Abstract. This study aims to provide understanding on the accuracy of height derived from Google Earth (H GoogleEarth ) as compared to height obtained from Malaysian Geoid Model (H MyGeoid ), Mean Sea Level (H MSL ) and Earth Geoid Model 96 (H EGM96 ). Total of 50 established points with height acquired from H MyGeoid and H MSL were measured within UiTM (Universiti Teknologi MARA) Arau Campus. These points were also used to extract height from Google Earth and EGM96. Statistical results showed a good range of R

Rice is the primary source of nutrition food of more than half of the world’s population, and it is hugely important in the global economic growth, food security, water use, and climate change. The need for satellite systems to monitor rice crops and assist in rice crop management is gaining in popularity. The European Space Agency’s (ESA) launched Sentinel-2 A + B twin platform’s which enhanced the temporal, spatial, and spectral resolution, opening the way for their widely use in crop monitoring. Aside from the technical features of the Sentinel-2 A and B constellation, the easily accessible type of information they generate as well as the appropriate support software have been significant improvements for rice crop monitoring. In this study, the spectral reflectance has been analysed to find how far their potential in determining rice growth phases. The highest spectrum in reflectance was observed in the near infrared (NIR) region (842 nm). Because of the structure of mesophyll cells tissues and the inner backscatter of air spaces, moisture content, and air–water abstraction layers within the leaves, the reflectance in the NIR region seems to be much larger than in the visible band. The multi-temporal vegetation index namely Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Normalized Difference Moisture Index (NDMI) have derived from ten Sentinel-2 images cover the entire rice season. These indices have been tested to determine the rice growth phases over the rice season. The spatial distribution of each tested indices is displayed in the map output. The maps are then analysed and compared to determine the potential of each index in determining rice growth phases. It was discovered in this study that there was a quadratic correlation between all of the tested indices and rice age. The Normalized Difference Vegetation Index (NDVI) is the most accurate vegetation index for estimating rice growth phases, followed by SAVI and NDMI.

Coastal erosion and accretion are long-term process that may cause changes in shoreline and beach profiles. Due to erosion and accretion effects, most of the coastal areas in Malaysia are suffering from destruction of property especially at the coastal areas in east coast of Peninsular Malaysia. This study was conducted to determine the effects of erosion and accretion on beach profiles at four (4) coastal areas in Kuala Terengganu using remote sensing and GPS observation methods. The objectives include to derive the coastal erosion and accretion rate, to measure coastal elevation for beach slope angle calculation, and to determine the relationship between beach slope angle with coastal erosion and accretion. The erosion and accretion rate was derived from SPOT-5 satellite image and unmanned aerial vehicles (UAV). In order to obtain the beach profile, the elevation with 50m offset for every chainage, and 5m offset for each cross-section point were carried out using real-time kinetic (RTK) observation methods. It was found that the highest and lowest erosion and accretion rates were 170.29 m²/year and 57.53 m²/year, respectively. The beach profile became steeper with the beach slope values of 11.004° and 7.652° at high and low erosion areas, respectively. The relationships between beach slope angle and coastal erosion/accretion were found as 0.12 and 0.86 respectively. The findings showed that steeper beach profiles influenced the high rate values of erosion and accretion. For more accurate findings, further studies on the factors affecting the erosion and accretion such as monsoon seasonal changes and morphological impact are necessary to support the reliable decision-making process for sustainable coastal management.

The unprecedented outbreak of Coronavirus Disease 2019 (COVID-19) has impacted the whole world in every aspect including health, social life, economic activity, education, and the environment. The pandemic has led to an improvement in air quality all around the world, including in Malaysia. Lockdowns have resulted in industry shutting down and road travel decreasing which can reduce the emission of Greenhouse Gases (GHG) and air pollution. This research assesses the impact of the COVID-19 lockdown on emissions using the Air Pollution Index (API), aerosols, and GHG which is Nitrogen Dioxide (NO 2 ) in Malaysia. The data used is from Sentinel-5p and Sentinel-2A which monitor the air quality based on Ozone (O 3 ) and NO 2 concentration. Using an interpolated API Index Map comparing 2019, before the implementation of a Movement Control Order (MCO), and 2020, after the MCO period we examine the impact on pollution during and after the COVID-19 lockdown. Data used Sentinel-5p, Sentinel-2A, and Air Pollution Index of Malaysia (APIMS) to monitor the air quality that contains NO 2 concentration. The result has shown the recovery in air quality during the MCO implementation which indirectly shows anthropogenic activities towards the environmental condition. The study will help to enhance and support the policy and scope for air pollution management strategies as well as raise public awareness of the main causes that contribute to air pollution.

Various technique and application have been used in determining the hazard analysis. AHP technique was chosen for this study in effort to find the most factors cause the landslide in the study area. The aim of this study is to determine the factors of landslide hazard using satellite imagery Landsat-8 OLI and Analytic Hierarchy Technique (AHP) in Tanjung Bungah, Penang. This study embarks on three objectives which are to identify the parameter involved in landslide hazard based on surface characteristics, to derive topographical surface from satellite image Landsat 8 OLI in relation of landslide hazard and to determine the correlation of identified parameter and derived topographical information for landslide hazard using AHP technique in Tanjung Bungah, Penang. There are 6 parameters used which are slope, aspect, lithology, rainfall, land surface temperature (LST), and soil-adjusted vegetation index (SAVI). Landsat 8 has been processed to provide the secondary data used in GIS platform. All the processed data are then overlaid using weighted overlay analysis. The output of the analysis shown is spatially visualized to examine the location of the landslide hazards risk. The map produced help in better understanding of nature impact of past, current and future development decision making.