Browsing by Author "K N Abdul Maulud"

Now showing 1 - 3 of 3
  • Thumbnail Image
    ItemOpen Access
    Assessment of Coastal Inundation of Low Lying Areas due to Sea Level Rise
    (IOP Publishing, 2018) F A Mohd; K N Abdul Maulud; O A Karim; R A Begum; N A Awang; M R Abdul Hamid; N A Abd Rahim; A H Abd Razak
    The objective of this study is to identify the potential of coastal inundation area due to Sea Level Rise (SLR) along of Cherating to Pekan coast.
  • Thumbnail Image
    ItemOpen Access
    Distribution ozone concentration in Klang Valley using GIS approaches
    (IOP Publishing, 2017) A Sulaiman; A A Ab Rahman; K N Abdul Maulud; M T Latif; F Ahmad; M A Abdul Wahid; M A Ibrahim; N D Abdul Halim
    Today, ozone has become one of the main air pollutants in Malaysia. The high ozone precursor concentrations have been encouraging the ozone production. The development of the Klang Valley, Malaysia has many types of physical activities such as urban commercial, industrial area, settlement area and others, which has increased the risk of atmospheric pollution. The purpose of this paper is to determine the spatial distribution between types of land use and ozone concentration that are occurred in the year 2014. The study areas for this paper include Shah Alam, Kajang, Petaling Jaya and Port Klang.Distribution of ozone concentration will be showed via spatial analysis tools in Geographic Information Systems (GIS) approached and the types of land use will be extracted using Remote Sensing technique.
  • Thumbnail Image
    ItemRestricted
    Evaluation and Verification of Numerical Modelling of Nearshore Changes due to Waves and Currents Parameter in Carey Island, Malaysia
    (IOP Publishing, 2018) F A Mohd; K N Abdul Maulud; A A Abd Rahman; M A Ibrahim; N A Awang; N A Abd Rahim; A H Abd Razak
    The objective of this study is to stimulate and verify the best estimation of Manning values around the Selangor coast. This study was carried out to evaluate the accuracy of the simulation results, statistical analysis method namely Root Mean Square Error (RMSE) is calculated to compare the observed and simulated results.