Citation
Abstract
The mangrove forest ecosystem acts as a shield against the destructive tidal waves, preventing the coastal areas and other properties nearby from severe damages; this protective function certainly deserves attention from researchers to undertake further investigation and exploration. Mangrove forest provides different goods and services. The unique environmental factors affecting the growth of mangrove forest are as follows: distance from the sea or the estuary bank, frequency and duration of tidal inundation, salinity, and composition of the soil. These crucial factors may under certain circumstances turn into obstacles in accessing and managing the mangrove forest. One effective method to circumvent this shortcoming is by using remotely sensed imagery data, which offers a more accurate way of measuring the ecosystem and a more efficient tool of managing the mangrove forest. This paper attempts to review and discuss the usage of remotely sensed imagery data in mangrove forest management, and how they will improve the accuracy and precision in measuring the mangrove forest ecosystem. All types of measurements related to the mangrove forest ecosystem, such as detection of land cover changes, species distribution mapping and disaster observation should take advantage of the advanced technology; for example, adopting the digital image processing algorithm coupled with high-resolution image available nowadays. Thus, remote sensing is a highly efficient, low-cost and time-saving technique for mangrove forest measurement. The application of this technique will further add value to the mangrove forest and enhance its in-situ conservation and protection programmes in combating the effects of the rising sea level due to climate change.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Forestry Institute of Tropical Forestry and Forest Products |
Publisher: | Universiti Putra Malaysia Press |
Keywords: | Geoinformation technology; Mangrove; Remote sensing; Sustainable management; Tropical forest |
Depositing User: | Nabilah Mustapa |
Date Deposited: | 12 Feb 2019 07:02 |
Last Modified: | 12 Feb 2019 07:02 |
URI: | http://psasir.upm.edu.my/id/eprint/66301 |
Statistic Details: | View Download Statistic |
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