Article
Environmental Sciences
Peppe J. V. D'Aranno, Alessandro Di Benedetto, Margherita Fiani, Maria Marsella, Ilaria Moriero, Jose Antonio Palenzuela Baena
Summary: This study aims to analyze ground displacement using satellite remote sensing data and PSI technique to assess the stability of viaducts and embankments in the metropolitan area of the Gulf of Salerno, as well as understand the activity of the surrounding slopes. By utilizing data from European Space Agency missions and COSMO-SkyMed constellations, the analysis showed a consistency in displacement patterns in different subareas, highlighting the importance of remotely monitoring infrastructure behavior over long periods of time in a complex geological area.
Article
Remote Sensing
Olga Markogiannaki, Hang Xu, Fulong Chen, Stergios Aristotele Mitoulis, Issaak Parcharidis
Summary: Infrastructure monitoring is essential for evaluating capacity and functionality loss, and this study proposes a hybrid approach using D-TomoSAR techniques and engineering forensics to assess the structural condition of a landmark bridge. By analyzing displacement products and deformation trends, potential deterioration issues and vulnerable deck locations are identified, providing valuable evidence for decision-making.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Engineering, Civil
Zheng-Kuan Lee, Marco Bonopera, Chia-Chuan Hsu, Bo-Han Lee, Fang-Yao Yeh
Summary: In this study, a fiber Bragg grating (FBG)-differential settlement measurement (DSM) system was used to monitor the vertical displacement of a prestressed concrete box girder bridge for 2 years. The system showed potential for inexpensive and long-term monitoring of bridges without requiring suitable environmental conditions and intensive labor work.
Article
Environmental Sciences
Constantinos Nefros, Stavroula Alatza, Constantinos Loupasakis, Charalampos Kontoes
Summary: A reliable road network is important for connecting communities and promoting economic growth. Traditional methods for identifying and monitoring landslides on complex road networks are time-consuming and resource-intensive. This study applied parallelized PSI (P-PSI) to quickly identify and monitor potential landslide areas in the Chania regional unit of Crete, Greece, providing a valuable tool for local stakeholders.
Article
Engineering, Multidisciplinary
Shengang Li, Wentao Wang, Bo Lu, Xi Du, Manman Dong, Tianbiao Zhang, Zifan Bai
Summary: Bridges are critical components of transportation infrastructure, and regular inspections are necessary to ensure their long-term performance and public safety. This study presents an in-site structural health monitoring system deployed on the Caohekou Bridge in China, providing continuous real-time data for 4 years. Various structural parameters are monitored and assessed to understand the effects of time and temperature on structural deterioration. Additionally, methods are proposed to predict bridge responses under changing environmental and operational conditions, enabling early warning and effective maintenance decisions.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Chemistry, Analytical
Guido Luzi, Pedro F. Espin-Lopez, Fermin Mira Perez, Oriol Monserrat, Michele Crosetto
Summary: The use of radar interferometric techniques in non-urban areas can be challenging due to the lack of stable natural targets, but this can be partially compensated by installing reference targets. Passive corner reflectors (PCRs) are effective but suffer from drawbacks like being cumbersome and weather-sensitive, while active reflectors (AR) provide a less cumbersome alternative with stable phase response. This paper describes the design, implementation, and testing of an AR prototype aimed at providing a fair performance/cost benefit in areas with hard accessibility.
Article
Remote Sensing
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper explores the capability of a millimetre-wave multiple-input multiple-output (MIMO) radar system for micro-vibration monitoring of pipelines. The results show that the system can accurately detect small displacements and vibrations in pipelines and identify the dominant frequencies. The study validates the high potential of millimetre-wave MIMO radar systems for non-contact monitoring of micro-vibrations in pipelines.
REMOTE SENSING LETTERS
(2023)
Article
Environmental Sciences
Kyriaki Fotiou, Dimitris Kakoullis, Marina Pekri, George Melillos, Ramon Brcic, Michael Eineder, Diofantos G. Hadjimitsis, Chris Danezis
Summary: The urban development of Limassol has rapidly increased in the past five years, raising concerns about potential land subsidence along the coastal front. This study analyzed satellite data and found significant ground subsidence in the Limassol coastal area. The impact of skyscrapers on the coastal front of Limassol was also preliminarily assessed.
Article
Computer Science, Information Systems
Lapo Miccinesi, Alessandra Beni, Massimiliano Pieraccini
Summary: This article proposes a multi-monostatic radar for retrieving the displacement vector, which can simultaneously detect two independent displacement components. The radar was successfully tested in both a controlled environment and on a real bridge, confirming its effectiveness.
Article
Chemistry, Analytical
Jianliang Zhang, Jian Zhang, Zhishen Wu
Summary: This paper proposes an anomaly detection method for structural health monitoring (SHM) data based on LSTM network. The method reduces workload for preparing training sets, achieves real-time anomaly detection, and avoids high alarm rate by utilizing double thresholds. The case study and validation results with actual data show that the proposed method can accurately detect abnormal events.
Article
Chemistry, Analytical
Valerio Gagliardi, Luca Bianchini Ciampoli, Sebastiano Trevisani, Fabrizio D'Amico, Amir M. Alani, Andrea Benedetto, Fabio Tosti
Summary: The research demonstrates the effectiveness of using Sentinel-1A SAR data for continuous and long-term monitoring of millimetre-scale displacements in airport runways, paving the way for more efficient and sustainable maintenance strategies to be included in next generation Airport Pavement Management Systems (APMSs).
Article
Environmental Sciences
Fabio Bovenga, Ilenia Argentiero, Alberto Refice, Raffaele Nutricato, Davide O. Nitti, Guido Pasquariello, Giuseppe Spilotro
Summary: This study uses MTInSAR to investigate the ground stability of two hilly villages in Italy and finds evidence of nonlinear displacements in key infrastructures.
Article
Remote Sensing
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This study develops a ground-based synthetic aperture radar (GBSAR) imaging system and interferometric processing framework for structural health monitoring (SHM). The proposed GBSAR system can monitor sub-millimeter displacements with high spatial resolution and 0.02 mm precision in the LOS direction. It also demonstrates high potential for measuring continuous sub-second LOS displacements and long-term 3D displacement vectors.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Engineering, Civil
Sunjoong Kim, Ho-Kyung Kim, Billie F. Spencer
Summary: This study proposes a machine-learning-based fault-data management approach to accurately estimate damping values by identifying and removing sensor faults in long-term monitored data of large-scale structures. The method uses a support Vector Machine (SVM) and a new feature to classify faulty and normal data, and augments training samples using digital simulation. The effectiveness of the approach is validated using data from a wireless sensor network in a cable-stayed bridge.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2022)
Article
Environmental Sciences
Ankur Pandit, Suryakant Sawant, Jayantrao Mohite, Srinivasu Pappula
Summary: Time-series InSAR coherence products generated from Sentinel-1 data were employed to monitor phenological stages, determine sowing and harvest dates for Bengal-gram crop. The lowest coherence value of 0.29 represents peak vegetation, and sowing/harvesting dates were identified by sudden shifts in coherence trend. The analysis showed that InSAR coherence provides reliable information on crop growth stages and can be used for monitoring other crops as well.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Suresh Krishnan Palanisamy Vadivel, Duk-jin Kim, Jungkyo Jung, Yang-Ki Cho, Ki-Jong Han
Summary: The study utilized InSAR technique to assess the VLM at tide gauges in Korea, revealing overall stability with the largest VLM observed at the Pohang tide gauge station. Higher rates of uplift were observed along the coast of the Yellow Sea, while higher rates of subsidence were observed at Jeju and Seogwipo tide gauges. The approach provides unprecedented spatial and temporal resolution for estimating VLM rates at selected tide gauges when in-situ and GNSS observations are not available.
Article
Geosciences, Multidisciplinary
Seung-Woo Lee, Sung Hyun Nam, Duk-Jin Kim
Summary: This study presents a new algorithm for estimating typhoon winds using multiple satellite observations and applies it to Typhoon Soulik (2018). The algorithm showed reasonable and practical estimates in open ocean conditions, but significantly overestimated parameters when the typhoon rapidly weakened before making landfall. The research highlights the importance of continuously monitoring typhoon winds in real-time using multiple satellite observations for timely and operationally important analysis results.
FRONTIERS OF EARTH SCIENCE
(2022)
Review
Environmental Sciences
Do-Seong Byun, Jin-Yong Jeong, Duk-jin Kim, Sungmin Hong, Kyu-Tae Lee, Kitack Lee
Summary: The Ieodo Ocean Research Station provides a platform for monitoring air and sea environments, with technical lessons learned from five research projects launched since 2016. The purpose is to share experiences and best practices to facilitate future research activities in similar environments.
FRONTIERS IN MARINE SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Juyoung Song, Duk-jin Kim, Sangho An, Junwoo Kim
Summary: This study proposes two novel algorithms to improve the accuracy of vessel detection in synthetic aperture radar (SAR) images. The first algorithm compares the vessel detection output with traditional vessel monitoring apparatus information to demonstrate the position and velocity of vessels. The second algorithm restores the position of the vessel by estimating velocity and measuring the orientation angle. These algorithms show more accurate results compared to traditional methods in the experiments.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Oliver L. Stephenson, Tobias Kohne, Eric Zhan, Brent E. Cahill, Sang-Ho Yun, Zachary E. Ross, Mark Simons
Summary: Satellite remote sensing, especially synthetic aperture radar (SAR), plays a key role in rapid damage mapping after natural disasters. However, current SAR damage mapping methods face challenges in distinguishing damage from other surface changes. This study proposes a novel approach that combines deep learning with the full time history of SAR observations to detect anomalous variations in surface properties due to natural disasters. By using recurrent neural networks (RNN) as probabilistic anomaly detectors on coherence time series, the method shows good agreement with observed damage and quantitative improvement compared to traditional methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Multidisciplinary Sciences
Seung-Tae Lee, Yang-Ki Cho, Duk-jin Kim
Summary: Sea surface temperature (SST) is crucial for understanding coastal seas. Landsat 8 data helps to determine the variability of SST near tidal flats, where the temperature range is higher and the gradients are influenced by heating and cooling from the flats.
SCIENTIFIC REPORTS
(2022)
Article
Environmental Sciences
Junwoo Kim, Hwisong Kim, Hyungyun Jeon, Seung-Hwan Jeong, Juyoung Song, Suresh Krishnan Palanisamy Vadivel, Duk-jin Kim
Summary: The research presents a novel deep learning-based water body extraction model that utilizes Sentinel-1 data and various flood-related geospatial data, showing improved accuracy of up to 7.68% when compared to traditional methods. By customizing and optimizing the U-Net model to incorporate geospatial data, the study demonstrates the potential for operational flood monitoring using deep learning techniques.
Article
Environmental Sciences
Noel Ivan Ulloa, Sang-Ho Yun, Shou-Hao Chiang, Ryoichi Furuta
Summary: This study utilizes synthetic aperture radar (SAR) imagery and deep learning methods for flood mapping, incorporating historical SAR images and spatial features. By differentiating the synthetic image from the post-image, the accuracy of flood-induced change detection can be improved. Experimental results demonstrate that the Convolutional Long Short-Term Memory (ConvLSTM) method achieves higher classification accuracy in flood mapping.
Article
Chemistry, Analytical
Ji-Hwan Hwang, Duk-jin Kim, Ki-Mook Kang
Summary: This paper describes a multifunctional scatterometer system and optimized radar signal processing method for simultaneous observation of various physical oceanographic parameters. By integrating separate measurement functions into a single observation system, the efficiency of system operation and cross-analysis of observation data are improved. The operability of the proposed system was examined through field campaigns, and the observation data was cross-analyzed with in-situ data, showing high accuracy.
Article
Geosciences, Multidisciplinary
Matthew Bonnema, Cedric H. David, Renato Prata de Moraes Frasson, Catalina Oaida, Sang-Ho Yun
Summary: This study presents the global variation of lake and reservoir surface areas using radar remote sensing. The global aggregate area variations were only 2% of total surface area, but the variations of shoreline regions equaled 20% of total surface area. Smaller water bodies contributed more to these variations, and reservoirs tended to be more variable than lakes of similar size. The large surface area variations, especially in small water bodies, could have a previously underappreciated impact on the Earth System.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Junwoo Kim, Hwisong Kim, Duk-jin Kim, Juyoung Song, Chenglei Li
Summary: This article presents a deep learning-based flood area extraction model for a fully automated flood monitoring system. The model was tested and optimized to improve image segmentation accuracy and reduce processing time. The results demonstrate the operation and robustness of the system in accurately extracting flooded areas and reducing misclassification of constructed facilities and mountain shadows. This research could serve as a valuable reference and benchmark for other countries seeking to build cloud-based flood monitoring systems using deep learning.
Article
Geosciences, Multidisciplinary
Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, Sang-Ho Yun
Summary: This article proposes a framework that combines remote-sensing data, supplementary datasets, and machine-learning algorithms to assess building damage caused by earthquakes in a semi-automated manner. The framework integrates building inventory data, earthquake ground shaking intensity maps, and InSAR images to classify the damage state of buildings using ensemble models. Case studies of four recent earthquakes demonstrate the successful identification of damaged buildings using both multi-class and binary classification approaches.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Geochemistry & Geophysics
Zhang-Feng Ma, Sheng-Ji Wei, Xing Li, Yosuke Aoki, Ji-Hong Liu, Xiao-Jie Liu, Wen-Fei Mao, Shun Yang, Nan-Xin Wang, Qi-Huan Huang, Teng Huang, Sang-Ho Yun
Summary: Obtaining millimeter-scale along-track deformations using phase measurements is a challenging task for the InSAR community. In this study, a new time series burst overlap interferometry algorithm is proposed to improve measurement accuracy and achieve high precision along-track deformation measurements.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Hyoseong Lee, Duk-jin Kim
Summary: Tidal flats are internationally protected areas, but also common sites of accidents. Understanding the geomorphologic characteristics of tidal flats is crucial for visitor safety. This article proposes a practical method to correct distorted digital elevation models (DEMs) using a globally collected DEM, effectively estimating changes in tidal flats over time.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Remote Sensing
Juyoung Song, Duk-jin Kim, Ji-hwan Hwang, Sangho An, Junwoo Kim
Summary: This study emphasizes the importance of acquiring precise position and velocity information from GNSS-INS sensors for obtaining SAR images through BPA. Multiple operations of Kalman Filter were conducted to assess the effective order of sensor noise calibration. Experimental results showed that different orders of Kalman Filter applied to FMCW-SAR raw data can achieve optimum BPA image restoration.
KOREAN JOURNAL OF REMOTE SENSING
(2021)