Preprints
https://doi.org/10.5194/essd-2024-157
https://doi.org/10.5194/essd-2024-157
15 May 2024
 | 15 May 2024
Status: this preprint is currently under review for the journal ESSD.

Global mapping of oil palm planting year from 1990 to 2021

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

Abstract. Oil palm is a controversial crop, primarily because it is associated with negative environmental impacts such as tropical deforestation. Mapping the crop and its characteristics, such as age, is crucial for informing public and policy discussions regarding these impacts. Oil palm has received substantial mapping efforts, but up-to-date accurate oil palm maps for both extent and age are essential for monitoring impacts and informing concomitant debate. Here, we present a 10-meter resolution global map of industrial and smallholder oil palm, developed using Sentinel-1 data for the years 2016–2021 and a deep learning model based on convolutional neural networks. In addition, we used Landsat-5, -7, and -8 to estimate the planting year from 1990 to 2021 at a 30-meter spatial resolution. The planting year indicates the year of establishment for an oil palm plantation as of 2021, either newly planted or replanted oil palm in an existing plantation. We validated the oil palm extent layer using 17,812 randomly distributed reference points. The accuracy of the planting year layer was assessed using field data collected from 5,831 industrial parcels and 1,012 smallholder plantations distributed throughout the oil palm growing area. We found oil palm plantations covering a total mapped area of 23.98 Mha, and our area estimates are 16.66 ± 0.25 Mha of industrial and 7.59 ± 0.29 Mha of smallholder oil palm worldwide. The producers’ and users’ accuracy is 91.9 ± 3.4 % and 91.8 ± 1.0 % for industrial plantations, and 72.7 ± 1.3 % and 75.7 ± 2.5 % for smallholders, which improves upon a previous global oil palm dataset, particularly in terms of omission of oil palm. The overall mean error between estimated planting year and field data was -0.24 years and the root-mean-square error was 2.65 years, but the agreement was lower for smallholders. Mapping the extent and planting year of smallholder plantations remains challenging, particularly for wild and sparsely planted oil palm, and future mapping efforts should focus on these specific types of plantations. The average oil palm plantation age was 14.1 years, and the area of oil palm over 20 years was 6.28 Mha. Given that oil palm plantations are typically replanted after 25 years, our findings indicate that this area will require replanting within the coming decade, starting from 2021. Our dataset provides valuable input for optimal land use planning to meet the growing global demand for vegetable oils. The global oil palm extent layer for the year 2021 and the planting year layer from 1990 to 2021 can be found at https://doi.org/10.5281/zenodo.11034131 (Descals, 2024).

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

Status: open (until 01 Aug 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2024-157', Denis murphy, 19 May 2024 reply
  • RC1: 'Comment on essd-2024-157', Anonymous Referee #1, 13 Jun 2024 reply
Adrià Descals, David L. A. Gaveau, Serge Wich, Zoltan Szantoi, and Erik Meijaard

Data sets

Global oil palm extent and planting year from 1990 to 2021 Adrià Descals https://doi.org/10.5281/zenodo.11034131

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

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Short summary
This study provides a 10-m global oil palm extent layer for 2021 and a 30-m oil palm planting year layer from 1990 to 2021. The oil palm extent layer was produced using a convolutional neural network that identified industrial and smallholder plantations using Sentinel-1 data. The oil palm planting year was developed using a methodology specifically designed to detect the early stages of oil palm development in the Landsat time series.
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