| Summary: | Mangroves are very well known for their contribution to wildlife, human and ecosystem. Mangroves provide habitat, food, medicine and building material make them so valuable and important. However, despite all the benefits they offer, mangroves are being threatened all over the world. Mangrove loss and deforestation have become a worldwide issue. The destruction and replacement of mangrove forests spread widely for various reasons. This study focuses on determining the effect of environmental parameters towards mangrove areas. Three indicators were taken as a primary parameter in this study. Those parameters were tidal regime, wind intensity and relative sea level. The three information were obtained from Forest Research Institute Malaysia (FRIM), Forestry Department Peninsular Malaysia (FDIM) and Malaysian Meteorological Department (MMD) as well as from previous studies. The study area for this research covered the east and west coast of Malaysia. For the east coast was Chendering in Terengganu, whereas for the west coast was Kuala Perlis in Perlis. The detection of mangrove areas was performed using Landsat 5 TM and Landsat 8 OLI satellite imageries in PCI Geomatica 2013 software. The process of determining the mangrove area was done using supervised classification with maximum likelihood classifier and supported with site verification. The area covered was 5 km × 5 km per image or 25 km2 with the range period of 10 years from 2005 to 2015, and the satellite images selected were in the years of 2005, 2010 and 2015. The changes of mangrove areas were determined. Chendering mangrove areas increased 3243 m2 during 2005–2015, while in Kuala Perlis mangrove increased 1892 m2 during the same period. The relationships between tidal regime, relative sea level and wind intensity were analysed based on the results from mangrove area changes that was obtained through supervised classification and correlation analysis. The final result shows several responses that accomplished the objectives of this study. The classification processing for the mangrove area was successfully acquired with more than 85% accuracy. The mangrove areas have shown some changes during the years of 2005, 2010 and 2015. © Springer Nature Singapore Pte Ltd. 2022.
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