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
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.
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.
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.
The management of Islamic cemeteries is a social requirement that needs to be implemented in Malaysia community especially among Muslims. The cemetery management system is particularly inadequate because of the current rapid development and a high number of deaths in specific urban areas. This circumstance has produced several concerns, including the lack of an orderly death record and the non-uniform arrangement of grave sites, all of which contribute to the lack of a cemetery. Therefore, the emerging demands in creating the Muslim cemetery management system are highly significant. The Muslim Graveyard Management System (MGMS) was created using a combination of Geographical Information System (GIS), aerial imagery and the used of Survey123 Mobile Apps technologies. This study focuses on the development of GIS and web-based systems to assist authorities in managing funeral records more effectively. The study was also conducted to assist the deceased's heirs in identifying the location of their family graves. This system is well equipped with a search function that can provide information of the deceased by using an Internet browser. In addition, the use of quick response code (QR code) in this IGMS system allows various types of information to be directly accessible and easily generated with fast-reading accuracy. Consequently, this study has foreseen the practicality and potential of this MGMS system through a conducted case study at the Islamic cemetery,
Forest biomass or above-ground carbon stock is the mass of carbon that stored in trees which requires a continuous monitoring in order to predict the amount of potential carbon accumulation of the forest. Therefore, the forest has an important role at absorbing carbon Dioxide (CO2) from the atmosphere. This research aims to measure the capability of Quick Terrain Modeller software at estimating above-ground carbon stock by single tree segmentation combining ground inventory, Light Detection and Ranging (LiDAR), and by using allometric equations. In particular, to achieve the aim, there are three (3) objectives were outlined. Canopy Height Models (CHM) was generated via Quick Terrain Modeller (QTM) and ArcGIS. Non-linear Regression analyses were performed for both surface models to ensure the models were fit to estimate carbon stock. Secondly, tree contours were delineated using watershed transformation. Local maxima were determined at the raster as a pour point for watershed and also represent the highest peak of the tree crown. In addition, flow direction, drop output, and flow accumulation of the raster were also determined to generate contour from the watershed transformation. Manual tree crown projection was performed by watershed tree contour to generate Crown Projection Area (CPA). Then, from the digitized CPA, carbon stock and above-ground biomass was calculated using equations from [1] and [2]. Thirdly, tree species on the selected area were extracted and finally a map of tree carbon stock by species was produced. From the generated map, total carbon stock according to species and total carbon stock in single tree according to species information were extracted. As a result, Hopea sulcata; the endangered tree species appeared to be the highest appearance in the map followed by Dipterocarpus verrucosus, Shorea macroptera, Endospermum diadenum, and the other less appeal species. Also from the map, Hopea Sulcata has the highest carbon stock which is 23% compared to the other species. However, for a single tree, Dipterocarpus verrucosus held the highest carbon stock which is 1565.401 kg/tree.
The world was shocked by an unprecedented outbreak caused by coronavirus disease 2019 (COVID-19). In Malaysia, it started with the largest number of COVID-19 cases with the first wave of infection on 25 January 2020. The objectives of this paper are to obtain the perspective of the respondents about the need for web-mapping in the form of mapping the geospatial data in Malaysia and to visualize the current online datasets of COVID-19 disease case clusters. The study area would cover the entire Malaysia since a rapidly increasing number of citizens were affected by this virus. To be specific, this study focused on the active clusters of COVID-19 in Malaysia. The data were freely shared in real-time by referring to the Ministry of Health (MOH) channel. The hotspots map were explored using the Map Editor by Cloud GIS. The approach has been illustrated using a dataset of whole Malaysia which are locally transmitted confirmed cases in four phases of COVID-19 wave in Malaysia. This study is significant to raise public awareness of the virus, especially among Malaysian citizens. It can provide an accurate estimation of the cluster tracking of the COVID-19 system by using geospatial technology. Therefore, people are more concerned and followed all the Standard Operating Procedure (SOP) provided by the government to prevent the spread of COVID-19.
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