Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad

Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has...

Full description

Saved in:

Bibliographic Details
Main Author:	Ahad, Mohamad Firdaus
Format:	Thesis
Language:	English
Published:	2020
Subjects:	GB Physical geography
Online Access:	https://ir.uitm.edu.my/id/eprint/33151/1/33151.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.33151
record_format	uketd_dc
spelling	my-uitm-ir.331512020-08-04T02:55:20Z Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad 2020-08-04 Ahad, Mohamad Firdaus GB Physical geography Geomorphology. Landforms. Terrain Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has been reported in several studies. Rubber growth is important to take care to ensure the absorption of carbon dioxide can be increased. However, in this study there are some area not fully covered by rubber trees. To measure how much area had been covered and does not been covered by the rubber trees, LAI measurement can be used to calculate the canopy. The aim of this study is to evaluate leaf area index on rubber leaves using an unmanned aerial vehicle images at Research Station RRIM, Malaysian Rubber Board (MRB) Kota Tinggi, Johor and the objectives is to produce Leaf Area Index map using drone based multispectral images and to determine healthiness of rubber tree based on leaf area index map. The methods for extracting the vegetation LAI is the vegetation index method. Leaf area index can be identified by the red, blue, green band and little at the near infrared band with using raster calculator. As a result, the map LAI for rubber tree using drone based multispectral images will produce and the healthiness of rubber tree can be identify based on the leaf area index map. 2020-08 Thesis https://ir.uitm.edu.my/id/eprint/33151/ https://ir.uitm.edu.my/id/eprint/33151/1/33151.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surverying (R)
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	GB Physical geography GB Physical geography
spellingShingle	GB Physical geography GB Physical geography Ahad, Mohamad Firdaus Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
description	Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has been reported in several studies. Rubber growth is important to take care to ensure the absorption of carbon dioxide can be increased. However, in this study there are some area not fully covered by rubber trees. To measure how much area had been covered and does not been covered by the rubber trees, LAI measurement can be used to calculate the canopy. The aim of this study is to evaluate leaf area index on rubber leaves using an unmanned aerial vehicle images at Research Station RRIM, Malaysian Rubber Board (MRB) Kota Tinggi, Johor and the objectives is to produce Leaf Area Index map using drone based multispectral images and to determine healthiness of rubber tree based on leaf area index map. The methods for extracting the vegetation LAI is the vegetation index method. Leaf area index can be identified by the red, blue, green band and little at the near infrared band with using raster calculator. As a result, the map LAI for rubber tree using drone based multispectral images will produce and the healthiness of rubber tree can be identify based on the leaf area index map.
format	Thesis
qualification_level	Bachelor degree
author	Ahad, Mohamad Firdaus
author_facet	Ahad, Mohamad Firdaus
author_sort	Ahad, Mohamad Firdaus
title	Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
title_short	Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
title_full	Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
title_fullStr	Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
title_full_unstemmed	Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad
title_sort	leaf area index estimation of rubber tree using drone based multispectral images / mohamad firdaus ahad
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surverying (R)
publishDate	2020
url	https://ir.uitm.edu.my/id/eprint/33151/1/33151.pdf
_version_	1783734223946907648

Leaf area index estimation of rubber tree using drone based multispectral images / Mohamad Firdaus Ahad

Similar Items