The paper presents new radar maps of the south polar region of the Moon at 4.2 cm wavelength with an average spatial resolution of 90 m. The maps are based on radar images obtained in 2023 using the 64-m TNA-1500 antenna of the Bear Lakes Satellite Communications Center of the Special Design Bureau of the Moscow Power Engineering Institute and the 13.2-m RT-13 radio telescopes at the Svetloe and Zelenchukskaya observatories of the Institute of Applied Astronomy of the Russian Academy of Sciences. Radar images are formed in a specific coordinate system relating the Doppler frequency shift with the propagation time delay of the echo components, which makes it difficult to tie them to selenographic coordinates. In this paper, an original method for converting echo Doppler frequency and time delay to selenographic latitude and longitude is proposed, using bilinear interpolation by ephemeris nodal values, taking into account long integration times. The accuracy of the reference of the maps constructed in this way was assessed and compared with the LROC WAC global optical map of the Moon and mosaics of permanently shadowed regions from LROC NAC. It is shown that radar maps at 4.2 cm wavelength contain features of the lunar surface that are hidden in optical images and are located in the regolith at depths of up to 1 m or in permanently shadowed regions of the south polar region of the Moon. The maps of the lunar echoes specular and diffuse polarization components, as well as a map of the distribution of circular polarization ratios, are available on the Internet at http://luna.iaaras.ru/ and can be useful for studying the geological history of the Moon, searching for ice deposits, and selecting safe landing sites when planning future lunar missions.

Permafrost, a critical global cryospheric component, supports subarctic boreal forests but is frequently disturbed by wildfires, an important driver of permafrost degradation. Wildfires reduce vegetation, organic layers, and surface albedo, leading to active layer thickening and ground subsidence. Recent studies using interferometric synthetic aperture radar (InSAR) have confirmed the rapid and extensive post-fire permafrost degradation, and have largely focused on short-term impacts. However, the longer-term post-fire permafrost deformation, potentially persisting for decades, remains poorly understood due to limited data. Here, we applied InSAR in North Yukon to detect deformation signals across multiple fire scars in the past five decades. Using a chronosequence (space-for-time substitution) approach, we summarize a continuous trajectory of post-fire permafrost evolution: (a) an initial degradation stage, characterized by abrupt subsidence up to 50 mm/year and gradually slowing over the first decade, with cumulative subsidence exceeding 100 mm locally; (b) an aggradation stage from approximately 15 to 30 years after fire, marked by ground uplift reaching 25 mm/year before gradually declining, compensating for the earlier subsidence; and (c) a stabilization stage beyond three to four decades, where permafrost nearly recovers to pre-fire conditions with indistinguishable deformation between burned and unburned areas. Notably, the rarely-reported uplift phase appears closely related to vegetation regeneration and fire-greening feedback that provide thermal protection, suggesting a critical mechanism of permafrost recovery. These findings provide new insights into the resilience of boreal-permafrost systems to wildfires and also underscore the importance of long-term InSAR monitoring in understanding permafrost responses to wildfires under climate change.

Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere. This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau, China, as well as in the related ecological and hydrological processes. However, the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques. Thus, this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected (GRD) data, the polarization decomposition parameters of Sentinel-1A single-look complex (SLC) data, the normalized difference vegetation index (NDVI) based on Sentinel-2B data, and the topographic factors based on digital elevation model (DEM) data. By combining these parameters with a machine learning model, we established a feature selection rule. A cumulative importance threshold was derived for feature variables, and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination (R2) and the unbiased root mean square error (ubRMSE). The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion, and the SHapley Additive exPlanations (SHAP) method was used to analyze the importance of these variables. The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion. Compared to the unfiltered model, the optimal feature combination led to a 0.09 increase in R2 and a 0.7% reduction in ubRMSE. Ultimately, the optimized model achieved a R2 of 0.87 and an ubRMSE of 5.6%. Analysis revealed that soil particle size had significant impact on soil water retention capacity. The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable, demonstrating a significant positive correlation. Moreover, the microtopographical features of hummocks interfered with soil moisture estimation, indicating that such terrain effects warrant increased attention in future studies within the permafrost regions. The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau, but also exhibits high computational efficiency (with a relative time reduction of 18.5%), striking an excellent balance between accuracy and efficiency. This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data, offering critical insights for ecological conservation, water resource management, and climate change adaptation on the Qinghai-Xizang Plateau.

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.

This study investigates the detectability of a putative layer of regolith containing water ice in the lunar polar regions using ground penetrating radar (GPR). Numerical simulations include realistic variations in the relative permittivity of the lunar regolith, considering both density and, for the first time, the effects of temperature on permittivity profiles. We follow the case of previous theoretical studies of water migration, which suggest that water ice accumulates at depths ranging from a few centimeters to tens of centimeters, appropriate depths to explore using GPR. In particular, frequency-modulated continuous wave (FMCW) radar is well-suited for this purpose due to its high range resolution and robust signal-to-noise ratio. This study evaluates two scenarios for the presence of lunar water ice: (1) a layer of regolith containing water ice at a depth of 5 cm, with a thickness of 5 cm, and (2) a layer of regolith containing water ice at a depth of 20 cm, with a thickness of 10 cm. Our computational results show that FMCW GPR, equipped with a dynamic range of 90 dB, is capable of detecting reflections from the interfaces of these layers, even under conditions of low water ice content and using antennas with low directivity. In addition, optimized antenna offsets improve the resolution of the upper and lower interfaces, particularly when applied to the surface of ancient crater ejecta. This study highlights the critical importance of understanding subsurface density and temperature structures for the accurate detection of water-ice-bearing regolith layers.

Flash floods are highly destructive natural disasters, particularly in arid and semi-arid regions like Egypt, where data scarcity poses significant challenges for analysis. This study focuses on the Wadi Al-Barud basin in Egypt's Central Eastern Desert (CED), where a severe flash flood occurred on 26-27 October 2016. This flash flood event, characterized by moderate rainfall (16.4 mm/day) and a total volume of 8.85 x 106 m3, caused minor infrastructure damage, with 78.4% of the rainfall occurring within 6 h. A significant portion of floodwaters was stored in dam reservoirs, reducing downstream impacts. Multi-source data, including Landsat 8 OLI imagery, ALOS-PALSAR radar data, Global Precipitation Measurements-Integrated Multi-satellite Retrievals for Final Run (GPM-FR) precipitation data, geologic maps, field measurements, and Triangulated Irregular Networks (TINs), were integrated to analyze the flash flood event. The Soil Conservation Service Curve Number (SCS-CN) method integrated with several hydrologic models, including the Hydrologic Modelling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), and European Hydrological System Model (MIKE-SHE), was applied to evaluate flood forecasting, watershed management, and runoff estimation, with results cross-validated using TIN-derived DEMs, field measurements, and Landsat 8 imagery. The SCS-CN method proved effective, with percentage differences of 5.4% and 11.7% for reservoirs 1 and 3, respectively. High-resolution GPM-FR rainfall data and ALOS-derived soil texture mapping were particularly valuable for flash flood analysis in data-scarce regions. The study concluded that the existing protection plan is sufficient for 25- and 50-year return periods but inadequate for 100-year events, especially under climate change. Recommendations include constructing additional reservoirs (0.25 x 106 m3 and 1 x 106 m3) along Wadi Kahlah and Al-Barud Delta, reinforcing the Safaga-Qena highway, and building protective barriers to divert floodwaters. The methodology is applicable to similar flash flood events globally, and advancements in geomatics and datasets will enhance future flood prediction and management.

The existence of dispersive clay soils can cause serious erosion, void, and structural damage due to an imbalance of the electrochemical forces within the particles, which causes the soil particles to be repulsive instead of being attracted to each other. Dispersivity is observed in several highway embankments in Mississippi, and the embankments have eroded and developed voids over time. The current study investigated the root cause of the voids observed within the subgrade of the state highway 477 in Mississippi and evaluated the dispersivity of high cations-based soil. As part of an investigative initiative, a 2D Ground Penetration Radar (GPR) of the highway embankment road to make a 2D profile of the soil subsurface media was surveyed to reveal that potential hotspots were overlooked, leading to suspected soil dispersivity and subsequent issues. To assess the extent of visible voids and sinkholes, dispersive tests, including the Double Hydrometer Test (DHT), were conducted to evaluate the dispersivity of the clay soils. A series of boreholes were drilled along the roadway to collect the soil samples, determine their physical properties, and identify clay soil dispersity within the soil profile. Following the confirmation of dispersive soil existence through these tests, advanced analyses, such as Scanning Electron Microscope (SEM) to identify the microstructures and the ionic compositions of the soil particles and Toxicity Characteristic Leaching Procedure Tests (TCLPT) to assess the solubility of high concentrated elements in liquid, were performed to comprehend the root cause of the soil dispersion. Based on the results of the analysis, the GPR wave cannot pass through the subgrade, which mostly happens due to the presence of the charge within the soil. Based on SEM, DHT, and TCLP test results, the soil samples have high cations, including the presence of K + . Moreover, a similar distribution of the ionic compositions was observed among the majority of the soil samples; however, the percent of dispersion regarding clay soil particles varied.

Waterlogging is a significant concern in urban areas and can result in severe disruptions and damage and it's an urban problem. This study is conducted in Thoothukudi and Tamil Nadu, which are particularly sensitive to waterlogging because of their geographical and meteorological circumstances. Using synthetic aperture radar (SAR) images from 2015 to 2022, topographical analysis, land use/land cover (LULC) data, and geological insights, this research intends to identify and assess areas prone to water logging. The data source for this study comprises rainfall records from the Indian Meteorological Department (IMD), Sentinel-1 SAR imagery, Sentinel-2 multispectral images from the European Space Agency (ESA), and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM).Terrain analysis was undertaken using DEM to generate elevation, slope, and aspect maps, while SAR data were processed to extract water pixels, which included the extraction of water pixels from SAR data for each year and overlaying them. The overlaid image was correlated with topographic maps to identify the high-risk regions. Key places such as Muthayapuram, Milavittan, Bryant Nagar, and Thalamuthunagar were constantly highlighted as prone to floods. Additionally, the saltpan regions, defined by low-lying water table levels, endure continuous flooding, demonstrating the usefulness of combining SAR imaging with topographic analysis for urban water management. These findings provide useful insights for urban planners and policymakers, underlining the need for deliberate steps to reduce waterlogging, maintain public health, and minimize infrastructure damage, thus enabling sustainable development in Thoothukudi.

In this study, a methodology is proposed to use dual-polarimetric synthetic aperture radar (SAR) to identify the spatial distribution of soil liquefaction. The latter is a phenomenon that occurs in conjunction with seismic events of a magnitude generally higher than 5.5-6.0 and which affects loose sandy soils located below the water table level. The methodology consists of two steps: first the spatial distributions of soil liquefaction is estimated using a constant false alarm rate method applied to the SPAN metric, namely the total power associated with the measured polarimetric channels, which is ingested into a bitemporal approach to sort out dark areas not genuine. Second, the obtained masks are read in terms of the physical scattering mechanisms using a child parameter stemming from the eigendecomposition of the covariance matrix-namely the degree of polarization. The latter is evaluated using the coseismic scenes and contrasted with the preseismic one to have rough information on the time-variability of the scattering mechanisms occurred in the area affected by soil liquefaction. Finally, the obtained maps are qualitatively contrasted against state-of-the-art optical and interferometric SAR methodologies. Experimental results, obtained processing a time-series of ascending and descending Sentinel-1 SAR scenes acquired during the 2023 Turkiye-Syria earthquake, confirm the soundness of the proposed approach.

Reservoir landslides represent a significant geological hazard that jeopardizes the safety of reservoirs. Deformation monitoring and numerical simulation are essential methodologies for elucidating the evolutionary patterns of landslides. Nonetheless, the existing approaches exhibit limitations in revealing the potential deformation mechanism. Consequently, this study proposes an innovative strategy that incorporates interferometric synthetic aperture radar (InSAR) deformation characteristics alongside fluid-solid coupling stress analysis to investigate the deformation, focusing on the Shuizhuyuan landslide within the Three Gorges Reservoir area as a case study. Using temporary coherence point InSAR technology, significant motion units were identified, with a maximum deformation rate of -60 mm/yr. The complete deformation time series reveals three independent components of landslide movement and their trigger factors geometrically. Subsequently, the saturation permeability coefficient of the sliding mass in the seepage analysis is modified with the assistance of InSAR deformation. Then, we coupled the seepage analysis results to FLAC3D model for stress and strain analysis, and determined the seepage-induced progressive failure mechanism and the deformation mode of the Shuizhuyuan landslide, driven by reservoir water-level (RWL) drop. The numerical simulation results aid in interpreting the deformation mechanism of different spatial and temporal patterns of landslides from three aspects: hydrodynamic pressure from rainfall infiltration, groundwater hysteresis caused by RWL drop, and seepage forces from RWL rise. Furthermore, our findings reveal that the dynamic factor of safety (FOS) of landslide during the InSAR observation period is highly consistent with the periodic fluctuations of the RWL. However, there is also a small trend of overall decline in FOS that cannot be ignored.