The mining and reclamation of opencast coal mines affect the soil volumetric water content (SVWC1). An accurate measurement of the SVWC is critical for land reclamation. However, traditional methods often damage the soil structure and are time-consuming. Thus, a rapid and non-destructive method is required to measure the SVWC in reclaimed mining areas. This study aimed to evaluate the feasibility and effectiveness of using ground penetrating radar (GPR) for estimating SVWC in reclaimed mining areas. We obtained GPR data and collected soil profile samples from the South Dump of the Antaibao opencast coal mine in Pinglu District, Shuozhou City, Shanxi Province. Random Hough transformation and inverse distance weighted interpolation were used to analyze the two-dimensional soil water layer thickness (SWLT) and SVWC in different soil layers and profiles. The radar estimated and the sampling measured value of SVWC were consistent with the soil depth. The Pearson correlation coefficient (r) between the radar estimated and the sampling measured values of SVWC was 0.850 in different soil layers, the lowest root mean squared error (RMSE) was 0.43%, and the lowest relative root mean square error (RRMSE) was 3.80%. The r was up to 0.959, the lowest RMSE was 0.58% to 0.90%, and the lowest RRMSE was 1.46% in different profiles. These results demonstrate the method's feasibility and effectiveness, enabling the precise non-destructive estimation of SVWC. The results provide valuable technical support for the efficient reclamation and restoration of mining areas.

The conservation of Cultural Heritage in cave environments, especially those hosting cave art, requires comprehensive conservation strategies to mitigate degradation risks derived from climatic influences and human activities. This study, focused on the Polychrome Hall of the Cave of Altamira, highlights the importance of integrating remote sensing methodologies to carry out effective conservation actions. By coupling a georeferenced Ground Penetrating Radar (GPR) with a 1.6 GHz central-frequency antenna along with photogrammetry, we conducted non-invasive and high-resolution 3D studies to map preferential moisture pathways from the surface of the ceiling to the first 50 cm internally of the limestone structure. In parallel, we monitored the dynamics of surface water on the Ceiling and its correlation with pigment and other substance migrations. By standardizing our methodology, we aim to increase knowledge about the dynamics of infiltration water, which will enhance our understanding of the deterioration processes affecting cave paintings related to infiltration water. This will enable us to improve conservation strategies, suggesting possible indirect measures to reverse active deterioration processes. Integrating remote sensing techniques with geospatial analysis will aid in the validation and calibration of collected data, allowing for stronger interpretations of subsurface structures and conditions. All of this puts us in a position to contribute to the development of effective conservation methodologies, reduce alteration risks, and promote sustainable development practices, thus emphasizing the importance of remote sensing in safeguarding Cultural Heritage.

Fractures with fluid flow can lead to the damage of rock carving relics. During the detection of fractures, millimeter-scale fractures are usually difficult to determine due to their small apertures. Considering the rapid variation of water content in the fracture seepage zone can lead to anisotropy, this article proposes a new methodology to detect these millimeter-scale fractures with fluid flow using a time-lapse full-polarimetric ground penetrating radar (FP-GPR) scheme and an anisotropy analysis method. The time-lapse FP-GPR detection can monitor the water flow in the fracture and the infiltration in the rock, and the Freeman decomposition, H-Alpha decomposition, and a polarimetric phase (PP) feature are adopted to quantify and analyze the anisotropic effects over time. In the numerical test, we adopt hydrological modeling to build realistic dielectric models for time-lapse FP-GPR simulations. The results indicate that the variations of water contents and several polarimetric features, i.e., the surface-like scattering power, the double-bounce scattering power, and the averaged scattering angle, are consistent and are essentially related to the anisotropy of the seepage zone. Finally, we introduce the field tests performed at the experimental station of the Dazu Rock Carvings in Chongqing, China, which contain two cases I and II. Case I is an experiment on a surface fracture of a cliff, whereas case II is a detection test of a buried fracture. The results verify the effectiveness of the proposed methodology.

Tree root systems are crucial for providing structural support and stability to trees. However, in urban environments, they can pose challenges due to potential conflicts with the foundations of roads and infrastructure, leading to significant damage. Therefore, there is a pressing need to investigate the subsurface tree root system architecture (RSA). Ground-penetrating radar (GPR) has emerged as a powerful tool for this purpose, offering high-resolution and nondestructive testing (NDT) capabilities. One of the primary challenges in enhancing GPR's ability to detect roots lies in accurately reconstructing the 3-D structure of complex RSAs. This challenge is exacerbated by subsurface heterogeneity and intricate interlacement of root branches, which can result in erroneous stacking of 2-D root points during 3-D reconstruction. This study introduces a novel approach using our developed wheel-based dual-polarized GPR system capable of capturing four polarimetric scattering parameters at each scan point through automated zigzag movements. A dedicated radar signal processing framework analyzes these dual-polarized signals to extract essential root parameters. These parameters are then used in an optimized slice relation clustering (OSRC) algorithm, specifically designed for improving the reconstruction of complex RSA. The efficacy of integrating root parameters derived from dual-polarized GPR signals into the OSRC algorithm is initially evaluated through simulations to assess its capability in RSA reconstruction. Subsequently, the GPR system and processing methodology are validated under real-world conditions using natural Angsana tree root systems. The findings demonstrate a promising methodology for enhancing the accurate reconstruction of intricate 3-D tree RSA structures.

In permafrost regions, active layer thickness (ALT) observations measure the effects of climate change and predict hydrologic and elemental cycling. Often, ALT is measured through direct ground-based measurements. Recently, synthetic aperture radar (SAR) measurements from airborne platforms have emerged as a method for observing seasonal thaw subsidence, soil moisture, and ALT in permafrost regions. This study validates airborne SAR-derived ALT estimates in three regions of Alaska, USA using calibrated ground penetrating radar (GPR) geophysical data. The remotely sensed ALT estimates matched the field observations within uncertainty for 79% of locations. The average uncertainty for the GPR-derived ALT validation dataset was 0.14 m while the average uncertainty for the SAR-derived ALT in pixels coincident with GPR data was 0.19 m. In the region near Utqiavik, the remotely sensed ALT appeared slightly larger than field observations while in the Yukon-Kuskokwim Delta region, the remotely sensed ALT appeared slightly smaller than field observations. In the northern foothills of the Brooks Range, near Toolik Lake, there was minimal bias between the field data and remotely sensed estimates. These findings suggest that airborne SAR-derived ALT estimates compare well with in situ probing and GPR, making SAR an effective tool to monitor permafrost measurements.

Investigations into the susceptibility of permafrost landscapes response to thermokarst can be performed using various approaches, depending on the scale of investigation. In many cases, point-based field measurements are extrapolated to larger scales and vice versa. The integration of scales often requires some form of ground control in addition to remote sensing surveys, which are at times exclusively conducted. As upscaling from discrete field measurements can provide spatial coverage and landscape-scale significance, downscaling from remote sensing can offer insight into processes and serve as calibration or verification. Here we present a multiple-scale evaluation of an area initially interpreted as a relict active layer detachment slide (before 1950) on Melville Island in the High Arctic, where differential interferometric synthetic aperture radar (DInSAR) showed subsidence between 2013 and 2015. Ground-based, cryostratigraphy measurements were combined with ground-penetrating radar (GPR) to investigate permafrost ice-content. The results indicate greater subsidence within the relict active layer detachment as detected by DInSAR. GPR surveys and permafrost coring indicated the presence of an ice-rich or massive ice layer near the base of the active layer in this area. In addition, cryostratigraphic evidences of thaw unconformity and of massive ice depth helped validate the interpretations of the geomorphology in the active layer detachment. This combination of methods indicated a localized and inherited landform-subsidence association, which brought further insight into the interpretation of DInSAR subsidence data. The framework presented in this study demonstrates the importance of site-specific investigations of thermokarst signal in order to understand the processes behind the remote sensing results. (C) 2020 Elsevier B.V. All rights reserved.

Aufeis are sheets of ice unique to cold regions that originate from repeated flooding and freezing events during the winter. They have hydrological importance associated with summer flows and winter insulation, but little is known about the seasonal dynamics of the unfrozen sediment layer beneath them. This layer may support perennial groundwater flow in regions with otherwise continuous permafrost. For this study, ground penetrating radar (GPR) were collected in September 2016 (maximum thaw) and April 2017 (maximum frozen) at the Kuparuk aufeis field on the North Slope of Alaska. Supporting surface nuclear magnetic resonance data were collected during the maximum frozen campaign. These point-in-time geophysical data sets were augmented by continuous subsurface temperature data and periodic Structure-from-Motion digital elevation models collected seasonally. GPR and difference digital elevation model data showed up to 6 m of ice over the sediment surface. Below the ice, GPR and nuclear magnetic resonance identified regions of permafrost and regions of seasonally frozen sediment (i.e., the active layer) underlain by a substantial lateral talik that reached >13-m thickness. The seasonally frozen cobble layer above the talik was typically 3- to 5-m thick, with freezing apparently enabled by relatively high thermal diffusivity of the overlying ice and rock cobbles. The large talik suggests that year-round groundwater flow and coupled heat transport occurs beneath much of the feature. Highly permeable alluvial material and discrete zones of apparent groundwater upwelling indicated by geophysical and ground temperature data allows direct connection between the aufeis and the talik below.

The distribution of the permafrost in the Tibetan Plateau has dramatically changed due to climate change, expressed as increasing permafrost degradation, thawing depth deepening and disappearance of island permafrost. These changes have serious impacts on the local ecological environment and the stability of engineering infrastructures. Ground penetrating radar (GPR) is used to detect permafrost active layer depth, the upper limit of permafrost and the thawing of permafrost with the season's changes. Due to the influence of complex structure in the permafrost layer, it is difficult to effectively characterize the accurate structure within the permafrost on the radar profile. In order to get the high resolution GPR profile in the Tibetan Plateau, the reverse time migration (RTM) imaging method was applied to GPR real data. In this paper, RTM algorithm is proven to be correct through the groove's model of forward modeling data. In the Beiluhe region, the imaging result of GPR RTM profiles show that the RTM of GPR makes use of diffracted energy to properly position the reflections caused by the gravels, pebbles, cobbles and small discontinuities. It can accurately determine the depth of the active layer bottom interface in the migration section. In order to prove the accuracy of interpretation results of real data RTM section, we set up the three dielectric constant models based on the real data RTM profiles and geological information, and obtained the model data RTM profiles, which can prove the accuracy of interpretation results of three-line RTM profiles. The results of three-line RTM bears great significance for the study of complex structure and freezing and thawing process of permafrost at the Beiluhe region on the Tibetan Plateau.

The distribution of shallow frozen ground is paramount to research in cold regions, and is subject to temporal and spatial changes influenced by climate, landscape disturbance and ecosystem succession. Remote sensing from airborne and satellite platforms is increasing our understanding of landscape-scale permafrost distribution, but typically lacks the resolution to characterise finer-scale processes and phenomena, which are better captured by integrated surface geophysical methods. Here, we demonstrate the use of electrical resistivity imaging (ERI), electromagnetic induction (EMI), ground penetrating radar (GPR) and infrared imaging over multiple summer field seasons around the highly dynamic Twelvemile Lake, Yukon Flats, central Alaska, USA. Twelvemile Lake has generally receded in the past 30yr, allowing permafrost aggradation in the receded margins, resulting in a mosaic of transient frozen ground adjacent to thick, older permafrost outside the original lakebed. ERI and EMI best evaluated the thickness of shallow, thin permafrost aggradation, which was not clear from frost probing or GPR surveys. GPR most precisely estimated the depth of the active layer, which forward electrical resistivity modelling indicated to be a difficult target for electrical methods, but could be more tractable in time-lapse mode. Infrared imaging of freshly dug soil pit walls captured active-layer thermal gradients at unprecedented resolution, which may be useful in calibrating emerging numerical models. GPR and EMI were able to cover landscape scales (several kilometres) efficiently, and new analysis software showcased here yields calibrated EMI data that reveal the complicated distribution of shallow permafrost in a transitional landscape. Copyright (c) 2016 John Wiley & Sons, Ltd.