The cessation of dewatering following coalfield abandonment results in the rise of minewater, which can create significant changes in the local and regional hydrogeological regime. Monitoring such change is challenging but essential to avoiding detrimental consequences such as groundwater contamination and surface flooding. Inverse modelling methods using satellite radar interferometry (InSAR) have proven capable for retrospectively mapping minewater level changes, however, there is a need for the capability to remotely monitor changes as they occur. In this study, ground deformation measurements obtained from InSAR are used to develop a method to remotely monitor the spatio-temporal rise of minewater, which could be implemented in near real-time. The approach is demonstrated over the Horlivka mining agglomeration, Ukraine, where there is no other feasible approach possible due to a lack of safe ground access. The results were blindly validated against in-situ measurements before being used to forecast the time until minewater will reach the natural water table and Earth's surface. The findings reveal that, as a result of military conflict in Donbas, an environmental catastrophe could occur where potentially radioactive minewater is forecast to reach the natural water table between May and August of 2024.
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http://dx.doi.org/10.1016/j.scitotenv.2022.159272 | DOI Listing |
Sci Data
January 2025
ESA-ESRIN, Frascati, Rome, Italy.
Sea ice thickness is an essential variable to understand and forecast the dynamic ice cover and can be estimated by satellite altimetry. Nevertheless, it is affected by uncertainties especially from snow depth, a key parameter to derive it from ice freeboard. We developed a snow depth product based on the differences between CryoSat-2 SAR Ku and IceSat-2 laser altimeters which have different snow penetration capabilities.
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December 2024
School of Environment and Resources, Southwest University of Science and Technology, Mianyang 621010, China.
The Daguangbao landslide (DGBL), triggered by the 2008 Wenchuan earthquake, is a rare instance of super-giant landslides globally. The post-earthquake evolution of the DGBL has garnered significant attention in recent years; however, its deformation patterns remain poorly characterized owing to the complex local topography. In this study, we present the first observations of the surface dynamics of DGBL by integrating satellite- and ground-based InSAR data complemented by kinematic interpretation using a LiDAR-derived Digital Surface Model (DSM).
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December 2024
Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China.
Using microwave remote sensing to invert forest parameters requires clear canopy scattering characteristics, which can be intuitively investigated through scattering measurements. However, there are very few ground-based measurements on forest branches, needles, and canopies. In this study, a quantitative analysis of the canopy branches, needles, and ground contribution of Masson pine scenes in C-, X-, and Ku-bands was conducted based on a microwave anechoic chamber measurement platform.
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December 2024
ENSTA Bretagne, Lab-STICC, UMR CNRS 6285, 29806 Brest, France.
Satellite SAR (synthetic aperture radar) imagery offers global coverage and all-weather recording capabilities, making it valuable for applications like remote sensing and maritime surveillance. However, its use in machine learning-based automatic target classification faces challenges, including the limited availability of SAR target training samples and the inherent constraints of SAR images, which provide less detailed features compared to natural images. These issues hinder the effective training of convolutional neural networks (CNNs) and complicate the transfer learning process due to the distinct imaging mechanisms of SAR and natural images.
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December 2024
Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy.
Road safety applications for automotive scenarios rely on the ability to estimate vehicle positions with high precision. Global navigation satellite systems (GNSS) and, in particular, the global positioning system (GPS), are commonly used for self localization. But, especially in urban vehicular scenarios, due to obstructions, they may not provide the requirements for crucial position-based applications.
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