Abstract
Aboveground biomass (AGB) and wood volume are two useful parameters in showing the important role of forest in carbon cycling and practicing sustainable forest management. However, monitoring these parameters through conventional method such as destructive sampling has proven to be laborious, cost-ineffective, and time-consuming especially on a large forested area. A more logical approach with acceptable accuracy is to use satellite imagery data such as Landsat 8 to estimate AGB and wood volume of planted forest. The objectives of this study were to identify which spectral bands in Landsat 8 and vegetation indices that most correlated to AGB and wood volume of Acacia mangium plantation. Correlation and simple linear regression analyses were performed to determine the relationships between bands reflectance, vegetation indices, AGB, and wood volume. Results showed that reflectance of band 2 and band 5 is correlated to both AGB and wood volume. Using vegetation indices, correlation between Landsat bands reflectance and studied parameters improved significantly. Normalized difference vegetation index (NDVI) and modified vegetation index (ND52) from band 2 and band 5 showed significantly negative correlations with AGB; r = −0.73 and r = −0.76, respectively. Wood volume was also correlated with NDVI (r = −0.75) and ND52 (r = −0.77). The results suggest that AGB and wood volume of A. mangium plantation can be possibly estimated using NDVI and ND52 at an acceptable level of accuracy.
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Acknowledgements
The authors would like to thank Daiken Sarawak Sdn. Bhd. for allowing their plantation area as the study site. This study was funded by FRGS/STWN02(02)/1142/2014(09) grant.
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Anuar, A.N., Jusoh, I., Suhaili, A. (2018). Estimation of Acacia mangium Aboveground Biomass and Wood Volume Through Landsat 8. In: Saian, R., Abbas, M. (eds) Proceedings of the Second International Conference on the Future of ASEAN (ICoFA) 2017 – Volume 2. Springer, Singapore. https://doi.org/10.1007/978-981-10-8471-3_31
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DOI: https://doi.org/10.1007/978-981-10-8471-3_31
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