ORCID Profile
0000-0002-5419-1362
Current Organisation
National Research and Innovation Agency
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Publisher: IEEE
Date: 21-12-2022
Publisher: IOP Publishing
Date: 11-2016
Publisher: IOP Publishing
Date: 06-2019
DOI: 10.1088/1755-1315/280/1/012004
Abstract: Lombok Island was hit by a series of earthquakes in July and August 2018 with magnitude 6 class. This series of earthquakes resulted in fatalities and material losses that even reached Sumbawa Island to the east of Lombok Island. The earthquake was triggered by Flores back arc thrust resulting in ground deformation. Ground deformation can be identified by satellite-based remote sensing method. The Sentinel-1A and Sentinel-1B satellites are two satellites carrying C-band SAR sensors with a temporal resolution of 12 days each for the same orbit, and the difference in time between the two is 6 days. Therefore, ground deformation related to seismo-tectonic or volcanic activities can be identified by interfering two SAR images (interferometric synthetic aperture radar or InSAR) at least in 6 days. By utilizing Sentinel Application Platform (SNAP) a free open source software (FOSS) and combining with other InSAR software, an interferogram that represents line of sight displacement (LOS) between ground and satellite can be generated. Line of sight displacement can then be interpreted as ground deformation signals. It is shown that the series of Lombok earthquake cause an uplift up to 70cm and subsidence up to 25cm. This deformation affects areas around epicentre. A field survey was conducted to obtain information directly and it was seen that the ground deformation that was identified with the InSAR technique were consistent with the findings in the field. This shows the advantages of remote sensing in terms of ability to cover a wide area in a short time.
Publisher: Penerbit BRIN
Date: 17-03-2023
DOI: 10.55981/BRIN.668
Abstract: Prosiding Use Cases Artificial Intelligence Indonesia adalah buku yang mengumpulkan hasil-hasil kajian dan liputan 26 use cases inovasi dan 4 inisiatif pemanfaatan kecerdasan artifisial yang kemudian dipetakan menjadi lima klaster bidang kecerdasan artifisial, yakni: riset industri dan hankam, layanan publik dan kesehatan, kota cerdas dan kebencanaan, ketahanan pangan dan maritim, serta klaster inisiatif pemanfaatan kecerdasan artifisial. Materi buku diperoleh dari para kontributor seluruh anggota quadhelix dan para narasumber pegiat kecerdasan artifisial di Indonesia. Buku ini akan membantu masyarakat dalam mendapatkan pengetahuan dan pencerahan tentang seluruh teknologi kecerdasan artifisial yang membantu sektor-sektor terkait dalam hal otomatisasi, alat bantu untuk menganalisis, membuat rekomendasi serta keputusan, memprediksi dan sebagainya.
Publisher: Springer Science and Business Media LLC
Date: 12-04-2016
Publisher: IEEE
Date: 24-11-2022
Publisher: IEEE
Date: 24-11-2022
Publisher: Informa UK Limited
Date: 04-08-2023
Publisher: Elsevier BV
Date: 11-2023
Publisher: IEEE
Date: 08-2019
Publisher: IEEE
Date: 11-2018
Publisher: IEEE
Date: 08-2019
Publisher: IOP Publishing
Date: 06-2019
DOI: 10.1088/1755-1315/280/1/012021
Abstract: Sentinel satellite imagery using radar sensors for one particular area with the same orbit can be compared every 6 days and freely available to be downloaded. This advantage can be exploited to regularly identify land surface changes in a particular region. Paddy is a fast-growing crop with an approximately 120-day life cycle and specific growth stages related to phenological aspect, especially to changes in plant height. Hence, paddy growth stages can be monitored using this radar sentinel satellite with dual polarization data. Radar satellite is also cloud-free and therefore suitable for tropical regions such as Indonesia. This paper describes the results of a study on paddy field observation based on a correlation analysis between backscatter values of Sentinel-1A data with paddy growth stage observation. Sentinel-1A data from January 2018 to May 2018 were downloaded and processed using SNAP software. The study observed 5 stages: early vegetative (V1), late vegetative (V2), generative (G), Harvest (P), and Land Preparation (PL). An experiment was conducted by collocating the backscatter value of pixels at the location of the paddy growth stage observations, grouping and calculating the frequency for each class and then removing the class that had small frequency. These steps were carried out by way of iterations until the condition was above 5% of the threshold. Classification was performed based on range value obtained from the experiment to create paddy growth stage polygons. Correlation value between backscatter value σ 0 VH and paddy growth stage observation was 0.758. While correlation value between backscatter value σ 0 VV and paddy growth stage observation was 0.537.
Publisher: World Scientific Publishing Co. Pte. Ltd.
Date: 2009
Publisher: IEEE
Date: 29-09-2021
Publisher: IEEE
Date: 29-09-2021
Publisher: Informa UK Limited
Date: 25-03-2010
Publisher: IEEE
Date: 09-2018
Publisher: IEEE
Date: 09-2018
Publisher: IEEE
Date: 21-12-2022
Publisher: IEEE
Date: 21-12-2022
Publisher: Lembaga Penelitian dan Pengabdian kepada Masyarakat ITS
Date: 08-2014
Publisher: IEEE
Date: 09-2018
Publisher: Hindawi Limited
Date: 06-03-2021
DOI: 10.1155/2021/6625774
Abstract: Information about oil palm phenology is required for oil palm plantation management, but using spaceborne polarimetric radar imagery remains challenging. However, spaceborne polarimetric radar on X-, C-, and L-band is promising on structure vegetation and cloud area. This study investigates the scattering model of oil palm phenology based on spaceborne X-, C-, and L-band polarimetric Synthetic Aperture Radar (SAR) imaging. The X-, C-, and L-band polarimetric SAR are derived from spaceborne of TerraSAR-X, Sentinel-1A, and ALOS PALSAR 2. Study area is located in oil palm plantations, Asahan District, North Sumatra, Indonesia. The methodology includes data collection, preprocessing, radiometric calibration, speckle filtering, terrain correction, extraction of scattering value, and development of scattering model of oil palm phenology. The results showed different scattering characteristics for the X-, C-, and L-band polarimetric SAR of oil palm for age and found the potential of the scattering model for oil palm phenology based on the X-band on HH polarization that showed a nonlinear model with R 2 = 0.65 . The C-band on VH and VV polarization showed a nonlinear model with R 2 = 0.56 and R 2 = 0.89 . The L-band on HV and HH polarization showed a logarithmic model with R 2 = 0.50 and R 2 = 0.51 . In this case, the most potential of the scattering model of oil palm phenology based on R 2 is using C-band on VV polarization. However, the scattering model based on X-, C-, and L-band is potentially to be used and applied to identify the phenology of oil palm in Indonesia, which is the main parameter in yield estimation. For the future phenology model needs to improve accuracy by integrating multisensors, including different wavelengths on optical and microwave sensors and more in situ data.
Publisher: IEEE
Date: 07-12-2020
Publisher: Elsevier BV
Date: 07-2014
Publisher: IEEE
Date: 11-2021
Publisher: IEEE
Date: 21-12-2022
Publisher: AIP Publishing
Date: 2023
DOI: 10.1063/5.0124872
Publisher: IEEE
Date: 10-2019
Publisher: World Scientific Publishing Company
Date: 05-2010
Publisher: IEEE
Date: 29-09-2021
Publisher: Elsevier BV
Date: 02-2012
Publisher: American Geophysical Union (AGU)
Date: 06-2012
DOI: 10.1029/2011JB008940
Publisher: Lembaga Penelitian dan Pengabdian kepada Masyarakat ITS
Date: 02-2016
Publisher: IEEE
Date: 24-11-2022
Publisher: Penerbit BRIN
Date: 17-03-2023
Abstract: Indonesia terletak di daerah khatulistiwa, jalur pertemuan beberapa lempeng tektonik, dan dilalui jalur gunung api dunia. Kondisi ini membuat Indonesia menjadi daerah rawan bencana alam berupa gempa, tsunami, letusan gunung api dan bencana turunan dari kondisi hidrometeorologi, seperti banjir, longsor, kekeringan, dan kebakaran lahan. Wilayah daratannya seluas 1,9 juta kilometer persegi didiami oleh populasi dengan laju pertumbuhan 1,49% per tahun dan diproyeksikan berjumlah 285 juta jiwa pada 2025. Pertumbuhan ekonomi dan hasil pembangunan memproyeksikan bahwa 65% dari populasi ini berdiam di wilayah perkotaan dan beberapa di antaranya rawan bencana. Selain itu, infrastruktur dibangun mengikuti populasi dan pusat kegiatan yang kadang terletak di zona rawan bencana sehingga terdapat potensi kerusakan jika terjadi bencana. Terkait dengan bencana, upaya yang dilakukan berupa mitigasi dan adaptasi. Fenomena bencana hidrometeorologi sudah dapat dimodelkan berdasarkan data dan teknologi utamanya kecerdasan artifisial yang saat ini terus berkembang. Selain itu, untuk pengembangan wilayah dan tata ruang, model spasial dinamis dikembangkan berbasis sistem cerdas. Saat ini, Pusat Teknologi Pengembangan Sumber Daya Wilayah mengkaji satu purwarupa, yaitu Sistem Informasi Simulasi Spasial Dinamik Tata Guna Lahan (SIMULAN). Sistem ini dikembangkan untuk memahami perubahan lahan secara spasial, dinamika perkembangan wilayah dan perkotaan secara real time, dan memodelkan kemungkinan perubahan lahan. Saat ini, SIMULAN fokus pada wilayah pesisir dan menghasilkan model simulasi dalam perubahan lahan terkait dengan mitigasi bencana tsunami. Dalam hal ini, diikaji dua skenario, yaitu skenario perubahan lahan pada kondisi normal (sesuai dengan arahan dokumen rencana tata ruang) dan skenario dengan adanya potensi bahaya tsunami. Wilayah yang dipilih adalah Kawasan Kuta Selatan (Kabupaten Badung, Bali). Selain itu, SIMULAN juga diarahkan untuk dapat memahami dan menilai kerusakan lingkungan yang disebabkan alih fungsi lahan dan bencana alam dengan memanfaatkan data penginderaan jauh dan sistem informasi geografis yang diolah menjadi sebuah model prediksi perubahan guna lahan spasial berbasis cellular automata. Pengembangan teknologi ini diharapkan menjadi salah satu dasar dalam pengambilan keputusan oleh para pemangku kebijakan yang terkait dengan penataan ruang dan perencanaan pembangunan wilayah dengan menganalisis tren perubahan lahan dengan berbagai skenario yang dikembangkan serta d ak perubahan lahan (seperti lingkungan dan ekonomi) pada level lokal, regional, dan nasional.
Publisher: Springer Science and Business Media LLC
Date: 09-2007
DOI: 10.1186/BF03352046
Abstract: 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.
Publisher: IEEE
Date: 11-2021
Publisher: IEEE
Date: 21-12-2022
Publisher: IEEE
Date: 09-2018
Publisher: Walter de Gruyter GmbH
Date: 10-2020
Abstract: On 6 December 2016 at 22:03 UTC, a devastating magnitude 6-class strike-slip earthquake occurred along an unidentified and unmapped fault in Pidie Jaya, northern Sumatra. We analysed the possible fault using continuous Global Positioning System (GPS) observation available in the region. In our investigation, we searched for the fault source parameters of the north- and south-dipping left-lateral faults and the west- and east-dipping right-lateral faults. We identified that the fault responsible for the earthquake was located offshore, with a southwest-northeast direction. We also computed the Coulomb failure stress and compared the result with the distribution of the aftershocks. In this study, we demonstrated that the result of the geological field survey conducted soon after the mainshock was attributed to the secondary effects of ground shaking and near-surface deformation, and not surface faulting. The newly identified offshore fault proposed by this study calls for further investigation of the corresponding submarine morphological attributes in this particular region.
Publisher: IOP Publishing
Date: 06-2018
Publisher: IEEE
Date: 21-12-2022
No related grants have been discovered for Agustan Agustan.