Determination of Aboveground Biomass and Standing Wood Volume of Acacia mangium Plantation using Landsat 8 Operational Land Imager
In Sarawak, Acacia mangium is the major species used in the establishment of planted forest. In this era of carbon accounting and trading, measurements of carbon stock and sequestration of forest plantations are essential. For measuring carbon stock in a forest plantation, assessing the amount of ab...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2022
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/39198/5/Aqilah%20Nabihah%20Binti%20Anuar%20ft.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In Sarawak, Acacia mangium is the major species used in the establishment of planted forest. In this era of carbon accounting and trading, measurements of carbon stock and sequestration of forest plantations are essential. For measuring carbon stock in a forest plantation, assessing the amount of aboveground biomass (AGB) and standing wood volume are two very useful forest stand parameters. There are varies of methods that can be used in determining these parameters. Conventional method such as destructive sampling has proved to be laborious and time consuming, especially when involving a large forested area. Recently remote sensing technologies have been broadly used in many forestry applications and Landsat satellite imagery has been applied to predict AGB of forest areas. However, the ability of spectral reflectance value for estimating AGB and timber volume based is not fully understood, especially in Malaysia. This study was carried out to determine the spectral signatures from reflectance bands and vegetation indices that were correlated with AGB and standing wood volume from the study area that made of Acacia mangium. Besides, it was carried out to develop equations for estimating AGB and standing wood volume based on reflectance bands and vegetation indices and finally to map the distribution of estimated aboveground biomass and standing wood volume of the plantation. Field sampling was carried out for ground truthing and to provide baseline data set used to develop equations for estimating the AGB and standing wood volume. Landsat 8 image analyses were carried out to identify the spectral signatures detected from reflectance bands and vegetation indices that were correlated with AGB and standing wood volume of an A. mangium plantation. Results showed that band 5 near-infrared and band 4 from reflectance bands was significantly correlated and weakly correlated, respectively with AGB and standing wood volume. Vegetation indices correlated with AGB and standing wood volume were normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI), atmospherically resistant vegetation index (ARVI), bare soil index (BI) and normalized difference 67 (ND67). Partial Least Square (PLS) regression analyses showed that the developed equations for AGB and standing wood volume yielded R2 of 0.84 and 0.87, respectively. The variables for estimating AGB and standing wood volume were similar, however the coefficients and constants varied. Based on the developed equations the mean AGB and standing wood volume of the A. mangium plantation ranged from 60 to 240 Mg ha-1 and 80 to 400 m3 ha-1, respectively. This study demonstrated that satellite image from Landsat 8 is capable of providing real-time AGB and standing wood volume. It can be used to monitor the forest resources over a large area with minimal ground works. Application of satellite remote sensing can assist forest managers in assessing important forest stand parameters rapidly, and it can be performed repeatedly and accurately. |
|---|