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Gravity change is happened among other caused by the changes of surface and subsurface mass. 4D gravity survey is applied for monitoring the physical changes of subsurface water. Identification and characterization anomaly sources is very important because several source give the near equal resource...

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Bibliographic Details
Main Author: MULYANAGARA (NIM 12303015), GUNTUR
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/7990
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Gravity change is happened among other caused by the changes of surface and subsurface mass. 4D gravity survey is applied for monitoring the physical changes of subsurface water. Identification and characterization anomaly sources is very important because several source give the near equal resource as in the density change case caused by subsidence effect and ground water dynamic. So, developed filtering technique using computer to decrease the anomaly distortion at the contour before. And Fourier transform is a tool to analyze two dimension gravity data that distributed horizontal. Domain Fourier is the right place to apply filter to eliminate wavelength that unwanted.<p> <br /> <br /> <br /> <br /> <br /> <br /> <br /> Convolution of filter function as output of transformation from frequency domain to the space domain with the anomaly map in the domain space will producing subsidence new map output wiener filter from the anomaly time-lapse data. Low-pass filter method moving average becomes the standard of comparison from wiener filter output. Filtering process will make signal anomaly increasing. Interpretation by microgravity time-lapse anomaly and subsidence anomaly is being used as identification of water table derivative zones, subsidence and both of them. Resulting of time-lapse anomaly and filtering indicate areas where subsidence was happened. Subsidence anomaly dominates the north of Semarang area than south. Result of moving average filtering is near correlation with subsidence anomaly than wiener filter.