Applicability of rapideye satellite imagery in mapping Mangrove vegetation species at Matang Mangrove Forest Reserve, Perak, Malaysia

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7 Citations (Scopus)

Abstract

Mangroves are typically made up of salt tolerant species of vegetation with great diversity of flora and fauna which is mainly found in tropical and subtropical climate country. However, these forest ecosystems have been declining over time due to the various kinds of direct and indirect pressure. Thus, there is increasing need and efforts to monitor and assess this ecosystem for better conservation and management. In this study, multispectral RapidEye satellite image was analysed to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia. The Maximum Likelihood Classifier (MLC) was used to classify the mangrove vegetation species with integration of Normalized Difference Vegetation Index (NDVI) using NDVIRed and NDVIRed Edge data. Eleven species of mangrove vegetation were found within the study area including from the genus of Rhizophora, Avicennia, Bruguiera, Sonneratia and Xylocarpus. The overall classification accuracy assessment of RapidEye multispectral image integrated with NDVIRed Edge was higher at 87.5% with overall kappa statistics recorded of 0.85 compared to with employment of NDVIRed at 85% and kappa statistics of 0.80. The results indicated the applicability of Red Edge band in the RapidEye satellite imagery in combination with ancillary and field data to classify the mangrove species within the study area. It also helps for better management and conservation process to ensure the sustainability of these valuable resources.

Original languageEnglish
Pages (from-to)123-136
Number of pages14
JournalJournal of Environmental Science and Technology
Volume7
Issue number2
DOIs
Publication statusPublished - 2014

Fingerprint

satellite imagery
mangrove
vegetation
accuracy assessment
multispectral image
NDVI
forest ecosystem
RapidEye
forest reserve
flora
sustainability
fauna
salt
ecosystem
climate
resource
statistics

Keywords

  • Classification
  • Matang mangrove forest reserve
  • Normalized difference vegetation index
  • RapidEye satellite imagery
  • Red Edge

ASJC Scopus subject areas

  • Environmental Science(all)

Cite this

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title = "Applicability of rapideye satellite imagery in mapping Mangrove vegetation species at Matang Mangrove Forest Reserve, Perak, Malaysia",
abstract = "Mangroves are typically made up of salt tolerant species of vegetation with great diversity of flora and fauna which is mainly found in tropical and subtropical climate country. However, these forest ecosystems have been declining over time due to the various kinds of direct and indirect pressure. Thus, there is increasing need and efforts to monitor and assess this ecosystem for better conservation and management. In this study, multispectral RapidEye satellite image was analysed to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia. The Maximum Likelihood Classifier (MLC) was used to classify the mangrove vegetation species with integration of Normalized Difference Vegetation Index (NDVI) using NDVIRed and NDVIRed Edge data. Eleven species of mangrove vegetation were found within the study area including from the genus of Rhizophora, Avicennia, Bruguiera, Sonneratia and Xylocarpus. The overall classification accuracy assessment of RapidEye multispectral image integrated with NDVIRed Edge was higher at 87.5{\%} with overall kappa statistics recorded of 0.85 compared to with employment of NDVIRed at 85{\%} and kappa statistics of 0.80. The results indicated the applicability of Red Edge band in the RapidEye satellite imagery in combination with ancillary and field data to classify the mangrove species within the study area. It also helps for better management and conservation process to ensure the sustainability of these valuable resources.",
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author = "Roslani, {M. A.} and {Ahmad Mustapha}, Muzzneena and Tukimat Lihan and {Wan Ahmad}, {Wan Juliana}",
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AU - Wan Ahmad, Wan Juliana

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AB - Mangroves are typically made up of salt tolerant species of vegetation with great diversity of flora and fauna which is mainly found in tropical and subtropical climate country. However, these forest ecosystems have been declining over time due to the various kinds of direct and indirect pressure. Thus, there is increasing need and efforts to monitor and assess this ecosystem for better conservation and management. In this study, multispectral RapidEye satellite image was analysed to identify the mangrove vegetation species within the Matang Mangrove Forest Reserve in Perak, Malaysia. The Maximum Likelihood Classifier (MLC) was used to classify the mangrove vegetation species with integration of Normalized Difference Vegetation Index (NDVI) using NDVIRed and NDVIRed Edge data. Eleven species of mangrove vegetation were found within the study area including from the genus of Rhizophora, Avicennia, Bruguiera, Sonneratia and Xylocarpus. The overall classification accuracy assessment of RapidEye multispectral image integrated with NDVIRed Edge was higher at 87.5% with overall kappa statistics recorded of 0.85 compared to with employment of NDVIRed at 85% and kappa statistics of 0.80. The results indicated the applicability of Red Edge band in the RapidEye satellite imagery in combination with ancillary and field data to classify the mangrove species within the study area. It also helps for better management and conservation process to ensure the sustainability of these valuable resources.

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