東京工業大学 · 工学
サドラ・カラムザデ教授の研究室は、人工衛星の合成開口レーダー(SAR)を活用した地震被害評価・地盤変動モニタリングを主軸としています。特に、地震後の建物損傷や道路の粗さ、舗装の劣化をSARデータと深層学習、機械学習を融合して評価する先進的な研究が特徴です。また、湖の干ばつに伴う地盤沈下や都市部の交通影響を考慮した高分解能SAR解析技術の開発も進めています。
Figures are computed from collected data and may differ slightly.
On 24 August 2016, the M 6.2 Amatrice earthquake struck central Italy, well-known as a seismically active region, causing considerable damage to buildings in the town of Amatrice and the surrounding area. Damage from this earthquake was assessed quantitatively by means of multitemporal synthetic aperture radar (SAR) coherence and SAR intensity methods using dual-polarized SAR data obtained from the Sentinel-1 (VV, VH) and ALOS-2 (HH, HV) satellites. We developed linear discriminant functions bas
In this study, we monitor pavement and land subsidence in Tabriz city in NW Iran using X-band synthetic aperture radar (SAR) sensor of Cosmo-SkyMed (CSK) satellites (2017-2018). Fifteen CSK images with a revisit interval of ~30 days have been used. Because of traffic jams, usually cars on streets do not allow pure backscattering measurements of pavements. Thus, the major paved areas (e.g., streets, etc.) of the city are extracted from a minimum-based stacking model of high resolution (HR) SAR im
This study is a new assessment of damaged roads after the Kumamoto earthquake in southern Japan (2016) using remotely sensed synthetic aperture radar (SAR) data, field data and deep learning. Three SAR images from descending orbits of Sentinel-1 in VV (vertical-vertical) polarizations are considered for radiometric calibration, geocoding and interferometric analyses. Field data in terms of the IRI (international roughness index) were gathered over more than 530 km using a smartphone acceleromete
Small earthquakes following a large event in the same area are typically aftershocks, which are usually less destructive than mainshocks. These aftershocks are considered mainshocks if they are larger than the previous mainshock. In this study, records of aftershocks (M > 2.5) of the Kermanshah Earthquake (M 7.3) in Iran were collected from the first second following the event to the end of September 2018. Different machine learning (ML) algorithms, including naive Bayes, k-nearest neighbors,
In this study, we used fifty-six synthetic aperture radar (SAR) images acquired from the Sentinel-1 C-band satellite with a regular period of 12 days (except for one image) to produce sequential phase correlation (sequential coherence) maps for the town of Sarpole-Zahab in western Iran, which experienced a magnitude 7.3 earthquake on 12 November 2017. The preseismic condition of the buildings in the town was assessed based on a long sequential SAR coherence (LSSC) method, in which we considered
We present deformation patterns in the Lake Urmia Causeway (LUC) in NW Iran based on data collected from four SAR sensors in the form of interferometric synthetic aperture radar (InSAR) time series. Sixty-eight images from Envisat (2004-2008), ALOS-1 (2006-2010), TerraSAR-X (2012-2013) and Sentinel-1 (2015-2017) were acquired, and 227 filtered interferograms were generated using the small baseline subset (SBAS) technique. The rate of line-of-sight (LOS) subsidence of the LUC peaked at 90 mm/year
The August 24, 2016, M 6.2 Amatrice earthquake in central Italy was one of the most destructive earthquakes in recent years, and it caused considerable human losses. The goal of this study is to distinguish between collapsed and standing buildings in the town of Amatrice using synthetic aperture radar (SAR) data acquired from the COSMO-SkyMed satellite. Data from both ascending and descending orbits in single HH polarization were evaluated separately. Two main representative change indices, SAR
The evaluation of buildings damage following disasters from natural hazards is a crucial step in determining the extent of the damage and measuring renovation needs. In this study, a combination of the synthetic aperture radar (SAR) and light detection and ranging (LIDAR) data before and after the earthquake were used to assess the damage to buildings caused by the Kumamoto earthquake. For damage assessment, three variables including elevation difference (ELD) and texture difference (TD) in pre-
We performed interferometric synthetic aperture radar (InSAR) analyses to observe ground displacements and assess damage after the M 6.6 Hokkaido Eastern Iburi earthquake in northern Japan on 6 September 2018. A multitemporal SAR coherence map is extracted from 3-m resolution ascending (track 116) and descending (track 18) ALOS-2 Stripmap datasets to cover the entire affected area. To distinguish damaged buildings associated with liquefaction, three influential parameters from the space-based In
This study aimed to classify an urban area and its surrounding objects after the destructive M7.3 Kermanshah earthquake (12 November 2017) in the west of Iran using very high-resolution (VHR) post-event WorldView-2 images and object-based image analysis (OBIA) methods. The spatial resolution of multispectral (MS) bands (~2 m) was first improved using a pan-sharpening technique that provides a solution by fusing the information of the panchromatic (PAN) and MS bands to generate pan-sharpened imag
Different methods have been proposed to create seismic site condition maps. Ground-based methods are time-consuming in many places and require a lot of manual work. One method suggests topographic data as a proxy for seismic site condition of large areas. In this study, we mainly focused on the use of an ASTER 1c digital elevation model (DEM) to produce Vs30 maps throughout Iran using a GIS-based regression analysis of Vs30 measurements at 514 seismic stations. These maps were found to be compar
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