relation: https://khub.utp.edu.my/scholars/12653/
title: Analysis of the hydrocarbon seepage detection in oil palm vegetation stress using unmanned aerial vehicle (UAV) multispectral data
creator: Asri, N.A.M.
creator: Sakidin, H.
creator: Othman, M.
creator: Matori, A.N.
creator: Ahmad, A.
description: Due to difference pressure beneath the earth, oil and gas or known as hydrocarbon most probably rises to the surface. This presence of oil and gas can be identified through their seepage. The hydrocarbon seepage can lead to an abnormality of soil and dynamism of vegetation health on land surface. This phenomenon can be act as indicator for detecting potential onshore of oil and gas reservoir. Through remote sensing spectral reflectance vegetation index, the abnormality and dynamism of plant growth can be detected. In this study, spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) Multispectral is used to monitor and determine the hydrocarbon seepage detection in oil palm vegetation stress. Based on the experimental design, 12 oil palm trees were simulated with crude oil and remaining three trees were left as control sample which these trees are divided into five sample. The spectra acquisition was taken on the first day, 30th day, 60th day and 90th day of experiment. From the data, the potential visible region and Near - Infrared (NIR) reflectance region being investigated by exerted the statistical analysis to vegetation index which is Normalised Difference Vegetation Index (NDVI) data trends to study the impact of hydrocarbon seepage towards oil palm tree. Detecting hydrocarbon seepage using vegetation reflectance is very useful in oil and gas field as this can be one of the alternative approaches in exploring new oil and gas resources. © 2020 Author(s).
publisher: American Institute of Physics Inc.
date: 2020
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Asri, N.A.M. and Sakidin, H. and Othman, M. and Matori, A.N. and Ahmad, A.  (2020) Analysis of the hydrocarbon seepage detection in oil palm vegetation stress using unmanned aerial vehicle (UAV) multispectral data.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85094574504&doi=10.1063%2f5.0018054&partnerID=40&md5=e75077b2bf8463ce66e9ccb1bc1b9b4d
relation: 10.1063/5.0018054
identifier: 10.1063/5.0018054