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This paper focuses on mapping and quantifying the rubberwood plantation’s volume by using the UPM-APSB’s AISA airborne hyperspectral sensor in Lebuh Silikon, Universiti Putra Malaysia, Serdang, Malaysia. The image and field spectral knowledge of the individual standing rubber tree was obtained by image analysis and field work, respectively. The correlations between the different crown area of rubber trees and the diameter at breast height with the ancillary data were obtained. A supervised classification method based on Spectral Angle Mapper (SAM) and spectral matching knowledge was presented and applied to classify the entire image leading towards an estimation of rubberwood volume for the study area.  It shows that the rubberwood volume of an old matured unmanaged rubber plantation can easily be predicted with high accuracy obtained through this approach. A total of 20 rubber tree samples were identified, quantified and mapped representing a standing rubberwood volume of 91.44 m3 /ha and a mapping accuracy of 89.84%. The study demonstrated that UPM-APSB’s AISA airborne hyperspectral sensor is capable of mapping individual rubber trees and estimate the standing ruberwood volume with an acceptable accuracy.</p

New Approaches in Estimating Rubberwood Standing Volume Using Airborne Hyperspectral Sensing