Articles | Volume 15, issue 9
https://doi.org/10.5194/essd-15-3991-2023
https://doi.org/10.5194/essd-15-3991-2023
Data description paper
 | 
08 Sep 2023
Data description paper |  | 08 Sep 2023

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

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., https://doi.org/10.5194/essd-2024-157,https://doi.org/10.5194/essd-2024-157, 2024
Revised manuscript accepted for ESSD
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, https://doi.org/10.5194/essd-13-5353-2021,https://doi.org/10.5194/essd-13-5353-2021, 2021
Short summary
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
Earth Syst. Sci. Data, 13, 1211–1231, https://doi.org/10.5194/essd-13-1211-2021,https://doi.org/10.5194/essd-13-1211-2021, 2021
Short summary

Related subject area

Domain: ESSD – Land | Subject: Land Cover and Land Use
Monsoon Asia Rice Calendar (MARC): a gridded rice calendar in monsoon Asia based on Sentinel-1 and Sentinel-2 images
Xin Zhao, Kazuya Nishina, Haruka Izumisawa, Yuji Masutomi, Seima Osako, and Shuhei Yamamoto
Earth Syst. Sci. Data, 16, 3893–3911, https://doi.org/10.5194/essd-16-3893-2024,https://doi.org/10.5194/essd-16-3893-2024, 2024
Short summary
A 100 m gridded population dataset of China's seventh census using ensemble learning and big geospatial data
Yuehong Chen, Congcong Xu, Yong Ge, Xiaoxiang Zhang, and Ya'nan Zhou
Earth Syst. Sci. Data, 16, 3705–3718, https://doi.org/10.5194/essd-16-3705-2024,https://doi.org/10.5194/essd-16-3705-2024, 2024
Short summary
Annual time-series 1 km maps of crop area and types in the conterminous US (CropAT-US): cropping diversity changes during 1850–2021
Shuchao Ye, Peiyu Cao, and Chaoqun Lu
Earth Syst. Sci. Data, 16, 3453–3470, https://doi.org/10.5194/essd-16-3453-2024,https://doi.org/10.5194/essd-16-3453-2024, 2024
Short summary
Retrieval of dominant methane (CH4) emission sources, the first high-resolution (1–2 m) dataset of storage tanks of China in 2000–2021
Fang Chen, Lei Wang, Yu Wang, Haiying Zhang, Ning Wang, Pengfei Ma, and Bo Yu
Earth Syst. Sci. Data, 16, 3369–3382, https://doi.org/10.5194/essd-16-3369-2024,https://doi.org/10.5194/essd-16-3369-2024, 2024
Short summary
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
Xingyi Huang, Yuwei Yin, Luwei Feng, Xiaoye Tong, Xiaoxin Zhang, Jiangrong Li, and Feng Tian
Earth Syst. Sci. Data, 16, 3307–3332, https://doi.org/10.5194/essd-16-3307-2024,https://doi.org/10.5194/essd-16-3307-2024, 2024
Short summary

Cited articles

Alouw, J. and Wulandari, S.: Present status and outlook of coconut development in Indonesia, in: IOP Conf. Ser. Earth and Environ. Sci., 418, 012035, https://doi.org/10.1088/1755-1315/418/1/012035, 2020. 
Burnett, M. W., White, T. D., McCauley, D. J., De Leo, G. A., and Micheli, F.: Quantifying coconut palm extent on Pacific islands using spectral and textural analysis of very high resolution imagery, Int. J. Remote Sens., 40, 7329–7355, 2019. 
Carr, P., Trevail, A., Bárrios, S., Clubbe, C., Freeman, R., Koldewey, H. J., Votier, S. C., Wilkinson, T., and Nicoll, M. A.: Potential benefits to breeding seabirds of converting abandoned coconut plantations to native habitats after invasive predator eradication, Restor. Ecol., 29, e13386, https://doi.org/10.1111/rec.13386, 2021. 
Chan, E. and Elevitch, C. R.: Cocos nucifera (coconut), Species profiles for Pacific Island agroforestry, 2, 1–27, 2006. 
Coppens D'Eeckenbrugge, G., Duong, N. T. K., and Ullivari, A.: Geographic Information Systems, chap. 2, Where we are today, Biodiversity International, ISBN 978-92-9043-984-4, 2018. 
Download
Short summary
The spatial extent of coconut palm is understudied despite its increasing demand and associated impacts. We present the first global coconut palm layer at 20 m resolution. The layer was produced using deep learning and remotely sensed data. The global coconut area estimate is 12.31 Mha for dense coconut palm, but the estimate is 3 times larger when sparse coconut palm is considered. This means that coconut production can likely increase on the lands currently allocated to coconut palm.
Altmetrics
Final-revised paper
Preprint