UPM Institutional Repository

Remote sensing indices for mangrove health assessment


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


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.

Download File

Text (Abstract)
Remote sensing indices for mangrove health assessment.pdf

Download (6kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Institute of Tropical Forestry and Forest Products
Publisher: Institution of Geospatial and Remote Sensing Malaysia
Keywords: Remote sensing; Indices; Mangroves health; Mangrove forests; Tropical forests
Depositing User: Mas Norain Hashim
Date Deposited: 22 Oct 2018 08:48
Last Modified: 22 Oct 2018 08:48
URI: http://psasir.upm.edu.my/id/eprint/62952
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item