Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin

Oil palm is crucial to ecology, the environment, and the economy. If improperly managed and monitored, unrestrained oil palm activities could contribute to deforestation, which can seriously affect the environment. Remote sensing provides a means to effectively detect and map oil palms from space. R...

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Main Author:	Sharuddin, Nurul Ain Nabilah
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Aerial geography Agriculture and the environment
Online Access:	https://ir.uitm.edu.my/id/eprint/69181/1/69181.pdf
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id	my-uitm-ir.69181
record_format	uketd_dc
spelling	my-uitm-ir.691812023-05-19T09:12:18Z Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin 2022 Sharuddin, Nurul Ain Nabilah Aerial geography Agriculture and the environment Oil palm is crucial to ecology, the environment, and the economy. If improperly managed and monitored, unrestrained oil palm activities could contribute to deforestation, which can seriously affect the environment. Remote sensing provides a means to effectively detect and map oil palms from space. Recent developments in big data and cloud computing enable quick mapping on a wide scale. However, the use of cloud computing remains limited and challenging in Malaysia. Thus, this study used image Sentinel 2 processed in Google Earth Engine (GEE) to classify mature and immature oil palms' land cover in TDM Plantation, Terengganu. Four (4) machine learning algorithms are used in classification, such as Random Forest (RF), smile Classification and Regression Tree (smileCART), Gradient Tree Boost (GTB), and Minimum Distance (MD). Overall accuracy (OA) and kappa produced by Random RF, GTB, smileCART and MD were OA = 85.14%, kappa = 0.80, OA = 84.00%, kappa = 0.78 , OA = 83.42%, kappa = 0.77 and OA = 78.29%, kappa = 0.71 respectively, for 6 classes (water body, built up, mature, immature, bare land and forest). Therefore, image Sentinel-2 efficiently detected mature and immature oil palms' land cover using the RF algorithm implemented in GEE. 2022 Thesis https://ir.uitm.edu.my/id/eprint/69181/ https://ir.uitm.edu.my/id/eprint/69181/1/69181.pdf text en public degree Universiti Teknologi MARA. Perlis Faculty of Architecture, Planning and Surveying
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Aerial geography Agriculture and the environment
spellingShingle	Aerial geography Agriculture and the environment Sharuddin, Nurul Ain Nabilah Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
description	Oil palm is crucial to ecology, the environment, and the economy. If improperly managed and monitored, unrestrained oil palm activities could contribute to deforestation, which can seriously affect the environment. Remote sensing provides a means to effectively detect and map oil palms from space. Recent developments in big data and cloud computing enable quick mapping on a wide scale. However, the use of cloud computing remains limited and challenging in Malaysia. Thus, this study used image Sentinel 2 processed in Google Earth Engine (GEE) to classify mature and immature oil palms' land cover in TDM Plantation, Terengganu. Four (4) machine learning algorithms are used in classification, such as Random Forest (RF), smile Classification and Regression Tree (smileCART), Gradient Tree Boost (GTB), and Minimum Distance (MD). Overall accuracy (OA) and kappa produced by Random RF, GTB, smileCART and MD were OA = 85.14%, kappa = 0.80, OA = 84.00%, kappa = 0.78 , OA = 83.42%, kappa = 0.77 and OA = 78.29%, kappa = 0.71 respectively, for 6 classes (water body, built up, mature, immature, bare land and forest). Therefore, image Sentinel-2 efficiently detected mature and immature oil palms' land cover using the RF algorithm implemented in GEE.
format	Thesis
qualification_level	Bachelor degree
author	Sharuddin, Nurul Ain Nabilah
author_facet	Sharuddin, Nurul Ain Nabilah
author_sort	Sharuddin, Nurul Ain Nabilah
title	Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
title_short	Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
title_full	Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
title_fullStr	Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
title_full_unstemmed	Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin
title_sort	detection of mature and immature oil palm from image sentinel-2 using google earth engine (gee) / nurul ain nabilah sharuddin
granting_institution	Universiti Teknologi MARA. Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2022
url	https://ir.uitm.edu.my/id/eprint/69181/1/69181.pdf
_version_	1783735852946423808

Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin

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