| Issue |
BIO Web Conf.
Volume 73, 2023
5th International Conference on Tropical Resources and Sustainable Sciences (CTReSS 5.0 2023)
|
|
|---|---|---|
| Article Number | 05009 | |
| Number of page(s) | 8 | |
| Section | Sustainability and Technology | |
| DOI | https://doi.org/10.1051/bioconf/20237305009 | |
| Published online | 08 November 2023 | |
Integrating Remote Sensing and GIS Techniques for Accurate Mapping and Analysis of Oil Palm Plantation Distribution in Kelantan: A Case Study
1 Faculty of Earth Science, Universiti Malaysia Kelantan, 17600 Jeli, Kelantan, Malaysia
2 Department of Applied Geology, Faculty of Geological Engineering, Universitas Padjadjaran, Sumedang, Indonesia
3 Department of Science Geology, Faculty of Geological Engineering, Universitas Padjadjaran, Sumedang, Indonesia
* Corresponding author: shaparas@umk.edu.my
The research conducted in Kelantan focused on analysing the distribution of oil palm plantations using remote sensing data and ArcGIS, a Geographic Information System (GIS) platform. The demand for accurate and up-to-date information on oil palm plantations has been increasing due to advancements in technology and the need for effective management of the environment. The study aimed to compare the distribution of oil palm plantations in 2016 and 2021 by using vegetation analysis techniques such as Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Soil-Adjusted Vegetation Index (SAVI). Remote sensing data from Landsat 8, specifically Bands 5, 4, and 2, were utilized to derive these vegetation indices. Ground-truthing data, obtained through GPS coordinates, were employed to increase the accuracy of the analysis. The expansion of oil palm plantations and non-oil palm areas was assessed using the Supervised Classification Maximum Likelihood method. The distribution data of oil palm plantations is highly sought after by oil palm plantation companies and serves public and private purposes, contributing to environmental monitoring and promoting sustainable practices.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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