Article
Environmental Sciences
David Gee, Andrew Sowter, Ahmed Athab, Stephen Grebby, Zhenming Wu, Kateryna Boiko
Summary: The rise of minewater after coalfield abandonment can result in significant changes in hydrogeological conditions, necessitating monitoring to prevent groundwater contamination and surface flooding. This study presents a method using SAR measurements to remotely monitor the rise of minewater in near real-time. The approach is validated in the Horlivka mining agglomeration, Ukraine, revealing a potential environmental catastrophe with potentially radioactive minewater reaching the natural water table between May and August of 2024 due to military conflicts in Donbas.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Pierre-Yves Declercq, Michiel Dusar, Eric Pirard, Jeffrey Verbeurgt, Atefe Choopani, Xavier Devleeschouwer
Summary: Spatio-temporal ground-movement measurements and mappings have been conducted in the Campine coalfield in Belgian Limburg after mine closure. The MT-InSAR technique was used to compare measurements with groundwater head changes and GNSS station data. Radar interferometry estimated ground movement extension and velocity. Results revealed a change from subsidence to uplift conditions in the western part of the coal basin and ongoing uplift in the eastern part. The closure of Zolder coal mine led to a recharge of mine-water aquifers, causing the observed changes.
Article
Environmental Sciences
Yaozong Xu, Tao Li, Xinming Tang, Xiang Zhang, Hongdong Fan, Yuewen Wang
Summary: The study conducted deformation observation experiments in the Datong coalfield using DInSAR, stacking-InSAR, and SBAS-InSAR methods and found that stacking-InSAR is an effective and efficient method for identifying the location and shape of mining deformations.
Article
Chemistry, Multidisciplinary
Shihang Zhou, Hongzhi Wang, Chengfang Shan, Honglin Liu, Yafeng Li, Guodong Li, Fajun Yang, Haitong Kang, Guoliang Xie
Summary: This paper aims to analyze the dynamic evolution law of land subsidence caused by multiple coal seam mining in the Ehuobulake Coal Mine. By combining FLAC3D numerical simulation and SBAS-InSAR technology, the method successfully monitors and analyzes the land subsidence under repeated mining of multiple coal seams. The results show significant asymmetry and increasing subsidence range due to the mining of lower layer coal, and the combined method provides reliable guidance for stability analysis and deformation prediction.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Huini Wang, Kanglun Li, Jun Zhang, Liang Hong, Hong Chi
Summary: This study used SBAS-InSAR technology to monitor surface deformation caused by underground activities in mining areas, quickly and accurately obtaining subsidence information and exploring the advantages of long-term monitoring in complex mining areas.
Article
Environmental Sciences
Federico Di Traglia, Claudio De Luca, Mariarosaria Manzo, Teresa Nolesini, Nicola Casagli, Riccardo Lanari, Francesco Casu
Summary: This study conducted a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) measurements to investigate the deformation phenomena of the Stromboli volcano in Italy. The analysis focused on different periods, revealing the effectiveness of combining different types of InSAR measurements for a comprehensive understanding of volcanic deformation.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Zoran Gojkovic, Milan Kilibarda, Ljiljana Brajovic, Milos Marjanovic, Aleksandar Milutinovic, Aleksandar Ganic
Summary: This paper analyzes time series deformation estimated from Sentinel-1 satellite images to monitor subsidence rates caused by open pit coal mining activities. The study compares the results with geodetic leveling and neotectonic uplift trends, demonstrating the effectiveness of the approach for deformation monitoring and geohazard monitoring.
Article
Environmental Sciences
Mengyao Shi, Honglei Yang, Baocun Wang, Junhuan Peng, Zhouzheng Gao, Bin Zhang
Summary: This study introduces a new method for estimating mining subsidence based on TS-InSAR results, improving boundary constraints and dynamic parameter estimation in the PIM. The experiment demonstrates that the proposed method is more accurate in detecting displacement in mining areas.
Article
Geosciences, Multidisciplinary
Wei Tang, Mingliang Wang, Peixian Li, Guorui Wang, Yueguan Yan, Weitao Yan
Summary: The aim of this study was to investigate regional-scale mining subsidence in the Ningdong coal base area in China using conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) methods. L-band and C-band SAR data from ALOS-2 and Sentinel-1A satellites were analyzed, and a coherence-based SBAS method was used to increase the spatial extent of displacement signals. The results demonstrated the effectiveness of combining L-band and C-band SAR data for monitoring mining subsidence and gaining insights into subsidence dynamics.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Geosciences, Multidisciplinary
Ya-xing Li, Ke-ming Yang, Jian-hong Zhang, Zhi-xian Hou, Shuang Wang, Xin-ming Ding
Summary: This study uses SBAS-InSAR and PS-InSAR techniques to estimate the surface incline and curvature in mining areas, providing a method for monitoring surface deformation beneath buildings.
Article
Environmental Sciences
Moidu Jameela Riyas, Tajdarul Hassan Syed, Hrishikesh Kumar, Claudia Kuenzer
Summary: Public safety and socio-economic development in the Jharia coalfield (JCF) in India critically depend on precise monitoring and comprehensive understanding of coal fires. This study used N-SBAS technique to analyze the spatiotemporal dynamics of coal fires, identifying prominent subsidence areas and temporal variations. The results provide valuable information for developing early warning systems and remediation strategies.
Article
Environmental Sciences
Yuxin Tian, Zhenghai Wang, Bei Xiao
Summary: This study uses the multiscale geographically weighted regression (MGWR) model to investigate spatial heterogeneity in factors influencing ground deformation, and identifies the drivers behind regional variations in ground deformation patterns. Significant ground deformation was found in specific areas of Zhuhai, with the key drivers being NDVI, groundwater extraction intensity, and soft soil thickness. The application of the MGWR model outperformed other regression models in identifying driving forces.
Article
Geochemistry & Geophysics
Guo Zhang, Zixing Xu, Zhenwei Chen, Shunyao Wang, Hao Cui, Yuzhi Zheng
Summary: The forward prediction of mining subsidence in coal mining areas is crucial for evaluating mining risk and improving mine management plans. This study proposed a method based on the logistic model and SBAS-InSAR for coal mining subsidence prediction, which was tested in two coal mining areas in Inner Mongolia. The predicted results were in agreement with the monitoring results, indicating the effectiveness and necessity of the proposed method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Information Systems
Xinpeng Diao, Quanshuai Sun, Yan Zhang, Kan Wu, Jing Yang, Xin Lu, Qiuwen Wang, Jing Wang
Summary: This study investigated the spatiotemporal evolution and deformation mechanism of mining subsidence in regions of fault occurrence using InSAR deformation analysis method. The results showed continuous and abnormal deformation in the working face, with a termination position different from the conventional subsidence basin. Different regions within the influence range of mining exhibited different deformation characteristics.
Article
Environmental Sciences
Hongwei Wang, Yuan Qi, Juan Zhang, Jinlong Zhang, Rui Yang, Junyu Guo, Dongliang Luo, Jichun Wu, Shengming Zhou
Summary: This study analyzed the influence of open-pit coal mining on the ground surface deformation of permafrost in the Muli region of the Qinghai-Tibet Plateau. The results showed that mining activities resulted in landscape destruction and accelerated permafrost degradation. The mining area experienced severe surface deformation, while the alpine marsh meadows exhibited significant subsidence.
Editorial Material
Multidisciplinary Sciences
Fulong Chen, Huadong Guo, Deodato Tapete, Nicola Masini, Francesca Cigna, Rosa Lasaponara, Salvatore Piro, Hui Lin, Peifeng Ma
NATIONAL SCIENCE REVIEW
(2021)
Article
Environmental Sciences
Francesca Cigna, Deodato Tapete
Summary: This paper uses an integrated urban and satellite Interferometric Synthetic Aperture Radar (InSAR) approach to investigate land subsidence, urban growth, and population trends in the Metropolitan Area of Morelia in Mexico, revealing a predominant edge-expansion growth model and a doubling population over the last 30 years. The study also shows that subsidence is structurally-controlled by main normal faults and non-linearly deforming subsidence bowls develop at extraction wells in both old and newly urbanized sectors.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Chemistry, Multidisciplinary
Margherita Berardi, Luigi Santamaria Amato, Francesca Cigna, Deodato Tapete, Mario Siciliani de Cumis
Summary: Volcanic monitoring reports contain valuable geochemical and geophysical data. This study presents a natural language processing system that can extract relevant gas parameters from such reports, as demonstrated by its successful application to monitoring bulletins from Stromboli volcano published between 2015 and 2021.
APPLIED SCIENCES-BASEL
(2022)
Article
Geosciences, Multidisciplinary
F. Cigna, D. Tapete
Summary: This study conducted the largest ever-made analysis of aquifers using satellite imagery, estimating subsidence rates and compaction volumes in Mexico. It found a correlation between InSAR-derived aquifer-system compaction and groundwater deficits, providing valuable information for groundwater management strategies in response to climate change and population growth.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Remote Sensing
Haonan Jiang, Timo Balz, Francesca Cigna, Deodato Tapete, Jianan Li, Yakun Han
Summary: This paper introduces a new multi-sensor InSAR time series data fusion method to address cases when partial overlaps and/or temporal gaps exist. The proposed method, which combines the Power Exponential Knothe Model and LSTM neural network, successfully maps long-term surface deformation in Wuhan by fusing COSMO-SkyMed, TerraSAR-X, and Sentinel-1 SAR datasets.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Editorial Material
Multidisciplinary Sciences
Lei Luo, Jie Liu, Francesca Cigna, Damian Evans, Mario Hernandez, Deodato Tapete, Peter Shadie, Athos Agapiou, Abdelaziz Elfadaly, Min Chen, Lanwei Zhu, Bihong Fu, Ruixia Yang, Shahina Tariq, Mohamed Ouessar, Rosa Lasaponara, Xinyuan Wang, Huadong Guo
Article
Remote Sensing
Francesca Cigna, Timo Balz, Deodato Tapete, Gino Caspari, Bihong Fu, Michele Abballe, Haonan Jiang
Summary: This paper showcases the main research avenues in optical and Synthetic Aperture Radar (SAR) remote sensing for archaeological and cultural heritage applications. It focuses on archaeological prospection and heritage site protection, utilizing novel sensor data, big data, and high-performance computing. Six demonstration use-cases are presented with various heritage asset types and research objectives. The results achieved contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Proceedings Paper
Geosciences, Multidisciplinary
S. Paloscia, E. Santi, S. Pettinato, A. Lapini, G. Fontanelli, S. Pilia, F. Baroni, G. Ramat, L. Santurri, C. Notarnicola, L. De Gregorio, G. Cuozzo, D. Tapete, F. Cigna
Summary: The research aims to develop innovative algorithms for estimating geophysical parameters of soil, snow, and vegetation using SAR and optical images, and monitor their changes and crop conditions. The results show that the estimation of soil moisture, vegetation biomass, snow water equivalent, and crop classification can be improved by using temporal series of images and machine-learning approaches.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Proceedings Paper
Geosciences, Multidisciplinary
Sang-Hoon Hong, Jeong-Heon Ju, Seo-Woo Park, Francesca Cigna
Summary: Ground subsidence, particularly in urban environments, poses a significant geohazard risk. Time-series analyses using multi-frequency SAR observations can be used to detect and study ground subsidence using various InSAR techniques.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Proceedings Paper
Geosciences, Multidisciplinary
Deodato Tapete, Francesca Cigna
Summary: Copernicus Sentinel-1 SAR and Sentinel-2 optical data were combined to document floods and fires affecting cultural heritage in remote or inaccessible locations in the Middle East. Change detection analysis using SAR amplitude and interferometric coherence, as well as the computation of spectral indexes using optical imagery, proved to be effective in accurately mapping the affected areas and temporally constraining the events.
2022 IEEE MEDITERRANEAN AND MIDDLE-EAST GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (M2GARSS)
(2022)
Article
Environmental Studies
Deodato Tapete, Francesca Cigna
Summary: This study evaluates the application of satellite-derived high-resolution digital surface models in Near and Middle Eastern archaeology, and finds that they are reliable for detection and measurement of archaeological mounds. The study also reveals that 53% of the mounds are affected by anthropogenic disturbances and proposes a viable automated method for their detection.
Article
Remote Sensing
Fulong Chen, Huadong Guo, Deodato Tapete, Francesca Cigna, Salvatore Piro, Rosa Lasaponara, Nicola Masini
Summary: This paper reviews the development of imaging radar technology and analyzes its performance and limitations in the field of cultural heritage monitoring and management. It proposes a flexible solution for the integration of imaging radar in cultural heritage through pilot synergy applications in archaeological prospection and cultural heritage diagnosis and conservation.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Engineering, Electrical & Electronic
Giacomo Fontanelli, Alessandro Lapini, Leonardo Santurri, Simone Pettinato, Emanuele Santi, Giuliano Ramat, Simone Pilia, Fabrizio Baroni, Deodato Tapete, Francesca Cigna, Simonetta Paloscia
Summary: This article introduces a method for early-season crop mapping using COSMO-SkyMed X-band dual-polarized data. By using a deep learning convolutional neural network for classification and combining HH+VV backscatter, high classification accuracy is achieved. The study finds that using a 3-D classifier with HH, VV, and HH+VV backscatter can achieve overall accuracy above 90% after June each year. However, relatively low producer accuracy is observed in vineyards and uncultivated fields, requiring further research.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Emanuele Santi, Ludovica De Gregorio, Simone Pettinato, Giovanni Cuozzo, Alexander Jacob, Claudia Notarnicola, Daniel Guenther, Ulrich Strasser, Francesca Cigna, Deodato Tapete, Simonetta Paloscia
Summary: This study estimates the dry snow water equivalent (SWE) in alpine areas using X-band synthetic aperture radar (SAR) data from the COSMO-SkyMed (CSK) satellite constellation. The SAR data is analyzed and compared with in situ measurements, and the sensitivity to SWE is assessed using a radiative transfer model. Two machine learning techniques, artificial neural networks (ANNs) and support vector regression (SVR), are employed to retrieve SWE from the CSK data. The validation results show a high correlation coefficient and low root-mean-square error, indicating the effectiveness of the CSK constellation for dry SWE retrieval in alpine areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Remote Sensing
Chenxiao Zhang, Yukang Feng, Lei Hu, Deodato Tapete, Li Pan, Zheheng Liang, Francesca Cigna, Peng Yue
Summary: This paper proposes a domain adaptation-based multi-source change detection network, which is capable of processing optical and SAR images and achieves the best performance in large-scale change detection tasks.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
