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Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems

Hassan, N. and Hashim, M. and Numata, S. and Tarmidi, M. Z. (2020) Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems. In: Hyperspectral Remote Sensing Theory and Applications A volume in Earth Observation. Elsevier, pp. 107-120. ISBN 978-0-08-102894-0

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Official URL: https://doi.org/10.1016/B978-0-08-102894-0.00006-1


Tree species relative abundance estimation of a tropical rainforest is quite a challenge especially when coarse spatial resolution data is utilized. In this chapter, modified canopy fractional cover (mCFC) was enhanced from the canopy fractional cover (CFC) model in estimation of chengal trees relative abundance in Hyperion EO-1 data, which is coarse spatial resolution hyperspectral data. Besides, mixture tuned matched filtering (MTMF) was employed to Hyperion EO-1 data to test the ability of mCFC in estimating the chengal trees relative abundance. Thus we hypothesized that mCFC has better capability to estimate the abundance of chengal trees more accurately than MTMF, while MTMF has better capability in estimating undisturbed forest. The accuracy of mCFC model (r2 = 0.667, P< 0.05) shows that mCFC has capability to estimate relative abundance of chengal trees better that MTMF. Therefore it can be concluded that the relative abundance of certain tree species extracted from Hyperion EO-1 satellite data using modified CFC is an obtrusive approach for identifying tree species composition

Item Type:Book Section
Uncontrolled Keywords:hyperspectral remote sensing, LiDAR, multi-spectral data
Subjects:G Geography. Anthropology. Recreation > G Geography (General) > G109.5 Global Positioning System
Divisions:Built Environment
ID Code:93883
Deposited By: Narimah Nawil
Deposited On:31 Jan 2022 16:37
Last Modified:31 Jan 2022 16:37

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