Remote sensing indices for mangrove health assessment
This paper is attempts to review the application of remote sensing technology for mangrove health assessment derived from spectral information. One of the most valuable forest lands in the coastal area is mangrove forests. Mangroves are economically and environmentally important for maintaining gl...
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| Format: | Article |
| Language: | English |
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Institution of Geospatial and Remote Sensing Malaysia
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/62952/ http://psasir.upm.edu.my/id/eprint/62952/1/Remote%20sensing%20indices%20for%20mangrove%20health%20assessment.pdf |
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| author | Mohd Razali, Sheriza Suk-ueng, Krittawit Nuruddin, Ahmad Ainuddin |
| author_facet | Mohd Razali, Sheriza Suk-ueng, Krittawit Nuruddin, Ahmad Ainuddin |
| author_sort | Mohd Razali, Sheriza |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This paper is attempts to review the application of remote sensing technology for mangrove health assessment derived from spectral information. One of the most valuable forest lands in the coastal area is mangrove forests. Mangroves are economically and environmentally important for maintaining global conservation. Increase in population is putting high pressure in coastal areas with conversion of many mangrove forests to other land usages, including infrastructure, aquaculture, rice and salt production. The conversion affects water quality and hence, increases pressure to mangrove health. The health of mangrove can be assessed by employing remote sensing indices. Remote sensing technology is a very important technique for assessing mangrove health by derivation of spectral reflectance and conversion into mathematical equation. Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) are discussed in this paper. This paper also highlights the potential of the indices to be integrated with drought index for drought modelling systems. In addition, it explores various cases studied in Peninsular Malaysia and elsewhere to emphasise the utilisation of the indices in various locations of mangrove areas around the globe. |
| first_indexed | 2025-11-15T11:13:59Z |
| format | Article |
| id | upm-62952 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:13:59Z |
| publishDate | 2017 |
| publisher | Institution of Geospatial and Remote Sensing Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-629522018-10-22T08:48:48Z http://psasir.upm.edu.my/id/eprint/62952/ Remote sensing indices for mangrove health assessment Mohd Razali, Sheriza Suk-ueng, Krittawit Nuruddin, Ahmad Ainuddin This paper is attempts to review the application of remote sensing technology for mangrove health assessment derived from spectral information. One of the most valuable forest lands in the coastal area is mangrove forests. Mangroves are economically and environmentally important for maintaining global conservation. Increase in population is putting high pressure in coastal areas with conversion of many mangrove forests to other land usages, including infrastructure, aquaculture, rice and salt production. The conversion affects water quality and hence, increases pressure to mangrove health. The health of mangrove can be assessed by employing remote sensing indices. Remote sensing technology is a very important technique for assessing mangrove health by derivation of spectral reflectance and conversion into mathematical equation. Normalised Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) are discussed in this paper. This paper also highlights the potential of the indices to be integrated with drought index for drought modelling systems. In addition, it explores various cases studied in Peninsular Malaysia and elsewhere to emphasise the utilisation of the indices in various locations of mangrove areas around the globe. Institution of Geospatial and Remote Sensing Malaysia 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62952/1/Remote%20sensing%20indices%20for%20mangrove%20health%20assessment.pdf Mohd Razali, Sheriza and Suk-ueng, Krittawit and Nuruddin, Ahmad Ainuddin (2017) Remote sensing indices for mangrove health assessment. Malaysian Journal of Remote Sensing & GIS, 6 (2). pp. 10-16. ISSN 1511-7049 https://drive.google.com/file/d/0B4jwLxSd7T5hNFlwejNfeUMzRXc/view |
| spellingShingle | Mohd Razali, Sheriza Suk-ueng, Krittawit Nuruddin, Ahmad Ainuddin Remote sensing indices for mangrove health assessment |
| title | Remote sensing indices for mangrove health assessment |
| title_full | Remote sensing indices for mangrove health assessment |
| title_fullStr | Remote sensing indices for mangrove health assessment |
| title_full_unstemmed | Remote sensing indices for mangrove health assessment |
| title_short | Remote sensing indices for mangrove health assessment |
| title_sort | remote sensing indices for mangrove health assessment |
| url | http://psasir.upm.edu.my/id/eprint/62952/ http://psasir.upm.edu.my/id/eprint/62952/ http://psasir.upm.edu.my/id/eprint/62952/1/Remote%20sensing%20indices%20for%20mangrove%20health%20assessment.pdf |