The eastern part of Java Island is transversed by major faults such as Cepu,Blumbang,Surabaya,and Waru Segment,part of the Kendeng Fault,Wonsorejo Fault,Pasuruan Fault,and Probolinggo Fault.Due to the major fault,we u...The eastern part of Java Island is transversed by major faults such as Cepu,Blumbang,Surabaya,and Waru Segment,part of the Kendeng Fault,Wonsorejo Fault,Pasuruan Fault,and Probolinggo Fault.Due to the major fault,we used decomposition of identified fault from the Global Navigation Satellite System(GNSS)observation data to identify the potential of local deformation.We analyzed surface deformation due to the effect of major fault using scaling law and elastic half-space method.We investigated the possibility of unidentified fault using strain rates based on velocity vector data before and after correcting the effect of a major fault.We found that strain calculation for principal strain value in the eastern part of Java Island is less than one microstrain/year and the dominant one with a compression pattern due to the Sunda subduction zone.The maximum shear strain rate value goes from 0.002 to 0.094 microstrain/year,and the dilatation rate value ranges from-0.141 to 0.038 microstrain/year,which correlates with the reverse of the Kendeng Fault.A higher compression pattern outside the major fault in a differential maximum shear strain rate might indicate a local fault.展开更多
The Lembang Fault is a major geological feature in West Java that borders the northern edge of Bandung(one of Indonesia’s largest cities).It lies just south of the active Tangkuban Perahu Volcano,exhibiting clear geo...The Lembang Fault is a major geological feature in West Java that borders the northern edge of Bandung(one of Indonesia’s largest cities).It lies just south of the active Tangkuban Perahu Volcano,exhibiting clear geomorphic signs of recent activity,and has been scientifically confirmed as active through geological and geophysical studies.In this work,we describe an Integrated along the Lembang Fault,which can be used for geodynamic research in Indonesia.We discuss the design of a seismic and Global Navigation Satellite System(GNSS)array sensor network for continuous monitoring,and report the status of monitoring stations that periodically collect highly accurate,continuous seismographic and GNSS readings,transmitting these data to a central server in Bandung for post-processing.Solutions from the array data are used to provide precise measurements of the deformation of the Earth’s surface over large distances,allowing for spatio-temporal tracking of tectonic movement,and resulting in a better understanding of seismic events in the region.In this study,our investigation revealed a significant compression rate of an estimated 13 microstrain/yr along the Lembang Fault,whereas the strain rate is much smaller farther south of the fault.This study presents the design of a seismo-geodetic observatory network that can be implemented in earthquake-prone regions for mitigation purposes,with particular utility for studying other active faults that also traverse populated areas in Indonesia.展开更多
The Global Positioning System(GPS) Indonesian Continuously Operating Reference Stations(InaCORS)network has been used for various applications ranging from land administration to geodynamics.Crustal dynamic process pl...The Global Positioning System(GPS) Indonesian Continuously Operating Reference Stations(InaCORS)network has been used for various applications ranging from land administration to geodynamics.Crustal dynamic process plays a significant role in almost all Indonesia regions except in Kalimantan Island since it’s located on the stable continental plate. Therefore, the study of deformation in an area with less tectonic activities would be relatively simple to elucidate another terrestrial process. Here, we analyzed the deformation process in Kalimantan Island using continuous geodetic observation. We found that vertical displacement shows oscillation signals which are related to the hydrological cycle of water storage changes. Along with the GPS data, we utilized rain precipitation data to analyze both spatial and temporal variation of vertical displacement to support the hypothesis of elastic response to the load of water mass variations. Finally, we emphasized that continuous GPS observation in Kalimantan is reliable for detecting seasonal hydrological water storage changes.展开更多
The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration ...The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration Systems (LAS). LAS services involve requests and responses concerning public and private cadastral data, including credentials of parties, ownership, and spatial parcels. This study explores the integration of CTI in LAS to enhance cyber resilience, focusing on the unique vulnerabilities of LAS, such as sensitive data management and interconnection with other critical systems related to spatial data uses and changes. The approach employs a case study of a typical country-specific LAS to analyse structured vulnerabilities and their attributes to determine the degree of vulnerability of LAS through a quantitative inductive approach. The analysis results indicate significant improvements in identifying and mitigating potential threats through CTI integration, thus enhancing cyber resilience. These findings are crucial for policymakers and practitioners to develop robust cybersecurity strategies for LAS.展开更多
Tropical lakes such as Lake Sentarum in Kalimantan,Indonesia,represent ecologically rich ecosystems with high biodiversity and constitute the largest lake on the island of Kalimantan.This lake serves as a sensitive in...Tropical lakes such as Lake Sentarum in Kalimantan,Indonesia,represent ecologically rich ecosystems with high biodiversity and constitute the largest lake on the island of Kalimantan.This lake serves as a sensitive indicator of climate change;however,its monitoring is often hindered by persistent cloud cover.This study evaluates the effectiveness of a Gradient Tree Boosting machine learning model integrated with multisource satellite data,including optical imagery,Sentinel-1 SAR,Sentinel-2,and high resolution NICFI data,in accurately mapping surface water dynamics.The Gradient Tree Boosting model was trained and validated using water and non water samples collected from annual imagery spanning 2019 to 2024,achieving validation accuracies ranging from 80 percent to 97 percent.Results demonstrate that Gradient Tree Boosting successfully integrates the strengths of each sensor,producing consistent annual water maps despite extreme hydrological fluctuations caused by El Nino and La Nina events.These findings highlight the model’s potential application in water resource man-agement,particularly in providing accurate baseline data to support adaptation planning for droughts and floods in climate vulnerable regions.展开更多
The Mentawai Forearc Sliver(MFS)is characterized by oblique deformation formed as slip partitioned between normal and parallel trench plate convergence.The surge of great earthquakes from 2004 to2012 along the adjacen...The Mentawai Forearc Sliver(MFS)is characterized by oblique deformation formed as slip partitioned between normal and parallel trench plate convergence.The surge of great earthquakes from 2004 to2012 along the adjacent Sunda trench left a large unbroken segment known as the Mentawai Seismic Gap.Here,we adopted continuous Global Navigation Satellite System(GNSS)observation data to identify the present regional crustal deformation using geodetic strain rates.The principal strain rate,dilatation rate,and maximum shear strain rate are about 0.13 microstrain/yr,0.2 microstrain/yr,and 0.1 microstrain/yr,respectively,with the range of its uncertainties between 0.01 and 0.04 microstrain/yr.The dilatation and maximum shear strain rates reveal the spatial coverage of strike-slip duplex and backthrust tectonics along the Mentawai Forearc Sliver.展开更多
We investigated the active crustal structure in Yogyakarta,Indonesia,using new and denser Global Positioning System(GPS)data.Deformation rate estimated from five years(2013-2018)of observations on 22 campaign might re...We investigated the active crustal structure in Yogyakarta,Indonesia,using new and denser Global Positioning System(GPS)data.Deformation rate estimated from five years(2013-2018)of observations on 22 campaign might record broad deformation after the 2006 Mw7.8 Java tsunami earthquake and postseismic transient due to the 2006 Mw6.3 Yogyakarta earthquake.We conducted a decomposition method to obtain a short wavelength feature by removing those postseismic deformations from the observation data.The short wavelength pattern revealed active tectonics indicating a combination of E-W dip-slip motion and N-S left-lateral structure.A large maximum shear strain rate(>0.1 microstrain/yr)was estimated along the Opak fault while a large dilatation rate(<-0.1 microstrain/yr)was estimated around the Bantul Graben.The analysis result indicates important implications for crustal dynamics and assessing future seismic hazards potential in the Yogyakarta region.展开更多
Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works us...Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works used local-scale case studies that focused on a specific earthquake characteristic using knowledgedriven techniques, such as crustal deformation analysis. In this study, a data-driven-based analysis is used to detect anomalies using displacement rates and deformation pattern features extracted from daily global navigation satellite system(GNSS) data using a machine learning algorithm. The GNSS data with188 and 1181 continuously operating reference stations from Indonesia and Japan, respectively, are used to identify the anomaly of recent major earthquakes in the last two decades. Feature displacement rates and deformation patterns are processed in several window times with 2560 experiment scenarios to produce the best detection using tree-based algorithms. Tree-based algorithms with a single estimator(decision tree), ensemble bagging(bagging, random forest and Extra Trees), and ensemble boosting(AdaBoost, gradient boosting, LGBM, and XGB) are applied in the study. The experiment test using realtime scenario GNSSdailydatareveals high F1-scores and accuracy for anomaly detection using slope windowing 365 and 730 days of 91-day displacement rates and then 7-day deformation pattern features in tree-based algorithms. The results show the potential for medium-term anomaly detection using GNSS data without the need for multiple vulnerability assessments.展开更多
RS （remote sensing） applications to hydrological problem solving have successfully transitioned from being experimental to operational in the last couple of years, and information gathered through these technologies...RS （remote sensing） applications to hydrological problem solving have successfully transitioned from being experimental to operational in the last couple of years, and information gathered through these technologies can facilitate water resource procedures. Patterns from RS imagery can be translated into a deterministic distribution of input data over a wide area on a pixel-by-pixel basis. This paper presents the implementation of different methodologies of integrating satellite-derived information from RS, and GIS （geographic information system） visualization and simulation capabilities in improving hydrologic estimation processes.展开更多
The Palu MW7.4 earthquake occurred on September 28, 2018, with the epicenter at 119.86°, 0.72°. The severe shaking caused severe damage in Central Sulawesi, especially in Palu. We conducted a postseismic def...The Palu MW7.4 earthquake occurred on September 28, 2018, with the epicenter at 119.86°, 0.72°. The severe shaking caused severe damage in Central Sulawesi, especially in Palu. We conducted a postseismic deformation study to determine the deformation pattern and reduce future earthquakes’ impact.Interferometric Synthetic Aperture Radar(In SAR) data were processed using Li CSBAS to get the time series. The time series data were fitted to exponential and logarithmic functions to determine the mechanism of postseismic deformation. The exponential model identified the influence of the viscoelastic mechanism, and the logarithm identified the afterslip mechanism. The Palu earthquake was fitted to logarithmic and exponential, but the logarithmic was more significant than an exponential function.Afterslip mechanism predominates, and viscoelastic mechanisms play a minor role in this postseismic deformation.展开更多
基金partially supported by UGM’s Fund in the scheme of the RTA Project
文摘The eastern part of Java Island is transversed by major faults such as Cepu,Blumbang,Surabaya,and Waru Segment,part of the Kendeng Fault,Wonsorejo Fault,Pasuruan Fault,and Probolinggo Fault.Due to the major fault,we used decomposition of identified fault from the Global Navigation Satellite System(GNSS)observation data to identify the potential of local deformation.We analyzed surface deformation due to the effect of major fault using scaling law and elastic half-space method.We investigated the possibility of unidentified fault using strain rates based on velocity vector data before and after correcting the effect of a major fault.We found that strain calculation for principal strain value in the eastern part of Java Island is less than one microstrain/year and the dominant one with a compression pattern due to the Sunda subduction zone.The maximum shear strain rate value goes from 0.002 to 0.094 microstrain/year,and the dilatation rate value ranges from-0.141 to 0.038 microstrain/year,which correlates with the reverse of the Kendeng Fault.A higher compression pattern outside the major fault in a differential maximum shear strain rate might indicate a local fault.
基金the National Research and InnovationAgency of Indonesia (BRIN) under research grant Rumah Program Kebencanaan 2022-2025support from the Earth Observatory Singapore (EOS)supported by the Ministry of Higher Education, Science,and Technology, and Institut Teknologi Bandung through the Indonesian Collaborative Research Program.
文摘The Lembang Fault is a major geological feature in West Java that borders the northern edge of Bandung(one of Indonesia’s largest cities).It lies just south of the active Tangkuban Perahu Volcano,exhibiting clear geomorphic signs of recent activity,and has been scientifically confirmed as active through geological and geophysical studies.In this work,we describe an Integrated along the Lembang Fault,which can be used for geodynamic research in Indonesia.We discuss the design of a seismic and Global Navigation Satellite System(GNSS)array sensor network for continuous monitoring,and report the status of monitoring stations that periodically collect highly accurate,continuous seismographic and GNSS readings,transmitting these data to a central server in Bandung for post-processing.Solutions from the array data are used to provide precise measurements of the deformation of the Earth’s surface over large distances,allowing for spatio-temporal tracking of tectonic movement,and resulting in a better understanding of seismic events in the region.In this study,our investigation revealed a significant compression rate of an estimated 13 microstrain/yr along the Lembang Fault,whereas the strain rate is much smaller farther south of the fault.This study presents the design of a seismo-geodetic observatory network that can be implemented in earthquake-prone regions for mitigation purposes,with particular utility for studying other active faults that also traverse populated areas in Indonesia.
基金partially supported by RISTEK-DIKTI in the scheme of PDUPT Project 2567/UN1.DITLIT/DIT-LIT/LT/2019
文摘The Global Positioning System(GPS) Indonesian Continuously Operating Reference Stations(InaCORS)network has been used for various applications ranging from land administration to geodynamics.Crustal dynamic process plays a significant role in almost all Indonesia regions except in Kalimantan Island since it’s located on the stable continental plate. Therefore, the study of deformation in an area with less tectonic activities would be relatively simple to elucidate another terrestrial process. Here, we analyzed the deformation process in Kalimantan Island using continuous geodetic observation. We found that vertical displacement shows oscillation signals which are related to the hydrological cycle of water storage changes. Along with the GPS data, we utilized rain precipitation data to analyze both spatial and temporal variation of vertical displacement to support the hypothesis of elastic response to the load of water mass variations. Finally, we emphasized that continuous GPS observation in Kalimantan is reliable for detecting seasonal hydrological water storage changes.
文摘The current global cybersecurity landscape, characterized by the increasing scale and sophistication of cyberattacks, underscores the importance of integrating Cyber Threat Intelligence (CTI) into Land Administration Systems (LAS). LAS services involve requests and responses concerning public and private cadastral data, including credentials of parties, ownership, and spatial parcels. This study explores the integration of CTI in LAS to enhance cyber resilience, focusing on the unique vulnerabilities of LAS, such as sensitive data management and interconnection with other critical systems related to spatial data uses and changes. The approach employs a case study of a typical country-specific LAS to analyse structured vulnerabilities and their attributes to determine the degree of vulnerability of LAS through a quantitative inductive approach. The analysis results indicate significant improvements in identifying and mitigating potential threats through CTI integration, thus enhancing cyber resilience. These findings are crucial for policymakers and practitioners to develop robust cybersecurity strategies for LAS.
文摘Tropical lakes such as Lake Sentarum in Kalimantan,Indonesia,represent ecologically rich ecosystems with high biodiversity and constitute the largest lake on the island of Kalimantan.This lake serves as a sensitive indicator of climate change;however,its monitoring is often hindered by persistent cloud cover.This study evaluates the effectiveness of a Gradient Tree Boosting machine learning model integrated with multisource satellite data,including optical imagery,Sentinel-1 SAR,Sentinel-2,and high resolution NICFI data,in accurately mapping surface water dynamics.The Gradient Tree Boosting model was trained and validated using water and non water samples collected from annual imagery spanning 2019 to 2024,achieving validation accuracies ranging from 80 percent to 97 percent.Results demonstrate that Gradient Tree Boosting successfully integrates the strengths of each sensor,producing consistent annual water maps despite extreme hydrological fluctuations caused by El Nino and La Nina events.These findings highlight the model’s potential application in water resource man-agement,particularly in providing accurate baseline data to support adaptation planning for droughts and floods in climate vulnerable regions.
基金supported by Universitas Gadjah Mada through the 2022 Indonesian Collaborative Research Program.
文摘The Mentawai Forearc Sliver(MFS)is characterized by oblique deformation formed as slip partitioned between normal and parallel trench plate convergence.The surge of great earthquakes from 2004 to2012 along the adjacent Sunda trench left a large unbroken segment known as the Mentawai Seismic Gap.Here,we adopted continuous Global Navigation Satellite System(GNSS)observation data to identify the present regional crustal deformation using geodetic strain rates.The principal strain rate,dilatation rate,and maximum shear strain rate are about 0.13 microstrain/yr,0.2 microstrain/yr,and 0.1 microstrain/yr,respectively,with the range of its uncertainties between 0.01 and 0.04 microstrain/yr.The dilatation and maximum shear strain rates reveal the spatial coverage of strike-slip duplex and backthrust tectonics along the Mentawai Forearc Sliver.
基金partially supported by Universitas Gadjah Mada in the scheme of Final Project Recognition.
文摘We investigated the active crustal structure in Yogyakarta,Indonesia,using new and denser Global Positioning System(GPS)data.Deformation rate estimated from five years(2013-2018)of observations on 22 campaign might record broad deformation after the 2006 Mw7.8 Java tsunami earthquake and postseismic transient due to the 2006 Mw6.3 Yogyakarta earthquake.We conducted a decomposition method to obtain a short wavelength feature by removing those postseismic deformations from the observation data.The short wavelength pattern revealed active tectonics indicating a combination of E-W dip-slip motion and N-S left-lateral structure.A large maximum shear strain rate(>0.1 microstrain/yr)was estimated along the Opak fault while a large dilatation rate(<-0.1 microstrain/yr)was estimated around the Bantul Graben.The analysis result indicates important implications for crustal dynamics and assessing future seismic hazards potential in the Yogyakarta region.
基金the Program PenelitianKolaborasi Indonesia(PPKI)Non APBN Universitas Diponegoro Universitas Diponegoro Indonesia under Grant 117-03/UN7.6.1/PP/2021.
文摘Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works used local-scale case studies that focused on a specific earthquake characteristic using knowledgedriven techniques, such as crustal deformation analysis. In this study, a data-driven-based analysis is used to detect anomalies using displacement rates and deformation pattern features extracted from daily global navigation satellite system(GNSS) data using a machine learning algorithm. The GNSS data with188 and 1181 continuously operating reference stations from Indonesia and Japan, respectively, are used to identify the anomaly of recent major earthquakes in the last two decades. Feature displacement rates and deformation patterns are processed in several window times with 2560 experiment scenarios to produce the best detection using tree-based algorithms. Tree-based algorithms with a single estimator(decision tree), ensemble bagging(bagging, random forest and Extra Trees), and ensemble boosting(AdaBoost, gradient boosting, LGBM, and XGB) are applied in the study. The experiment test using realtime scenario GNSSdailydatareveals high F1-scores and accuracy for anomaly detection using slope windowing 365 and 730 days of 91-day displacement rates and then 7-day deformation pattern features in tree-based algorithms. The results show the potential for medium-term anomaly detection using GNSS data without the need for multiple vulnerability assessments.
文摘RS （remote sensing） applications to hydrological problem solving have successfully transitioned from being experimental to operational in the last couple of years, and information gathered through these technologies can facilitate water resource procedures. Patterns from RS imagery can be translated into a deterministic distribution of input data over a wide area on a pixel-by-pixel basis. This paper presents the implementation of different methodologies of integrating satellite-derived information from RS, and GIS （geographic information system） visualization and simulation capabilities in improving hydrologic estimation processes.
基金partially supported by UGM’s Social Fund in the scheme of the RTA Project 2022
文摘The Palu MW7.4 earthquake occurred on September 28, 2018, with the epicenter at 119.86°, 0.72°. The severe shaking caused severe damage in Central Sulawesi, especially in Palu. We conducted a postseismic deformation study to determine the deformation pattern and reduce future earthquakes’ impact.Interferometric Synthetic Aperture Radar(In SAR) data were processed using Li CSBAS to get the time series. The time series data were fitted to exponential and logarithmic functions to determine the mechanism of postseismic deformation. The exponential model identified the influence of the viscoelastic mechanism, and the logarithm identified the afterslip mechanism. The Palu earthquake was fitted to logarithmic and exponential, but the logarithmic was more significant than an exponential function.Afterslip mechanism predominates, and viscoelastic mechanisms play a minor role in this postseismic deformation.
