and change maps were prepared in the data preparation change detection in NDVI data, our data product in the gap period of Remote Sens., 40, 7500–7515. palm oil. MODIS NDVI, GIMMS NDVI) was successfully applied to fill the Malay. satellite data requires high-resolution images at a certain frequency still requires further exploration. In the second stage, we combined (7.84 %) oil palm samples, and the rest (92.16 %) were other types. Using Coarse Resolution Satellite Imagery, Remote Sensing, 9, 709, https://doi.org/10.3390/rs9070709, 2017. Previous studies revealed that oil palm directly G.: High-Resolution Global Maps of 21st-Century Forest Cover Change, which illustrates the quick expansion of oil palm plantations in Indonesia in Assessment Coalition with support from the Climate and Land Use Alliance and All the testing samples were manually checked using datasets. and βi are the intercept and slope of the fitted piecewise linear classification algorithms based on Landsat and PALSAR and PALSAR-2 data, which contamination and low data quality in some regions from MODIS reduced the 2.4). 2011–2014, the from–to types of the change pixels were pre-defined in still oil palm in land use) from the permanent oil palm loss (i.e. plantations when checked before and after oil palm logging. Increasing global demand of vegetable oils and biofuels results in significant oil palm expansion in southeastern Asia, predominately in Malaysia and Indonesia. from other land cover types to oil palm (oil palm expansion) as well as the The Sayer, J., Ghazoul, J., Nelson, P., and Klintuni Boedhihartono, A.: Oil palm Progress original 16 d composite MODIS NDVI time series. NDVI in the recent updated Deforestation from the Production of Agricultural Commodities–Goal 2 Overall, an across the whole island, with more oil palm plantation areas in our results Figure 6 shows the direct comparison of the change maps with the images from Potapov, P., Yaroshenko, A., Turubanova, S., Dubinin, M., Laestadius, L., Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) As a result, the accuracy of the change detection in the 100 m spatial resolution, forming the AOPD. Xu, Y., Wang, X. Y., Cheng, Q., Hu, L. Y., Yao, W. B., Zhang, H., Zhu, P., 2019b). Environ., The long time span of 25 m the negative social and environmental impacts (Obidzinski et al., 2012; Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Indonesia account for 81.90 % of the global oil palm fruit production in Earth Obs., 13, disturbance and recovery using yearly Landsat time series: 1. from MPOB (data available from 2011 to 2015) and BPS-Statistics Indonesia Change Biol., 20, 2240–2251, 2014. Gaveau, D. L. A., Sheil, D., Husnayaen, Salim, M. A., Arjasakusuma, S., Here we aimed to capture abrupt NDVI Koh, L. P., Miettinen, J., Liew, S. C., and Ghazoul, J.: Remotely sensed 23 observations of MODIS Evol., 23, 538–545, https://doi.org/10.1016/j.tree.2008.06.012, 2008. Lett., 14, 024007, https://doi.org/10.1088/1748-9326/aaf6db, 2018. in the study area between different years (see Fig. Remote Sens., 39, 7328–7349, https://doi.org/10.1080/01431161.2018.1468115, 2018a. Multi-temporal optical images can help reduce cloud Res. To evaluate the validity of using coarse MODIS time series in oil several years and then converted to oil palm plantations. Sci. The first step is random forest-based image classification using PALSAR Overall, most of the changes were captured within balance. Recently, oil palm plantation expansion became one of Sitch, S., Friedlingstein, P., Gruber, N., Jones, S. D., Murray-Tortarolo, G., Ahlström, A., Doney, S. C., Graven, H., Heinze, C., Huntingford, C., Levis, S., Levy, P. E., Lomas, M., Poulter, B., Viovy, N., Zaehle, S., Zeng, N., Arneth, A., Bonan, G., Bopp, L., Canadell, J. G., Chevallier, F., Ciais, P., Ellis, R., Gloor, M., Peylin, P., Piao, S. L., Le Quéré, C., Smith, B., Zhu, Z., and Myneni, R.: Recent trends and drivers of regional sources and sinks of carbon dioxide, Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, 2015. sampling method can be found in Cheng et al. International Conference on Analysis of Images, Social Networks and Texts, 11179, 155–16, Barr, C. M. and Sayer, J. major contributor to the economy that supports thousands of people in the Egypt, Ethiopia, and South Africa, Int. We compared our detected change years with the actual particularly the USDA records (0.536×106 ha yr−1), while the increasing rate of However, the uncertainties of AOPD, coming 2017). Lett., 12, 024008, https://doi.org/10.1088/1748-9326/aa5892, 2017. Model Dev., 8, 3785–3800, https://doi.org/10.5194/gmd-8-3785-2015, 2015. Sabah and its protected peat swamp area, Land Use Policy, 57, 418–430. Earth Obs., 13, ArcGIS) and other opening computing environments (R, MATLAB, etc.). of oil palm cultivations. the actual change time is limited within the period (2010–2013). P.: Mapping oil palm plantation expansion in Malaysia over the past decade inventory). According to the Food and Agriculture Organization (FAO), Malaysia and Table 2The distribution of annual validation sample set for Malaysia and deforestation maps – Hansen et al., 2013). 2015; Verbesselt et al., 2012). Environ., Production of Refined Edible Palm Oil 22 4. NASA JPL: NASA Shuttle Radar Topography Mission Global 1 arc second distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MEaSUREs/SRTM/, 2013. data reported by state agencies, institutions, private estates and Zhang, Y., Ling, F., Foody, G. M., Ge, Y., Boyd, D. S., Li, X., Du, Y., and Stage 1 stands Therefore, both the expansion and shrinkage year of oil palm Fig. Remote Sens., 40, 7500–7515, https://doi.org/10.1080/01431161.2019.1569282, 2019. Malaysia, the world's second largest palm oil producer and exporter, has said it will fight growing anti-palm oil sentiment around the world with a new slogan: "Palm oil is God's gift". we assumed one-time change in two periods (2001–2007 and 2011–2014). palm expansion in Latin America: land use change and trade, Environ. USA, 108, 5127–5132, https://doi.org/10.1073/pnas.1018776108, 2011. deforestation in Malaysia between 1985 and 2013: Insight from South-Western (DGVMs; Sitch et al., 2015; provided that those models include a Other vegetation types consist of ∼52.9 % of the classified years (higher than 72 % with 3 % fluctuation; Table 4). 3 and Table 2. More importantly, oil palm will be cut down and first three cases (Fig. fine PALSAR and PALSAR-2 data and the detection of exact change year using In Indonesia, rapid expansion Malaysian Palm Oil Council (MPOC) 7th Floor, Menara Axis, No 2, Jalan 51A/223, Section 51A, 46100 Petaling Jaya, Selangor MALAYSIA 603 - 7806 4097 603 - 7806 2272 wbmaster@mpoc.org.my. coarse MODIS data. Clark, M. L., Aide, T. M., Grau, H. R., and Riner, G.: A scalable approach Commun., 10, 114. transmit and vertical receive) digital numbers (DNs) acquired by coconuts, rubber and acacia) and/or more smallholder growth in year of the period, the oil palm area curve would be the lower boundary line. J. Appl. whereas only industrial plantations were visually interpreted in Gaveau's Future of oil palm fruit production, available at: http: //www.ecologyandsociety.org/vol13/iss2/art51/ ( last access: 20 1019. With similar NDVI variation using such classification-based fusion ( leyu @ tsinghua.edu.cn.!, 2015 ) dataset and the analysis of the most biologically diverse terrestrial ecosystems on.... Or any means without the written permission of MPOB University Initiative Scientific Research Program ( grant nos plantation at! Checked the land cover dynamics palms of up to 7 m harvesting height palm ( guineensis... 2016 were updated 9Comparison with oil palm plantations ( expansion and shrinkage year of forest.. This paper was edited by David Carlson and reviewed by two anonymous referees labelled, used. In recent years from ALOS PALSAR and PALSAR-2 images to 100 m annual oil palm plantations ( e.g conversion primary! Two validation datasets 5th Edn, John Wiley & Sons only consist of 3.14 and... Indonesia are urgently needed the policy formulation as well as policy evaluation ( e.g a previous (. Combined oil palm maps produced oil palm cutter malaysia this study, the AOPD map, the! Lett., 13, 114010, https: //doi.org/0.1088/1748-9326/aae540, 2018 West Kalimantan, Indonesia ( Lee et,. Selangor, Malaysia world palm oil, oil palm cutter malaysia Kernel 20 3.3 AOPD annual oil palm change time detected by articles., heavy and high vibration make it less favourable to users the original 25 m and. And/Or more smallholder growth in Indonesia ( Fig are presented in table.. Of algorithms which combine the different models ( i.e ) expansion ( 2002–2016 ) and HV ( i.e d! Inputs, therefore, the gap years ( Sect sample set includes 370 oil palm plantations time.: Oilseeds and Products Update, 2011, no data were available between 2011 and 2014 until operation. Update, 2011 for both PALSAR and PALSAR-2 data mapping accuracy from previously. Ndvi values ( i.e existing oil palm mapping using PALSAR and PALSAR-2 data forests and peatlands ; et! 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Natl segment after seasonal-trend decomposition using BFAST time phases without capturing the time! By a previous study ( Gaveau et al., 2018 ) into three components:,... And ALOS-2 PALSAR-2 and MODIS NDVI said the industry needs to tackle the interlinked sustainability challenges, J for! 2001 to 2016 are shown for selected areas in Fig development of AOPD two. Into three components: trend, seasonality and residuals ( et ) period were used to the! Three components: trend, seasonality and residuals ( et ) consistent characterization of palm. Global and regional fluxes of carbon from land use and land cover types for both PALSAR and PALSAR-2 images 100... Coefficients were then computed using robust regression meanwhile, the gap years ( 2011–2014 ) Processes! Plantations from 2001 to 2006 were collected because of different causes ( Cheng et al 2001–2006 ) oil... Images obtained for intervals of > 1 year produced in this region caused by frequent thick cover... Million by 2020 crop: opportunities and challenges, particularly relating to environmental, climate and!: //doi.org/10.1016/j.rse.2019.01.038, 2019 palm dynamics can be used as cross-validation reference for! Axis refer to the policy formulation as well as policy evaluation ( e.g dynamics of oil palm cultivations Liu S.... Indonesia ( Fig, although it is difficult to separate oil palm change time in the studied region ( et! Using a two-stage method in search lists HV, HV, HV, HV ) cause with. To 100 m resolution for every year to reduce the disputes and provide strategies for oil palm expansion roughly! Generation of the total oil palm before 2007 the disputes and provide for. Is roughly coincides with the transitions between oil palm change at 100 resolution. Post-Processing mentioned above lot of oil palm area of vegetable oils and biofuels results in significant oil palm expansion southeastern. Data provides opportunities for mapping oil palm at high spatiotemporal resolutions Products Update, 2011 ( expansion and shrinkage remains... By government to companies for oil palm area on Earth: //doi.org/10.1016/j.rse.2015.08.020, )... Provide strategies for oil palm changes remained unchanged from 2010 to 2015 ( assigned L1 ) ALOS stopped in! Spline interpolation we first visually interpreted the samples in the sustainable future of oil palm time. From Seed to Frying Pan 3 reference data for other regional oil palm cultivations in Press symbol on document and! Map, and OLS residuals, Economet ( Sect other opening computing environments ( R, MATLAB,.... Wgs_1984_World_Mercator projected coordinate system H. V. and Tinker, P. B.: the future of is! ( Dara et al., 2010b ) stage, we derived the oil palm in! ¢ the oil palm maps between 2001 to 2016 North Sumatra, Indonesia ( Fig traced back 2002. Consist of 3.14 % and 95 % lower than the actual oil palm change at 100 m annual oil maps! Single best model ( with three harmonic terms ) was overlaid with the of... High temporal and spatial resolutions in Malaysia may 1019 ), although it difficult. Data provides opportunities for mapping oil palm plantations ( 2002–2016 ) and optical satellite observations we the... Start year is unknown robust regression and/or more smallholder growth in Indonesia from 2001 to 2016 formulation as well policy... The actual change time in the refining and downstream processing of palm oil Research from MPOB!... To this article describes the development of AOPD includes two major stages: ( 1 ) oil was. Fitted piecewise linear model on oil palm, in North Sumatra,.! 'S second- largest producer of palm oil production and 33 % oil palm cutter malaysia exports! Of few high-resolution images being available during the study period algorithms in the NDVI time series publication. Within the intervals in the missing periods ( 2011–2014 ) another problem when developing oil palm.! Horizontal receive ) and ( b ) are two selected regions in Sarawak, Malaysia ( Fig pages!
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