Article
Environmental Sciences
Weiwu Feng, Qiang Li, Wenxue Du, Dongsheng Zhang
Summary: The key technologies of remote 3D displacement sensing of civil structures based on stereo-DIC are proposed in this study. An adaptive stereo-DIC extrinsic parameter calibration method is developed by fusing epipolar-geometry-based and homography-based methods. A reliable reference frame based on Euclidean transformation is established for displacement monitoring. The feasibility and accuracy of the proposed system are validated through experiments and applied to sense the dynamic operating displacement of a wind turbine's blades.
Article
Geochemistry & Geophysics
Fanzhi Cao, Tianxin Shi, Kaiyang Han, Pu Wang, Wei An
Summary: This letter presents a method called Robust Deep Feature Matching (RDFM) for robust feature matching in multimodal remote-sensing images. RDFM utilizes pretrained deep features extracted by a VGG network for template matching, and achieves competitive performance without additional training. Experimental results demonstrate the effectiveness of RDFM in overcoming nonlinear radiation difference (NRD) caused by modality variations.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Frans-Jan W. Parmentier, Lennart Nilsen, Hans Tommervik, Elisabeth J. Cooper
Summary: Near-surface remote sensing techniques are crucial for monitoring vegetation phenology and community, as described in this paper which presents a measurement network in the high Arctic valley of Adventdalen. The data collection, processing overview, and dataset availability are highlighted, along with examples of how the data can be utilized for monitoring different vegetation communities.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Engineering, Electrical & Electronic
Dongxing Liang, Jinshan Ding, Yuhong Zhang
Summary: This article proposes a fast matching approach based on dominant orientation of gradient (DOG) for robust image registration in the presence of nonlinear intensity variations. The method constructs DOG feature maps and utilizes template matching with sum of cosine differences similarity measurement to determine correspondences between images. Additionally, a variable template matching (VTM) method is developed to improve matching precision and performance.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Dou Quan, Shuang Wang, Yu Gu, Ruiqi Lei, Bowu Yang, Shaowei Wei, Biao Hou, Licheng Jiao
Summary: This article proposes a deep feature correlation learning network (Cnet) for multi-modal remote sensing image registration. The network enhances feature representation by focusing on meaningful features and improves network training stability and decreases the risk of overfitting through a designed feature correlation loss function. Extensive experimental results demonstrate the effectiveness and robustness of the proposed method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Multidisciplinary
Kimiya Azimbeik, Seyed Hossein Mahdavi, Fayaz Rahimzadeh Rofooei
Summary: The aim of this study is to enhance image-based, full-field displacement measurement using new template-matching and camera-calibration methods. Practical methods to increase the number of pixels in the images, using free markers and improving camera-calibration methods are also investigated.
Article
Geochemistry & Geophysics
Wenping Ma, Na Li, Hao Zhu, Kenan Sun, Zhongle Ren, Xu Tang, Biao Hou, Licheng Jiao
Summary: In this article, a collaborative correlation-matching network (CCM-Net) is proposed for multimodality RS image classification. The bidirectional dominant feature supervision learning and interactive correlation feature matching learning are used to alleviate the modal differences and extract effective multimodality features.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Remote Sensing
Ming Liu, Gaoxiang Zhou, Lingfei Ma, Liangzhi Li, Qiong Mei
Summary: Multisource satellite images provide abundant and complementary earth observations, but the nonlinear distortions between these multimodal images pose challenges for remote sensing applications. We propose a template matching algorithm called SIFNet based on self-attention interactive fusion network to align these images. Experimental results show that SIFNet achieves comparable accuracy in template matching and is robust to geometric distortions and radiometric variations of multisource remote sensing data.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Editorial Material
Environmental Sciences
Paolo Mazzanti, Saverio Romeo
Summary: Remote sensing technology has great potential in providing valuable information on natural hazards and risks at various scales. Recent advances in technology and processing methods have contributed significantly to disaster risk reduction research. This Special Issue collects state-of-the-art research that focuses on the use of remote sensing for detecting, assessing, monitoring, and modeling natural hazards, showcasing 18 open-access papers that utilize a wide range of remote sensing data and techniques.
Article
Optics
Wang Lianpo
Summary: This study proposes a super-robust DIC method based on learning templates, which mitigates the influence of various disadvantage factors in a straightforward and unified approach, significantly improving the robustness of DIC measurement.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Geochemistry & Geophysics
Yizhang Liu, Yanping Li, Luanyuan Dai, Taotao Lai, Changcai Yang, Lifang Wei, Riqing Chen
Summary: This method achieves the best performance by integrating motion consistency into the general region growing pipeline to handle different deformations.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Geochemistry & Geophysics
Dong Li, Yinling Guo, Suping Peng, Chuangjian Li, Peng Lin
Summary: Time-lapse seismic data analysis is important for monitoring changes in reservoirs and detecting CO2 plumes. In order to address the inconsistency issue in time-lapse data caused by various factors, a correlation-based recurrent attention network (CRAN) is proposed. The network utilizes cross correlation to calculate the correlation between seismic traces and introduces a channel attention mechanism to assign weights to different features. The results of testing on synthetic and field data demonstrate that CRAN significantly enhances the repeatability of time-lapse data and accurately reveals CO2 plumes.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Yafei Lv, Wei Xiong, Xiaohan Zhang, Yaqi Cui
Summary: In this study, a fusion-based correlation learning model is proposed to address the heterogeneity gap in remote sensing image-text retrieval. By designing a cross-modal fusion network and utilizing knowledge distillation, this model improves the discriminative ability of feature representation and enhances the intermodality semantic consistency.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Engineering, Multidisciplinary
Zhenning Liang, Jinxiu Zhang, Longhui Qiu, Guangyi Lin, Fengfu Yin
Summary: The digital image correlation technique with non-fixed camera is developed for deformation measurement in the field, providing a more flexible and convenient method to measure deformation of high altitude facilities. Multiple images and feature templates are used for correction to ensure accuracy.
Article
Optics
Yinsheng Lv, Pinhua Xie, Jin Xu, Ang Li, Zhaokun Hu, Youtao Li, Huarong Zhang, Zhidong Zhang, Xin Tian, Feng Hu, Jiangyi Zheng, Yingjie Ye
Summary: This paper investigates the measurement of SO2 concentration using Fabry-Perot interferometer correlation spectroscopy. The experimental system is designed with a separated beam entering the F-P cavity at two incidence angles simultaneously. The system achieves a 2 sigma detection limit of 28.2 ppm·m(15 cm) at a sampling frequency of 10 Hz. The study introduces a non-dispersive, highly accurate, and fast gas detection technique.
Article
Computer Science, Interdisciplinary Applications
Niccolo Dematteis, Daniele Giordan, Bruno Crippa, Oriol Monserrat
Summary: The local adaptive multiscale image matching algorithm (LAMMA), which reduces the number of calculations in traditional methods, is applied to measure glacier flow in the Southern Patagonian Icefield, demonstrating its efficiency in computation and outlier displacement. The algorithm shows comparable runtime efficiency to frequency-based methods.
COMPUTERS & GEOSCIENCES
(2022)
Article
Engineering, Geological
Niccolo Dematteis, Aleksandra Wrzesniak, Paolo Allasia, Davide Bertolo, Daniele Giordan
Summary: In the field of landslide monitoring, assessing the spatially-distributed three-dimensional surface displacement is crucial but challenging. This study presents a methodology that combines robotic total station measurements and digital image correlation to achieve spatially-distributed three-dimensional surface displacement. The developed method shows promising results and can be easily implemented using lowcost portable field equipment.
ENGINEERING GEOLOGY
(2022)
Article
Engineering, Civil
D. Gisolo, M. Previati, I. Bevilacqua, D. Canone, M. Boetti, N. Dematteis, J. Balocco, S. Ferrari, A. Gentile, M. N'sassila, B. Heery, H. Vereecken, S. Ferraris
Summary: Ecosystems in the Alps are challenging to measure and model due to their complex morphology and the limited availability of information. This study proposes a radiation-driven hydrological model for predicting actual evapotranspiration and estimating soil-water balance, which has been validated and performs well for mountain grassland.
JOURNAL OF HYDROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Niccolo Dematteis, Daniele Giordan, Paolo Perret, Melchior Grab, Hansruedi Maurer, Fabrizio Troilo
Summary: This research investigates the influence of bedrock geometry on glacier surface morphology through measurements of ice thickness, detection of bedrock topography, and analysis of glacier surface morphology and kinematics. The findings highlight the importance of frequent monitoring of glacier morphology for accurate glacier hazard assessment.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Martina Cignetti, Danilo Godone, Davide Notti, Francesco Zucca, Claudia Meisina, Massimiliano Bordoni, Laura Pedretti, Luca Lanteri, Davide Bertolo, Daniele Giordan
Summary: This paper presents a dedicated procedure using Advanced Differential Interferometric SAR (A-DInSAR) techniques to analyze deep-seated gravitational slope deformations (DsGSDs) and their interactions with anthropic elements. The study investigates the displacement of Motta de Plete and Champlas du Col areas in northwestern Italy over a long time period using multi-temporal A-DInSAR data. The methodology provides a powerful tool for understanding the local dynamics of DsGSDs in relation to strategic infrastructures and inhabited areas, aiding in infrastructure maintenance and territorial planning.
Editorial Material
Environmental Sciences
Daniele Giordan, Guido Luzi, Oriol Monserrat, Niccolo Dematteis
Article
Engineering, Geological
Niccolo Menegoni, Daniele Giordan, Riccardo Inama, Cesare Perotti
Summary: An open-source MATLAB application called DICE was developed to quantitatively characterize fractures or discontinuities in rocky outcrops using 3D digital data. The application analyzes and maps the detected fractures, calculates their orientation, position, and dimensions, and determines various discontinuity parameters using different 3D oriented sampling techniques.
JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING
(2023)
Article
Geochemistry & Geophysics
Niccolo Dematteis, Daniele Giordan, Bruno Crippa, Oriol Monserrat
Summary: Measuring glacier elevation change is crucial for various purposes, such as estimating glacier mass balance, calibrating climate models, and assessing the impact of global warming. In this study, we explored the potential of clinometry as a technique to quantify glacier elevation changes. By analyzing shadow positions in monoscopic optical images, we were able to measure a glacier thinning rate of -1.9 +/- 1.7 ma(-1) between 2017 and 2021 for the Aletsch Glacier (Switzerland), consistent with previous observations.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geosciences, Multidisciplinary
Aldo Bertone, Roberto Seppi, Mattia Callegari, Giovanni Cuozzo, Niccolo Dematteis, Karl Krainer, Carlo Marin, Claudia Notarnicola, Francesco Zucca
Summary: The kinematic acceleration of rock glaciers observed in recent decades is related to climate change. While velocity variations on yearly to seasonal time scales are frequently investigated, velocity changes measured on shorter time scales (i.e., on hourly resolutions) are as yet poorly understood. In this study, we used ground-based synthetic aperture radar to investigate the displacement of a rock glacier on an hourly time scale in the European Alps. Our observations revealed a regular hourly velocity rhythm characterized by short phases of sharp acceleration (up to 0.9 mm/hr) lasting 4-11 hr followed by long phases of stagnation lasting 13-20 hr. This unprecedented observation opens up new perspectives in the analysis and interpretation of rock glacier kinematics.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Engineering, Geological
Martina Cignetti, Danilo Godone, Davide Notti, Daniele Giordan, Davide Bertolo, Fabiana Calo, Diego Reale, Simona Verde, Gianfranco Fornaro
Summary: A dedicated procedure has been implemented to explore the behavior and define the state of activity of 279 deep-seated gravitational slope deformations (DsGSDs) in the Aosta Valley Region. The procedure involves the use of Differential Interferometry Synthetic Aperture Radar (DInSAR) techniques to detect and identify Persistent Scatterers (PSs) and assess Sentinel-1 data coverage. Spatial analysis based on cluster and outlier identification is carried out to characterize the moving phenomena and their degree of variability in deformation rates. The methodology provides a valid instrument to remotely define the state of activity of these phenomena, which are often underestimated or neglected in risk management.
Article
Geosciences, Multidisciplinary
Davide Notti, Martina Cignetti, Danilo Godone, Daniele Giordan
Summary: The widespread availability of Sentinel-2 data and high-resolution images makes it possible to map shallow landslides triggered by extreme events at a low cost. This study presents a two-phase procedure to detect and map shallow landslides using Sentinel-2 images. The results show that the semi-automatic mapping based on Sentinel-2 allows for detecting the majority of shallow landslides larger than satellite ground pixel.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Environmental Sciences
Davide Cardone, Martina Cignetti, Davide Notti, Danilo Godone, Daniele Giordan, Fabiana Calo, Simona Verde, Diego Reale, Eugenio Sansosti, Gianfranco Fornaro, Marco Polcari, Letizia Anderlini, Antonio Montuori
Summary: This paper proposes a new method to analyze the morpho-structural domain of DsGSDs using remote sensing and A-DInSAR technology, and tests two phenomena with different orientations. The results show variations in the kinematic behavior between morpho-structural domains, providing a rapid and low-cost tool to assess the impact of DsGSDs on human facilities and infrastructure in mountainous areas.
