Article
Engineering, Geological
Dingwen Zhang, Wentao Yang, Chong Xu, Tao Ye, Qiwei Liu
Summary: A new method is proposed in this study to extract deforming landslides from background noise using time-series Sentinel-2 images. The method was tested along a section of the Jinsha River in southwest China and was found to be effective in eliminating background noise and isolating deforming landslides.
Article
Engineering, Mechanical
R. Ceravolo, G. Coletta, G. Miraglia, F. Palma
Summary: This research systematically analyzes a large amount of heterogeneous field data to investigate the factors that have the greatest influence on structural behavior, which could contribute to modeling the behavior of historic buildings for Structural Health Monitoring (SHM) purposes.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Xingyu Wang, Hui Liu, Junzhao Du, Zhihan Yang, Xiyao Dong
Summary: Improving the performance of long-term time series forecasting is crucial for real-world applications. In this paper, we propose a Transformer-based model called CLformer, which integrates a time series decomposition method to extract short and long-term time patterns in more predictable components. Experimental results show that CLformer outperforms models using global autocorrelation and self-attention mechanisms in terms of efficiency and accuracy.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mathematics, Applied
Andrea Tigrini, Federica Verdini, Sandro Fioretti, Alessandro Mengarelli
Summary: In this study, extended detrended fluctuation analysis (EDFA) was applied to investigate the dynamics of human balance maintenance using an inverted pendulum (IP) model with intermittent control. The analysis focused on the changes in long-term correlation and inhomogeneity of the center of pressure (COP) time series. The results showed that the EDFA coefficients were sensitive to changes in the derivative control gain and had a correlation with the p parameter.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2022)
Article
Engineering, Electrical & Electronic
Baohang Wang, Chaoying Zhao, Qin Zhang, Zhong Lu, Antonio Pepe
Summary: The article discusses the continuous monitoring of land subsidence in Xi'an, China using synthetic aperture radar interferometry. The study shows that land subsidence has slowed in some areas while upliftment has been observed in other areas, indicating potential geohazard risks. The proposed approach using multisensor InSAR can provide near-real-time deformation measurements necessary for an early warning system.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Automation & Control Systems
Guoliang Feng, Liyong Zhang, Jianhua Yang, Wei Lu
Summary: This article proposes a method for long-term time series prediction, demonstrating its effectiveness and superior performance in a specific field through comparison tests with other forecasting methods.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Engineering, Geological
Michael J. J. Bentley, Jonathan M. M. Foster, Joshua J. J. Potvin, George Bevan, James Sharp, David J. J. Woeller, W. Andy Take
Summary: This passage discusses the susceptibility of river bank slopes incised into Champlain Sea Clay to highly retrogressive landslides and the concept of progressive failure. It explores whether surface displacement measurements can serve as an indicator of potential expansion of a progressive failure surface. The monitoring program conducted on an inclined slope found that sufficient pre-failure deformations exist to be measurable precursors to progressive failure.
Article
Multidisciplinary Sciences
Hiroshi Okamura, Yutaka Osada, Shota Nishijima, Shinto Eguchi
Summary: Nonlinear phenomena in ecology pose challenges for inference and prediction due to autocorrelation and outliers. Traditional least squares and least absolute deviations methods have limitations, leading to the development of a new robust regression approach that accurately estimates autocorrelation while reducing the influence of outliers. Simulations and real data analysis demonstrate that the new method outperforms existing methods in long-term and short-term prediction of nonlinear estimation problems in spawner-recruitment data.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Artificial Intelligence
Mingxin Tang, Wei Chen, Wen Yang
Summary: This study proposes a model for anomaly detection in state quantity time-series data in industrial systems using correlation supported by long short-term memory. The model is verified using real physical process data and shows superiority over existing industrial time-series models. This research addresses an interesting design methodology for anomaly detection of time-series data in IIoT.
CONNECTION SCIENCE
(2022)
Article
Physics, Fluids & Plasmas
A. S. Il'yn, A. Kopyev, V. A. Sirota, K. P. Zybin
Summary: We study finite-dimensional systems of linear stochastic differential equations with stationary continuous statistically isotropic stochastic processes. We find exact expressions for the Lyapunov and generalized Lyapunov exponents by analyzing the rate function of the diagonal elements of A.
Article
Computer Science, Artificial Intelligence
Yue Cheng, Weiwei Xing, Witold Pedrycz, Sidong Xian, Weibin Liu
Summary: This article proposes a long-term time-series forecasting method based on the nonlinear fuzzy information granule series, which improves the long-term performance of predictors. The method represents information granules with nonlinear time-dependent curves, and introduces a temporal window splitting algorithm based on curvature equations and weighted directed graphs. Nonlinear trend fuzzy granulation is used as a data preprocessing module to achieve better long-term forecasting performance. The proposed method achieves superior performance in traffic flow forecasting compared to existing models.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xingyu Wang, Hui Liu, Junzhao Du, Xiyao Dong, Zhihan Yang
Summary: In multivariate time series forecasting tasks, expanding forecast length and improving forecast efficiency is crucial. The proposed SDCNet model combines time series decomposition and CNNs to capture temporal patterns and inter-variable dependencies in a unified framework, achieving better performance than competing methods.
APPLIED SOFT COMPUTING
(2023)
Article
Environmental Sciences
Baiyu Dong, Yang Ye, Shixue You, Qiming Zheng, Lingyan Huang, Congmou Zhu, Cheng Tong, Sinan Li, Yongjun Li, Ke Wang
Summary: Identifying and classifying shrinking cities using long-term continuous night-time light (NTL) data and population data can provide a more accurate understanding of city shrinkage. The study found that the shrinkage pattern in northeastern China differed between two stages, with population decline and NTL decrease not synchronized in some cities.
Article
Thermodynamics
Congzhi Huang, Mengyuan Yang
Summary: Photovoltaic power is stochastic, intermittent, and volatile, posing challenges to the safe and stable operation of the power grid. To improve the accuracy of PV power forecasting, a MLSTNet model is proposed, using temporal and spatial feature extraction to achieve higher accuracy in ultra-short-term forecasting.
Article
Computer Science, Artificial Intelligence
Beakcheol Jang, Inhwan Kim, Jong Wook Kim
Summary: This study found a time precedence relationship between real-time uploaded web data and influenza outbreaks, proposing a new model for long-term influenza prediction based on this relationship. Experimental results showed that the model performed well in the ten-week long-term prediction.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Geological
Sylvain Fiolleau, Denis Jongmans, Gregory Bievre, Guillaume Chambon, Pascal Lacroix, Agnes Helmstetter, Marc Wathelet, Michel Demierre
Summary: The study reveals that the Harmaliere landslide exhibits two types of behaviors - upper sliding and lower flowing, with a total mass transfer of over 6 x 10(6) m(3) during multiple reactivations, and a mass transfer of 1 x 10(6) m(3) during the 2016 reactivation.
Editorial Material
Geosciences, Multidisciplinary
Yosuke Aoki, Masato Furuya, Francesco De Zan, Marie-Pierre Doin, Michael Eineder, Masato Ohki, Tim J. Wright
EARTH PLANETS AND SPACE
(2021)
Article
Geosciences, Multidisciplinary
P. Pitard, A. Replumaz, M. L. Chevalier, P. H. Leloup, M. Bai, M. P. Doin, C. Thieulot, X. Ou, M. Balvay, H. Li
Summary: Through thermochronology data and thermo-kinematic modeling, the geological features and movement velocities of thrust faults in the crustal thickening history have been determined. The study shows that the structure in the Muli thrust belt has significant changes in thrusting geometry from the surface to depth, and the exhumation of crustal rocks is influenced by deeper crustal processes.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Multidisciplinary Sciences
D. H. Shugar, M. Jacquemart, D. Shean, S. Bhushan, K. Upadhyay, A. Sattar, W. Schwanghart, S. McBride, M. Van Wyk de Vries, M. Mergili, A. Emmer, C. Deschamps-Berger, M. McDonnell, R. Bhambri, S. Allen, E. Berthier, J. L. Carrivick, J. J. Clague, M. Dokukin, S. A. Dunning, H. Frey, S. Gascoin, U. K. Haritashya, C. Huggel, A. Kaab, J. S. Kargel, J. L. Kavanaugh, P. Lacroix, D. Petley, S. Rupper, M. F. Azam, S. J. Cook, A. P. Dimri, M. Eriksson, D. Farinotti, J. Fiddes, K. R. Gnyawali, S. Harrison, M. Jha, M. Koppes, A. Kumar, S. Leinss, U. Majeed, S. Mal, A. Muhuri, J. Noetzli, F. Paul, I Rashid, K. Sain, J. Steiner, F. Ugalde, C. S. Watson, M. J. Westoby
Summary: On February 7, 2021, a catastrophic mass flow hit the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing extensive devastation and casualties. The collapse of rock and glacier ice led to a debris flow that transported large boulders and scoured valley walls, highlighting issues related to monitoring and sustainable development in high-mountain environments like the Himalayas.
Article
Environmental Sciences
Franck Thollard, Dominique Clesse, Marie-Pierre Doin, Joelle Donadieu, Philippe Durand, Raphael Grandin, Cecile Lasserre, Christophe Laurent, Emilie Deschamps-Ostanciaux, Erwan Pathier, Elisabeth Pointal, Catherine Proy, Bernard Specht
Summary: The FLATSIM service aims to process Sentinel-1 data over large areas using multi-temporal InSAR techniques, providing the ForM@ter scientific community with automatically processed products and quality indicators for research in seismology, tectonics, volcano-tectonics, and hydrological cycle.
Article
Geosciences, Multidisciplinary
Season Maharjan, Kaushal Raj Gnyawali, Dwayne D. Tannant, Chong Xu, Pascal Lacroix
Summary: The study introduces a method using Newmark sliding block model to evaluate earthquake-triggered landslides, with the 2015 Gorkha earthquake in Nepal as a case study. By utilizing high-resolution digital elevation models, geological maps, and peak ground acceleration data, the researchers successfully modeled landslide susceptibility and demonstrated the applicability of critical acceleration in rapidly creating earthquake-triggered landslide maps.
FRONTIERS IN EARTH SCIENCE
(2021)
Article
Geosciences, Multidisciplinary
M. Mathey, M-P Doin, P. Andre, A. Walpersdorf, S. Baize, C. Sue
Summary: Based on leveling and GNSS data analysis in the Western European Alps, we propose a new approach to map the uplift pattern using InSAR technology, overcoming the challenges of noise and low signal in mountainous areas. The results are consistent with other geodetic measurements and reveal small-scale spatial variations in the uplift pattern.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Engineering, Geological
Aya Cheaib, Pascal Lacroix, Swann Zerathe, Denis Jongmans, Najmeh Ajorlou, Marie-Pierre Doin, James Hollingsworth, Chadi Abdallah
Summary: This study investigates landslides triggered by earthquakes in a semi-arid region, finding that there are more limited-sized rockfalls near the epicenter and larger deep-seated landslides farther away, which is explained as an interaction between earthquake source properties and local geological conditions. The study also examines the kinematics of earthquakes-accelerated slow-moving ancient landslides.
Article
Environmental Sciences
Floriane Provost, David Michea, Jean-Philippe Malet, Enguerran Boissier, Elisabeth Pointal, Andre Stumpf, Fabrizio Pacini, Marie-Pierre Doin, Pascal Lacroix, Catherine Proy, Philippe Bally
Summary: This article introduces a toolbox called MPIC-OPT for processing optical images, which is aimed at measuring terrain deformation over time. The toolbox provides an end-to-end solution and includes options such as correction and filtering to enhance the accuracy and precision of the measurements. The performance of MPIC-OPT is tested on various use cases and is shown to produce results consistent with in-situ data. The study also highlights the importance of correlation threshold and temporal matching range parameters in the estimation of terrain deformation.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Pascal Lacroix, Theo Gavillon, Clement Bouchant, Jerome Lave, Jean-Louis Mugnier, Samir Dhungel, Flavien Vernier
Summary: In the days to weeks following an earthquake, landslides can exhibit specific post-seismic motions, such as delayed initiation and post-seismic relaxation. This study investigates the co- and post-seismic motions of slow-moving landslides accelerated by the Gorkha earthquake in Nepal. The study identifies 11 slow-moving landslides over an area of 750 km(2) and monitors their motions using satellite images. The post-seismic motions of the landslides are found to be much larger than the co-seismic ones, with a delayed initiation of several days observed in some landslides. The study suggests that the post-seismic motions may be caused by diffusion of groundwater or internal reconfiguration of the landslides.
SCIENTIFIC REPORTS
(2022)
Article
Geosciences, Multidisciplinary
Pascal Lacroix, Joaquin M. C. Belart, Etienne Berthier, Thorsteinn Saemundsson, Kristin Jonsdottir
Summary: Global deglaciation leads to more frequent slope instabilities in mountainous terrains. A study on a large slow-moving landslide in Iceland reveals that the landslide accelerates after a sudden increase in glacier mass loss, causing intense seismic activity.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Geosciences, Multidisciplinary
P. Lacroix, J. Huanca, L. A. Angel, E. Taipe
Summary: This study investigates the kinematics of a large landslide in Peru using high frequency acquisitions of the PlanetScope satellite constellation. The findings reveal a progressive acceleration of the landslide in the 3 months leading up to its failure, with a maximum displacement of 8 m. The high revisit frequency of the satellites enables the application of the Fukuzono method for landslide time-of-failure prediction. Although this study highlights the potential of satellite data in detecting landslide precursors, it also indicates the limited usefulness of optical satellites for predicting landslide time-of-failure.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Jacques Mourey, Pascal Lacroix, Pierre-Allain Duvillard, Guilhem Marsy, Marco Marcer, Emmanuel Malet, Ludovic Ravanel
Summary: This study investigates rockfall activity and its triggering factors in the Grand Couloir du Gouter in France, aiming to provide mountaineers with adaptation strategies. Results show that rockfalls are most frequent during the snowmelt period and there is a clear correlation between rockfall frequency and air temperature. Some rockfalls seem to be triggered by mountaineers. The findings have been used to implement management measures for climbers' safety.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2022)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)