Vegetation indices of Acacia mangium using Landsat 8 Operational Land Imager

Ismail Jusoh, . and Aqilah Nabihah Anuar, . and Affendi Suhaili, . Vegetation indices of Acacia mangium using Landsat 8 Operational Land Imager. pp. 57-69. ISSN 2672-7226

Monitoring a forest plantation using satellite remote sensing would be an attractive alternative compared to using a conventional method such as ground-based observations. Ground-based monitoring can be laborious and time-consuming especially when it involves a large forested area. In contrast satellite remote sensing can provide a synoptic view of the whole area in a single dataset. However the ability to relate the relationship between spectral reflectance signature from Landsat 8 and the planted Acacia mangium is not fully understood especially in Malaysia. This study was conducted to determine the vegetation reflectance band and indices to distinguish between A. mangium canopy and other land covers. Landsat 8 OLI image acquisition and analyses were performed to identify detected reflectance bands and vegetation indices (VIs) of the A. mangium plantation of four years old and above. Results showed that out of seven bands only band 7 or short-wave infrared 2 is the most suitable spectral band for detecting A. mangium trees of age four years and older. The spatial distribution of land cover illustrated that 55.1 of the plantation area is covered with A. mangium. The addition of NDVI EVI MSAVI and ND43 improved different land cover distinguishing capabilities. The higher the values of VIs the denser the A. mangium cover and the negative values illustrate less vegetation cover and open canopy within the study area. The VI shows a clear profile in which bare soil and water bodies are clearly defined against A. mangium canopy. A land cover map can be generated based on band 7 spectral response and VIs and provides realtime distribution of A. mangium. It can be used to monitor forest resources over a large area with minimal groundwork.

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Abstract

Monitoring a forest plantation using satellite remote sensing would be an attractive alternative compared to using a conventional method such as ground-based observations. Ground-based monitoring can be laborious and time-consuming especially when it involves a large forested area. In contrast satellite remote sensing can provide a synoptic view of the whole area in a single dataset. However the ability to relate the relationship between spectral reflectance signature from Landsat 8 and the planted Acacia mangium is not fully understood especially in Malaysia. This study was conducted to determine the vegetation reflectance band and indices to distinguish between A. mangium canopy and other land covers. Landsat 8 OLI image acquisition and analyses were performed to identify detected reflectance bands and vegetation indices (VIs) of the A. mangium plantation of four years old and above. Results showed that out of seven bands only band 7 or short-wave infrared 2 is the most suitable spectral band for detecting A. mangium trees of age four years and older. The spatial distribution of land cover illustrated that 55.1 of the plantation area is covered with A. mangium. The addition of NDVI EVI MSAVI and ND43 improved different land cover distinguishing capabilities. The higher the values of VIs the denser the A. mangium cover and the negative values illustrate less vegetation cover and open canopy within the study area. The VI shows a clear profile in which bare soil and water bodies are clearly defined against A. mangium canopy. A land cover map can be generated based on band 7 spectral response and VIs and provides realtime distribution of A. mangium. It can be used to monitor forest resources over a large area with minimal groundwork.

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Item Type:	Article
AGROVOC Term:	Acacia mangium
AGROVOC Term:	Forest plantations
AGROVOC Term:	Remote sensing
AGROVOC Term:	Vegetation
AGROVOC Term:	Earth observation satellites
AGROVOC Term:	Forest resources
AGROVOC Term:	Environmental monitoring
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/10735

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