Article
Remote Sensing
Bowen Chi, Huifu Zhuang, Hongdong Fan, Yang Yu, Lei Peng
Summary: In this paper, an adaptive patch-based Goldstein filter (AP-Goldstein filter) is proposed, which adapts patch sizes based on pseudo-variation coefficient and controls noise suppression parameter alpha through pseudo-coherence. The proposed method effectively suppresses phase noise of interferograms while maintaining edge detailed information and improving filtering automation.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Environmental Sciences
Francesca Cigna, Deodato Tapete
Summary: This paper trials the P-SBAS advanced InSAR processing chain on large stacks of Copernicus Sentinel-1 SAR images, showcasing the type and precision of deformation products generated and discussing the potential and challenges of big data processing using cloud/grid infrastructure.
Article
Engineering, Geological
Zijing Liu, Haijun Qiu, Shuyue Ma, Dongdong Yang, Yanqian Pei, Chi Du, Hesheng Sun, Sheng Hu, Yaru Zhu
Summary: This study analyzed the surface displacement, travel distance, and topographic changes of a reactivated landslide in Changhe Town, Gansu Province, China, using field investigation, InSAR, UAV photogrammetry, remote sensing imagery, and digital elevation model. The results indicate that it is a retrogressive landslide with large pre-failure deformation, spatial differences in surface travel distance, and significant changes in local topography and geomorphology.
Article
Geosciences, Multidisciplinary
Emanuele Intrieri, Pierluigi Confuorto, Silvia Bianchini, Carlo Rivolta, Davide Leva, Samuele Gregolon, Vincenzo Buchignani, Riccardo Fanti
Summary: This study proposes a two-folded procedure using ground displacement data measured by a ground-based interferometric radar to detect sinkhole precursors and generate a risk zonation map. The analysis revealed that Camaiore did not experience sinkhole-related subsidence, but measured vertical movements correlated with water table oscillations, suggesting the potential detection of sinkhole precursors. The risk zonation map identifies specific areas for monitoring and can inform urban planning and risk management strategies in sinkhole-prone areas.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Geosciences, Multidisciplinary
J. C. Roman-Herrera, J. Delgado, M. J. Rodriguez-Peces, J. A. Pelaez, J. Garrido
Summary: This study applies a fast evaluation method for seismically-induced landslides at a regional scale in the Granada Basin, southern Spain. The method considers the variability in input data through a logical tree scheme and combines it with five different empirical relations to obtain a final susceptibility map. The results show that southern and eastern sections of the basin are more vulnerable to landslides, especially around the A-92 highway and A-338 road.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Agronomy
Francisco A. Sanchez-Crespo, Jose Rafael Marques da Silva, Maria T. Gomez-Villarino, Eutiquio Gallego, Jose M. Fuentes, Ana Garcia, Francisco Ayuga
Summary: This study successfully utilized new satellite missions, such as Sentinel-1, combined with differential interferometry to monitor erosion in agricultural basins. The technique not only allows for the study of water and tillage erosion, but also enables testing the effectiveness of erosion control measures and verifying the results of different management practices over time.
Article
Environmental Sciences
Hande Mahide Yesilmaden, Cagri Alperen Inan, Bedri Kurtulus, Mustafa Can Canoglu, Ozgur Avsar, Moumtaz Razack
Summary: The study utilizes satellite imagery and SAR technology to analyze land subsidence in the Konya Plain in Turkey, showing that excessive groundwater extraction leads to significant subsidence rates, with a maximum value reaching 16 cm. The researchers used DInSAR technique and analyzed satellite images from three periods to provide accurate information on ground deformation.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Engineering, Geological
Hengyi Chen, Chaoying Zhao, Rongrong Sun, Liquan Chen, Baohang Wang, Bin Li
Summary: This study combines multi-temporal distributed scatterer InSAR technology and multi-platform SAR measurements to monitor the deformation of Zongling landslides. The results show that this technical route can provide high spatial-temporal sampling density of landslide deformation and generate new insights into the impact of natural factors and mining activities on karst landslides.
Article
Engineering, Electrical & Electronic
Akshar Tripathi, Arjuman R. Reshi, Md Moniruzzaman, Khan R. Rahaman, Reet K. Tiwari, Kapil Malik
Summary: This study utilizes Sentinel-1 and GRACE satellite data to investigate urban surface subsidence and explores the impact of groundwater exploitation on surface subsidence through correlation analysis and gravimetric anomaly estimation.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Environmental
Felipe Gonzalez
Summary: This study evaluates the structural stability of a phosphogypsum (PG) stack near Huelva, Spain, using a differential SAR interferometry (DInSAR) algorithm. The results reveal vertical and horizontal displacements, as well as the vulnerability of the stack to adverse weather conditions.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2022)
Article
Multidisciplinary Sciences
Baoxing Jiang, Kun Zhang, Xiaopeng Liu, Yuxi Lu
Summary: To address the issue of large prediction errors caused by the existing models' neglect of the correlation between subsidence points, a Multi-point Relationship Fusion (MRF) prediction model based on Graph Convolutional Networks (GCN) was proposed for mining-induced subsidence. Using surface deformation data obtained from 250 InSAR images and GNSS observation data, the MRF-GCN model demonstrated better accuracy than other models, with an R2 value of 0.865 and a MSE of 1.59899. Therefore, it can be applied to predict surface subsidence in large areas.
Article
Engineering, Geological
Andre Cahyadi Kalia
Summary: This study demonstrates the use of a semi-automatic method to detect spatial and temporal patterns in Sentinel-1 PSI datasets for landslide monitoring. The results show a correlation between surface deformation and a potential triggering factor, and the findings are verified using an independent dataset.
Article
Environmental Sciences
Ruonan Zhao, Zhabko Andrey Viktorovich, Junfeng Li, Chuang Chen, Meinan Zheng
Summary: This paper presents a strategy for extracting three-dimensional mining deformation using single-geometry SAR data. The methodology includes modeling the relationship between horizontal displacement and subsidence gradient and proposing a solution strategy to improve stability. The proposed method allows for the reconstruction of 3D displacements in mining areas using various types of SAR data. The effectiveness of the method is validated through simulation and in-site data, showcasing its applicability in mining deformation monitoring.
Article
Geochemistry & Geophysics
Gustavo H. X. Shiroma, Marco Lavalle, Sean M. Buckley
Summary: This article presents a projection algorithm that uses area elements to represent radar samples and associates them with map coordinates. It accurately performs geocoding and slant-range projection, while improving computation efficiency.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Pavlos Krassakis, Stavroula Kazana, Fulong Chen, Nikolaos Koukouzas, Issaak Parcharidis, Efthymios Lekkas
Summary: The study focuses on specific areas around the riverbeds of hidden urban streams in Athens, highlighting the high risk of ground subsidence. Through the analysis of historical data, technical studies, and satellite radar data, the study identifies potential risks associated with soil erosion and vertical displacements in the city.
GEOCARTO INTERNATIONAL
(2021)
Article
Geography, Physical
S. Mohammad Mirmazloumi, Yismaw Wassie, Jose Antonio Navarro, Riccardo Palama, Vrinda Krishnakumar, Anna Barra, Maria Cuevas-Gonzalez, Michele Crosetto, Oriol Monserrat
Summary: This study aims to investigate the temporal behavior of ground deformation time series and proposes a modified automatic classification workflow to classify ground deformations into seven main trends. The approach shows potential in accurately identifying ground movement types, detecting anomalies, and correctly recognizing stable targets, with an overall classification accuracy of 77.8%.
GISCIENCE & REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Lorenzo Nava, Oriol Monserrat, Filippo Catani
Summary: In this study, deep learning convolutional neural networks (CNNs) were used to compare the mapping and classification performances of optical images and synthetic aperture radar (SAR) images in landslide detection. The results showed that CNNs based on optical images achieved an overall accuracy of 98.96% in landslide detection, while CNNs based on SAR data reached accuracies beyond 95% in ground range detection.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Ali Bounab, Kamal Agharroud, Younes El Kharim, Rachid El Hamdouni, Layachi Faghloumi
Summary: This study investigated the effects of training data and computation technique selection on the accuracy and performance of landslide susceptibility maps (LSMs). The results showed that including relict landslides in the training data decreases the accuracy of LSMs, while the choice of different predictive variables combinations has a less significant impact. Models produced using frequency ratio and logistic regression tend to perform better, and artificial neural networks seem to outperform other models.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Yismaw Wassie, S. Mohammad Mirmazloumi, Michele Crosetto, Riccardo Palama, Oriol Monserrat, Bruno Crippa
Summary: Satellite-based interferometric synthetic aperture radar (InSAR) is a valuable technique for detecting and monitoring changes on the earth's surface. The multi-temporal differential InSAR (DInSAR) methods estimate the spatio-temporal deformation, but face challenges in resolving the inherent ambiguities of interferometric phases. Quality indices are proposed as important tools for achieving ultimate processing outcomes in DInSAR data processing.
Article
Environmental Sciences
Lorenzo Nava, Kushanav Bhuyan, Sansar Raj Meena, Oriol Monserrat, Filippo Catani
Summary: Multiple landslide events are common worldwide and can cause significant damage. This study explores the potential of SAR data combined with other data sources to map landslides, even under cloud cover. The findings demonstrate that the combination of SAR data and DL algorithms can help quickly map landslides, even during storms and under deep cloud cover.
Article
Environmental Sciences
Riccardo Palama, Michele Crosetto, Jacek Rapinski, Anna Barra, Maria Cuevas-Gonzalez, Oriol Monserrat, Bruno Crippa, Natalia Kotulak, Marek Mroz, Magdalena Mleczko
Summary: This work presents a methodology using interferometric synthetic aperture radar (InSAR) to analyze and monitor ground motion caused by underground mining activities in the Legnica-Glogow copper district, Poland. The technique utilizes a stack of Sentinel-1 synthetic aperture radar images and a small baseline multitemporal approach. The estimated displacement maps and time series are validated using global navigation satellite system (GNSS) measurements. The method is also used to analyze seismic tremors triggered by underground mining activities.
Article
Environmental Sciences
S. Mohammad Mirmazloumi, Angel Fernandez Gambin, Riccardo Palama, Michele Crosetto, Yismaw Wassie, Jose A. Navarro, Anna Barra, Oriol Monserrat
Summary: In this study, machine learning models were used to classify DInSAR time series, and their performance was evaluated. The study found that customized features significantly improved the accuracy of classification. The importance of different features in classification was also analyzed, and the reliability of the models was validated.
Article
Environmental Sciences
S. Mohammad Mirmazloumi, Mohammad Kakooei, Farzane Mohseni, Arsalan Ghorbanian, Meisam Amani, Michele Crosetto, Oriol Monserrat
Summary: This study proposes a workflow to generate a high-resolution LULC map of Europe using satellite images and survey data. By employing object-based segmentation algorithm, Artificial Neural Network, and rule-based post-processing steps, the generated map exhibits high accuracy in classification and identification of LULC classes.
Article
Remote Sensing
Guido Luzi, Anna Barra, Qi Gao, Pedro F. Espin-Lopez, Riccardo Palama, Oriol Monserrat, Michele Crosetto, Xavier Colell
Summary: A C-band low-cost active reflector was tested in an experimental campaign for monitoring a landslide-threatened area. With a network of passive corner reflectors and one active reflector installed along a forested slope, interferograms were processed to evaluate area stability. Despite temperature sensitivity, the active reflector operated with acceptable stability for deformation retrieval in monitoring purposes.
REMOTE SENSING LETTERS
(2022)
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
Geochemistry & Geophysics
Riccardo Palama, Oriol Monserrat, Bruno Crippa, Michele Crosetto, Guadalupe Bru, Pablo Ezquerro, Marta Bejar-Pizarro
Summary: This study investigates the potential of high-resolution synthetic aperture radar (SAR) images in generating digital elevation models (DEMs) using the radargrammetry technique. Two SAR images recorded by Capella Space X-band satellite radar sensor over La Palma during the Cumbre Vieja volcanic eruption are processed. An iterative point aggregation algorithm is adopted to identify matching pixels and height estimation is performed using distance minimization routine. The resultant radargrammetric DEM is validated against a lidar-based DEM, showing good agreement in less affected areas. Lava thickness estimation is conducted and compared with photogrammetry estimates from Pleiades mission data.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Review
Chemistry, Multidisciplinary
Rosa Maria Mateos, Roberto Sarro, Andres Diez-Herrero, Cristina Reyes-Carmona, Juan Lopez-Vinielles, Pablo Ezquerro, Monica Martinez-Corbella, Guadalupe Bru, Juan Antonio Luque, Anna Barra, Pedro Martin, Agustin Millares, Miguel Ortega, Alejandro Lopez, Jorge Pedro Galve, Jose Miguel Azanon, Susana Pereira, Pedro Pinto Santos, Jose Luis Zezere, Eusebio Reis, Ricardo A. C. Garcia, Sergio Cruz Oliveira, Arnaud Villatte, Anne Chanal, Muriel Gasc-Barbier, Oriol Monserrat
Summary: Coastal regions in Southwest Europe have undergone significant changes due to tourism-related urban development, making them highly vulnerable to the impacts of climate change. This study analyzed extreme weather events along the Atlantic and Mediterranean coasts of Southwest Europe from 2009 to 2020, quantifying their impacts on fatalities, injuries, and economic losses. The results showed an upward trend in the number of events, as well as human losses and damages. The Mediterranean coast, especially the Spanish Mediterranean coast, had a higher exposure due to rapid tourism growth and inadequate preparation for marine storms.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Belizario A. Zarate, Rachid El Hamdouni, Tomas Fernandez del Castillo
Summary: This case study focuses on the monitoring and characterization of landslides in El Plateado, Ecuador. Aerial images captured by a remotely piloted aerial vehicle (RPAS) were processed to generate high-resolution digital elevation models (DEMs) and orthoimages for analysis. The study found that the landslide has high slope and roughness, with notable changes in the main scarp and toe tip. The presence of fissures and rainfall infiltration contribute to instability. The study provides insights into landslide measurement accuracy, identification of elements, morphometric analysis, and the relationship with geotechnical factors.
Proceedings Paper
Geosciences, Multidisciplinary
Riccardo Palama, Oriol Monserrat, Bruno Crippa, Michele Crosetto, Guadalupe Bru, Pablo Ezquerro, Marta Bejar-Pizarro
Summary: In this study, the potential of generating precise DEMs using SAR data is investigated. The adopted method involves radargrammetry on consecutive SAR images, and the resultant DEM is compared with a Lidar-based DEM to evaluate its accuracy.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Article
Environmental Sciences
Ali Bounab, Younes El Kharim, Rachid El Hamdouni
Summary: This study assesses the impact of different resolution DEMs on the accuracy of rockfall simulations, finding that low to medium resolution DEMs result in large errors in the simulated trajectories and runout distances, while the 1m UAV-derived model produces more accurate results.