Articles | Volume 13, issue 3
Data description paper
24 Mar 2021
Data description paper |  | 24 Mar 2021

High-resolution global map of smallholder and industrial closed-canopy oil palm plantations

Adrià Descals, Serge Wich, Erik Meijaard, David L. A. Gaveau, Stephen Peedell, and Zoltan Szantoi

Related authors

Global mapping of oil palm planting year from 1990 to 2021
Adrià Descals, David L. A. Gaveau, Serge Wich, Zoltan Szantoi, and Erik Meijaard
Earth Syst. Sci. Data Discuss.,,, 2024
Preprint under review for ESSD
Short summary
High-resolution global map of closed-canopy coconut palm
Adrià Descals, Serge Wich, Zoltan Szantoi, Matthew J. Struebig, Rona Dennis, Zoe Hatton, Thina Ariffin, Nabillah Unus, David L. A. Gaveau, and Erik Meijaard
Earth Syst. Sci. Data, 15, 3991–4010,,, 2023
Short summary
Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
David L. A. Gaveau, Adrià Descals, Mohammad A. Salim, Douglas Sheil, and Sean Sloan
Earth Syst. Sci. Data, 13, 5353–5368,,, 2021
Short summary

Related subject area

Land Cover and Land Use
The ABoVE L-band and P-band airborne synthetic aperture radar surveys
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624,,, 2024
Short summary
A 30 m annual cropland dataset of China from 1986 to 2021
Ying Tu, Shengbiao Wu, Bin Chen, Qihao Weng, Yuqi Bai, Jun Yang, Le Yu, and Bing Xu
Earth Syst. Sci. Data, 16, 2297–2316,,, 2024
Short summary
Global 1 km land surface parameters for kilometer-scale Earth system modeling
Lingcheng Li, Gautam Bisht, Dalei Hao, and L. Ruby Leung
Earth Syst. Sci. Data, 16, 2007–2032,,, 2024
Short summary
ChinaRiceCalendar – seasonal crop calendars for early-, middle-, and late-season rice in China
Hui Li, Xiaobo Wang, Shaoqiang Wang, Jinyuan Liu, Yuanyuan Liu, Zhenhai Liu, Shiliang Chen, Qinyi Wang, Tongtong Zhu, Lunche Wang, and Lizhe Wang
Earth Syst. Sci. Data, 16, 1689–1701,,, 2024
Short summary
Harmonized European Union subnational crop statistics can reveal climate impacts and crop cultivation shifts
Giulia Ronchetti, Luigi Nisini Scacchiafichi, Lorenzo Seguini, Iacopo Cerrani, and Marijn van der Velde
Earth Syst. Sci. Data, 16, 1623–1649,,, 2024
Short summary

Cited articles

Austin, K. G., Schwantes, A., Gu, Y., and Kasibhatla, P. S.: What causes deforestation in Indonesia?, Environ. Res. Lett., 14, 024007,, 2019. 
Bronkhorst, E., Cavallo, E., van Dorth tot Medler, M., Klinghammer, S., Smit, H. H., Gijsenbergh, A., and van der Laan, C.: Current practices and innovations in smallholder palm oil finance in Indonesia and Malaysia: Long-term financing solutions to promote sustainable supply chains, Center for International Forestry Research (CIFOR), Bogor, Indonesia,, 2017. 
Byerlee, D., Falcon, W. P., and Naylor, R.: The tropical oil crop revolution: food, feed, fuel, and forests, Oxford University Press, Oxford, UK, 2017. 
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., and Yuille, A. L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, IEEE T. Pattern Anal., 40, 834–848, 2017. 
Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., and Adam, H.: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation, in: Computer Vision – ECCV 2018. ECCV 2018. Lecture Notes in Computer Science, vol 11211, edited by: Ferrari, V., Hebert, M., Sminchisescu, C., and Weiss, Y., Springer, Cham,, 2018. 
Short summary
Decision-making for sustainable vegetable oil production requires accurate global oil crop maps. We used high-resolution satellite data to train a deep learning model that accurately classified industrial and smallholder oil palm, the main oil-producing crop. Our results outperformed previous studies and proved the suitability of deep learning for land use mapping. The global oil palm area was 21±0.42 Mha for 2019; however, young and sparse plantations were not included in this estimate.
Final-revised paper