Oil palm age estimation using broad-band and narrow-band vegetation indices derived from Sentinel-2 data

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Published: Mar 4, 2024
DOI: https://doi.org/10.14456/apst.2024.30
Keywords:
Oil palm age Remote sensing Vegetation indices Spatial distribution map

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Angeli N. Jarayee
Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia
Helmi Z. M. Shafri
Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia
Yuhao Ang
Department of Civil Engineering and Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia
Yang P. Lee
Geoinformatics Unit, FGV Sdn Bhd, FGV Innovation Centre, Lengkuk Teknologi, Bandar Enstek, Negeri Sembilan, Malaysia
Shahrul A. Bakar
Geoinformatics Unit, FGV Sdn Bhd, FGV Innovation Centre, Lengkuk Teknologi, Bandar Enstek, Negeri Sembilan, Malaysia
Haryati Abidin
Geoinformatics Unit, FGV Sdn Bhd, FGV Innovation Centre, Lengkuk Teknologi, Bandar Enstek, Negeri Sembilan, Malaysia
Hwee S. Lim
School of Physics, Universiti Sains Malaysia (USM), Gelugor, Penang, Malaysia
Rosni Abdullah
School of Computer Sciences, Universiti Sains Malaysia (USM), Gelugor, Penang, Malaysia
Umar U. M. Junaidi
FGV Agri Services Sdn Bhd, Level 9, West, Wisma FGV, Jalan Raja Laut, Kuala Lumpur, Malaysia
Na’aim Samad
Geoinformatics Unit, FGV Sdn Bhd, FGV Innovation Centre, Lengkuk Teknologi, Bandar Enstek, Negeri Sembilan, Malaysia

Abstract

In the past, the monitoring of crops in the agriculture sector was done manually. However, this approach is inconvenient as it consumes time, energy, and money. Various vegetation indices obtained through remote sensing data are utilized to monitor vegetation development. One main factor affecting the oil palm’s production and health is its age. Therefore, this study aimed to determine the relationship between vegetation indices (VIs) and the age of oil palm using polynomial regression and to predict the oil palm age by generating the spatial distribution map. The data used were raw data that consisted of the oil palm age and its boundaries and the satellite data, Sentinel-2 imagery. There were four VIs used in this study: Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge (NDRE), Chlorophyll Content Index (CCI), and Soil Adjusted Vegetation Index (SAVI). Among these VIs, CCI achieved the best overall accuracy with R2 = 0.94, and the age of oil palm can be predicted using the equation y = -4.6062x2+27.864x+14.169. The findings demonstrate that the narrow-band vegetation index can effectively identify the spatial variation in the ages of oil palm trees and serve as an inventory for decision-making.

Article Details

How to Cite
Jarayee, A. N., Shafri, H. Z. M., Ang, Y., Lee, Y. P., Bakar, S. A., Abidin, H., Lim, H. S., Abdullah, R., Junaidi, U. U. M., & Samad, N. (2024). Oil palm age estimation using broad-band and narrow-band vegetation indices derived from Sentinel-2 data. Asia-Pacific Journal of Science and Technology, 29(02), APST–29. https://doi.org/10.14456/apst.2024.30
Issue
Vol. 29 No. 02 (2024): MAR-APR
Section
Research Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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