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

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 relat...

Full description

Bibliographic Details
Main Authors: Hassan, N., Hashim, M., Numata, S., Tarmidi, M. Z.
Other Authors: Pandey, P. C.
Format: Book Section
Published: Elsevier 2020
Subjects:
_version_ 1796865712211361792
author Hassan, N.
Hashim, M.
Numata, S.
Tarmidi, M. Z.
author2 Pandey, P. C.
author_facet Pandey, P. C.
Hassan, N.
Hashim, M.
Numata, S.
Tarmidi, M. Z.
author_sort Hassan, N.
collection ePrints
description 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
first_indexed 2024-03-05T21:01:14Z
format Book Section
id utm.eprints-93883
institution Universiti Teknologi Malaysia - ePrints
last_indexed 2024-03-05T21:01:14Z
publishDate 2020
publisher Elsevier
record_format dspace
spelling utm.eprints-938832022-01-31T08:37:08Z http://eprints.utm.my/93883/ Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems Hassan, N. Hashim, M. Numata, S. Tarmidi, M. Z. G109.5 Global Positioning System 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 Elsevier Pandey, P. C. Srivastava, P. K. Bhattacharya, B. Balzter, H. Petropoulos, G. P. 2020-08 Book Section PeerReviewed 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 https://doi.org/10.1016/B978-0-08-102894-0.00006-1 DOI: 10.1016/B978-0-08-102894-0.00006-1
spellingShingle G109.5 Global Positioning System
Hassan, N.
Hashim, M.
Numata, S.
Tarmidi, M. Z.
Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title_full Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title_fullStr Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title_full_unstemmed Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title_short Estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
title_sort estimation of chengal trees relative abundance using coarse spatial resolution hyperspectral systems
topic G109.5 Global Positioning System
work_keys_str_mv AT hassann estimationofchengaltreesrelativeabundanceusingcoarsespatialresolutionhyperspectralsystems
AT hashimm estimationofchengaltreesrelativeabundanceusingcoarsespatialresolutionhyperspectralsystems
AT numatas estimationofchengaltreesrelativeabundanceusingcoarsespatialresolutionhyperspectralsystems
AT tarmidimz estimationofchengaltreesrelativeabundanceusingcoarsespatialresolutionhyperspectralsystems