nan Agustan

Isolating along-strike variations in the depth extent of shallow creep and fault locking on the northern Great Sumatran Fault

The Great Sumatran Fault system in Indonesia is a major right-lateral trench-parallel system that can be divided into several segments, most of which have ruptured within the last century. This study focuses on the northern portion of the fault system which contains a 200-km-long segment that has not experienced a major earthquake in at least 170 years. In 2005, we established the Aceh GPS Network for the Sumatran Fault System (AGNeSS) across this segment. AGNeSS observes large displacements which include significant postseismic deformation from recent large megathrust earthquakes as well as interseismic deformation due to continued elastic loading of both the megathrust and the strike slip system. We parameterize the displacements due to afterslip on the megathrust using a model based on a rate- and state-dependent friction formalism. Using this approach, we are able to separate afterslip from other contributions. We remove predicted deformation due to afterslip from the observations, and use these corrected time series to infer the depth of shallow aseismic creep and deeper locked segments for the Great Sumatran Fault. In the northern portion of this fault segment, we infer aseismic creep down to 7.3 ± 4.8 km depth at a rate of 2.0 ± 0.6 cm/year. In the southwestern portion of the segment, we estimate a locking depth of 14.8 ± 3.4 km with a downdip slip rate of 1.6 ± 0.6 cm/year. This portion of the fault is capable of producing a magnitude 7.0 earthquake.

Preliminary report on crustal deformation surveys and tsunami measurements caused by the July 17, 2006 South off Java Island Earthquake and Tsunami, Indonesia

A large earthquake (Mw=7.7) along a plate boundary occurred in the south of Java Island on July 17, 2006, and caused a significant tsunami. We made GPS observations and tsunami heights measurements during the period from July 24 to August 1, 2006. The earthquake seems to be due to an interplate low angle reverse faulting, though there might be a possibility of high angle faulting within the subducting lithosphere. Crustal deformation distribution due to the earthquake, aided by tsunami heights measurements, might clarify which would be the case. We occupied 29 sites by GPS in the area of southern Java encompassing the area from 107.8 E to 109.50 E. These sites were occupied once before the earthquake. However, we were not able to detect significant coseismic displacements. The obtained displacements, most of which span several years, show ESE direction in ITRF2000 frame. This represents the direction of Sunda block motion. The tsunami heights measured at 11 sites were 6–7 m along the southern coast of Java and indicate that the observed heights are systematically higher than those estimated from numerical simulations that are based on seismic data analysis. This might suggest that fault offsets might have been larger—nearly double—than those estimated using seismic analysis. These results lead us to an idea that the rupture was very slow. If this is the case, the earthquake might have been a “tsunami earthquake” that is similar to the one that occurred on June 2, 1994 in the east of the present earthquake.

Measuring ground deformation of the tropical volcano, Ibu, using ALOS-PALSAR data

The ability of radar to penetrate cloud is utilized to measure ground deformation related to volcanic activity of the tropical Ibu Volcano, Indonesia. Ground deformation in the vicinity of the volcano is believed to be related to subsurface magma activity. Besides cloud cover, the high density of vegetation, which is common in rainforests, is also a major obstacle for studying ground deformation in Indonesia. Therefore, a longer wavelength such as L-band radar data is suitable to address these problems. Using L-band differential interferometry it was found that there was an inflation–deflation region around the volcano, especially in the crater region before the eruption.

Innovation on Geolocation and Pattern Recognition for Paddy Growth Stages Reporting in Indonesia

Information on paddy growth stages is important for rice yield prediction. By utilizing statistical approach such as Area Frame Sampling method, data on paddy growth stages in the certain area may be used to estimate its harvest potential. The method of area frame sampling is based on segment observations determined from a stratified random sampling. Normally, information of paddy growth stages is obtained from terrestrial and remote sensing method. Since the life cycle of paddy is around 120 days, temporal resolution for observation becomes the main consideration. There is a need to develop a robust location-based reporting system for paddy growth stage. This system is designed by controlling the observer to report paddy condition on a determined location, called segment; the observer must report from the center of each segment. This paper discusses the innovation on the use of mobile phone for geolocation and pattern recognition to collect paddy growth stage data. The GPS on the mobile phone is explored for geolocation whereas the camera on the mobile phone is utilized to capture the paddy images. This information is then sent to the server for automatic pattern recognition. The statistical method with pre-processing, feature extraction, classification, feature selection and learning were applied on pattern recognition. Testing on geolocation was conducted in the Java area since May 2017 and installed for 2,356 observers. It is found that 73% of observers successfully reported the paddy growth stage from the center of each segment, which is locked in 10-meter accuracy, and 27% reported not from the center of segment due to field conditions.It is also found that a combination of GPS and mobile network or assisted-GPS can speed up the positioning.

Measuring Deformation in Jakarta through Long Term Synthetic Aperture Radar (SAR) Data Analysis

Jakarta as a home for more than 10 millions habitant facing complex environmental problems due to physical development that cause physical deformation. Physical deformation issues such as decreasing environmental carrying capacity, land cover changes and land subsidence have occurred. Recent studies shows that the long of shoreline changes in a span of 13 years from 2002 to 2015 around 14 km due to land reclamation in Jakarta bay. Previous studies also concluded that Jakarta suffer a sinking phenomena due to its rapid subsidence rate, approximately 260 mm/year in northern part of Jakarta. During the 2007 to 2011, the land subsidence phenomena in Jakarta was observed by InSAR based on ALOS-PALSAR data and found that the subsided areas only occurred in certain areas, mainly in Pluit and Cengkareng regions, with a subsidence of approximately 70 cm for 4 years. Land subsidence is generally related to geological subsidence i.e. sediment consolidation due to its own weight and tectonic movements; or related to human activities such as withdrawal of ground water and geothermal fluid, oil and gas extraction from underground reservoirs, and collapse of underground mines. The amount of subsidence or uplift can be estimated from the number of concentric fringes that appear in the interferogram. This research utilizes Synthetic Aperture Radar (SAR) data observed from ALOS-2 (L-band) and Sentinel-1 (C-band) satellites. By interfering two single look complex (SLC) images from different observation epoch, it is found that the subsided area that has been identified before continues to subside. This occurs especially in Pluit region and has been revealed by interfering ALOS-2 data up to year 2016. The deformation in this area is approximately 12 cm from November 2015 to September 2016. The process of land reclamation also clearly identified by Sentinel-1 image by series data processing in Sentinels Application Platform (SNAP) software.