Fluid extraction or injection from reservoirs, which corresponds to subsidence or uplift, can cause offshore platform surface deformation. Extremely large deformation of offshore platforms often lead to production losses, threat to the structure integrity and loss of life. Therefore, preventing severe deformation incidents is important by monitoring surface deformation caused by oil and gas production activities. In this study, the A1 and B1 offshore platforms have been selected as research study areas to detect surface deformation caused by production activities. A total of 12 radar images from TerraSAR-X satellite were obtained from 24th August 2018 to 22nd August 2019 to derive surface deformation through the Stanford Method for Persistent Scatterers (StaMPS) method. The maximum amounts of subsidence observed on A1 and B1 platforms were -4 mm/yr and -6.3 mm/yr, respectively. This study provides an important insight the use of InSAR technology for the monitoring deformation of offshore platforms.
The effect of the atmospheric error in the spaceborne synthetic aperture radar (SAR) signal is more prominent in Malaysia due to its hot and wet conditions. Because the atmospheric error is believed to happen constantly in space and randomly in time, low-pass filtering in space and high-pass filtering in time is employed to measure it. However, with few scenes, the filtering technique’s reliability in removing atmospheric error may be insufficient, leading to erroneous surface deformation. Therefore, an external atmospheric correction needs to be modelled to improve the accuracy of surface deformation. In this study, the atmospheric error correction was estimated from GPS and applied to the deformation analysis. The result shows that the atmospheric error level estimated from the filtering technique was –6.9 to 7.5 radians, while using GPS was -1.0 to 1.9 radians. After using the filtering process, the rate of deformation fell dramatically. However, compared to the reference deformation, the rate was too low, indicating that the filtering technique overstated the level of atmospheric error. At many data collections, the atmospheric correction calculated from GPS gave deformation values closer to the reference deformation. Hence, this study will help the researchers to model the atmospheric correction over the Malaysia region in future.
Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), Advanced Land Observing Satellite World-3D (ALOSW3D), and TerraSAR-X Digital Elevation Measurement (TanDEM-X) are open-source Digital Elevation Model (DEM) datasets for environmental modelling and studies. The spatial resolution and vertical accuracy of DEM data sources play a significant role, particularly in dealing with land inundation, periodic flooding, and coastal erosion. In this study, the comparison between orthometric height, H from Global Navigation Satellite System (GNSS) observation, and DEM is performed to evaluate the accuracy of each DEM in terms of their Root Mean Square Error (RMSE) and correlation coefficient, R2 for monitoring the coastline. The result has indicated that TanDEM-X shows the smallest RMSE of 2.574 m compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D with RMSE of 2.968 m, 3.006 m, 3.217 m, 2.975 m, and 2.876 m respectively. Furthermore, TanDEM-X illustrates the largest correlation coefficients, R2 of 0.959 m, compared to SRTM30, SRTM90, ASTER, GMTED10, and ALOSW3D at 0.891 m, 0.899 m, 0.590 m, 0.888 m 0.913 m respectively. Hence, the result has indicated that TanDEM-X is the best option among all DEMs for any topographic applications.
With a coastline length extending over 13,000 km, including the Malaysia region, the South China Sea presents a challenge to retrieve high quality data along the coastal area especially the sea level anomaly and significant wave height. Currently, coastal altimetry is still facing some issues especially when using the low frequency data such as data lacking near the coast, questionable data accuracy since the altimeter footprint contaminated with the land and less coverage of data from the installed ground truth data. This study aims to assess the coastal altimetry data of sea level and significant wave height in the South China Sea using low and high frequency approaches. This study involved deriving data from sea level anomaly (SLA) and significant wave height (SWH) through the use of Prototype for Expertise on AltiKa for Coastal, Hydrology and Ice (PEACHI) for high frequency and Radar Altimeter Database System (RADS) for low frequency of altimetry and ground truth station which is from tide gauge and Acoustic Wave and Current Profiler (AWAC). Comparison between altimetry and ground truth data has been made in order to validate the significant agreement between them. The validation of the data is to evaluate both types of frequencies with respect to the coastal distance. Consequently, the high frequency results for coastal results with a root mean square reliable ±0.14 metre level for the sea level anomaly (SLA) and ±0.18 metre level for significant wave height (SWH) are more reliable. PEACHI distance-to-coast data obtained a sufficient standard residual deviation ranging from 0 cm to 2.87 cm compared to RADS altimetry ranging from 0.08 cm to 14.20 cm. The findings of this study indicate that the coastal altimetry data benefit coastal development, coastal defence, monitoring and tourism by various related agencies.
The element of higher order thinking skills (HOTs) in Islamic Education is important in contributing to the effectiveness of teaching and facilitation (PdPc) to students' appreciation of knowledge. Meanwhile, the teacher as the main implementing agent in applying HOTs elements. Therefore, this study aims to identify the elements that contribute to HOTs in the Teaching of Islamic Education Teachers. This study is a descriptive study using systematic literature review (SLR) method of qualitative. The main source of this study is through highlights of previous work obtained from the Google Scholar online database analyzed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA). The findings of the study show that the factors that affect the teaching of Islamic education is able to build HOTs is attitude, readiness, knowledge, skills and formulate. These findings are important to the field of education in Malaysia whether teachers, administrators, State Education Department, Ministry of Education Malaysia (MOE) in evaluating the HOTs curriculum from time to time, especially in the field of Islamic education
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