Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects

In this study, we used the spectral information divergence (SID) and spectral angle mapper (SAM) algorithm classification to identify ~ 40,000 individual trees from 19 mangrove species; these data were collected from 7 sampling points spread across 40,288 ha of the Matang Mangrove Forest Reserve (MM...

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Autores principales:	A.W. Zulfa, K. Norizah, O. Hamdan, I. Faridah-Hanum, P.P. Rhyma, A. Fitrianto
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Zonation pattern Spectroradiometer Anthropogenic Spectral information divergence Spectral angle mapper Matang Mangrove Forest Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/498e0f2615c24d7f83be9a6798f5b40c
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spelling	oai:doaj.org-article:498e0f2615c24d7f83be9a6798f5b40c2021-12-01T04:59:43ZSpectral signature analysis to determine mangrove species delineation structured by anthropogenic effects1470-160X10.1016/j.ecolind.2021.108148https://doaj.org/article/498e0f2615c24d7f83be9a6798f5b40c2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X2100813Xhttps://doaj.org/toc/1470-160XIn this study, we used the spectral information divergence (SID) and spectral angle mapper (SAM) algorithm classification to identify ~ 40,000 individual trees from 19 mangrove species; these data were collected from 7 sampling points spread across 40,288 ha of the Matang Mangrove Forest Reserve (MMFR) in the state of Perak, Malaysia. This information was examined and analysed to answer two questions: (1) can medium resolution of satellite image identify the individual mangrove species (2) how are the distributions of individual species within the mangrove zonation associated with the anthropogenic matrix? Species identification with spectral library derived from the in-situ measurements using the SID algorithm was compared with that derived from the Landsat 8 using the SAM algorithm; it was found that the two methods offered different but complementary information with different rates of accuracy. The observed levels of classification accuracy are at 84.95% and 85.21%, respectively for SID and SAM algorithm classification. The mangrove species distribution has a correlation with the anthropogenic activities, but the distribution occurred randomly without specific zones. All the 19 selected mangrove species are closely related with different correlation by the anthropogenic activities. The use of the SID and SAM algorithms may provide the most promising way of classification for improving the mangrove species identification, with medium resolution of satellite image. Recognising the characteristics of mangrove zonation may give a better understanding of mangrove species appearances and conservation. However, mangrove zonation will remain a daunting mapping task and is a challenge for the ecologists in the future.A.W. ZulfaK. NorizahO. HamdanI. Faridah-HanumP.P. RhymaA. FitriantoElsevierarticleZonation patternSpectroradiometerAnthropogenicSpectral information divergenceSpectral angle mapperMatang Mangrove ForestEcologyQH540-549.5ENEcological Indicators, Vol 130, Iss , Pp 108148- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Zonation pattern Spectroradiometer Anthropogenic Spectral information divergence Spectral angle mapper Matang Mangrove Forest Ecology QH540-549.5
spellingShingle	Zonation pattern Spectroradiometer Anthropogenic Spectral information divergence Spectral angle mapper Matang Mangrove Forest Ecology QH540-549.5 A.W. Zulfa K. Norizah O. Hamdan I. Faridah-Hanum P.P. Rhyma A. Fitrianto Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
description	In this study, we used the spectral information divergence (SID) and spectral angle mapper (SAM) algorithm classification to identify ~ 40,000 individual trees from 19 mangrove species; these data were collected from 7 sampling points spread across 40,288 ha of the Matang Mangrove Forest Reserve (MMFR) in the state of Perak, Malaysia. This information was examined and analysed to answer two questions: (1) can medium resolution of satellite image identify the individual mangrove species (2) how are the distributions of individual species within the mangrove zonation associated with the anthropogenic matrix? Species identification with spectral library derived from the in-situ measurements using the SID algorithm was compared with that derived from the Landsat 8 using the SAM algorithm; it was found that the two methods offered different but complementary information with different rates of accuracy. The observed levels of classification accuracy are at 84.95% and 85.21%, respectively for SID and SAM algorithm classification. The mangrove species distribution has a correlation with the anthropogenic activities, but the distribution occurred randomly without specific zones. All the 19 selected mangrove species are closely related with different correlation by the anthropogenic activities. The use of the SID and SAM algorithms may provide the most promising way of classification for improving the mangrove species identification, with medium resolution of satellite image. Recognising the characteristics of mangrove zonation may give a better understanding of mangrove species appearances and conservation. However, mangrove zonation will remain a daunting mapping task and is a challenge for the ecologists in the future.
format	article
author	A.W. Zulfa K. Norizah O. Hamdan I. Faridah-Hanum P.P. Rhyma A. Fitrianto
author_facet	A.W. Zulfa K. Norizah O. Hamdan I. Faridah-Hanum P.P. Rhyma A. Fitrianto
author_sort	A.W. Zulfa
title	Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
title_short	Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
title_full	Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
title_fullStr	Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
title_full_unstemmed	Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
title_sort	spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/498e0f2615c24d7f83be9a6798f5b40c
work_keys_str_mv	AT awzulfa spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects AT knorizah spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects AT ohamdan spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects AT ifaridahhanum spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects AT pprhyma spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects AT afitrianto spectralsignatureanalysistodeterminemangrovespeciesdelineationstructuredbyanthropogeniceffects
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Spectral signature analysis to determine mangrove species delineation structured by anthropogenic effects

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