Articles | Volume 13, issue 3
https://doi.org/10.5194/essd-13-1211-2021
https://doi.org/10.5194/essd-13-1211-2021
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

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Cited articles

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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, https://doi.org/10.17528/cifor/006612, 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, https://doi.org/10.1007/978-3-030-01234-2_49, 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.
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