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Illegal coal mining is prevalent worldwide, leading to extensive ground subsidence and land collapse. It is crucial to define the location and spatial dimensions of these areas for the efficient prevention of the induced hazards. Conventional methods for goaf locating using the InSAR technique are mostly based on the probability integral model (PIM). However, The PIM requires detailed mining information to preset model parameters and does not account for the layered structure of the coal overburden, making it challenging to detect underground goaves in cases of illegal mining. In response, a novel method based on the InSAR technique and the Stratified Optimal Okada Dislocation Model, named S-ODM, is proposed for locating goaves with basic geological information. Firstly, the S-ODM employs a numerical model to establish a nonlinear function between the goaf parameters and InSAR-derived ground deformation. Then, in order to mitigate the influence of nearby mining activities, the goaf azimuth angle is estimated using the textures and trends of the InSAR-derived deformation time series. Finally, the goaf's dimensions and location are estimated by the genetic algorithm–particle swarm optimization (GA-PSO). The effectiveness of the proposed method is validated using both simulation and real data, demonstrating average relative errors of 6.29% and 7.37%, respectively. Compared with the PIM and ODM, the proposed S-ODM shows improvements of 19.48% and 52.46% in geometric parameters. Additionally, the errors introduced by GA-PSO and the influence of ground deformation monitoring errors are discussed in this study. [ABSTRACT FROM AUTHOR]

Surface soil moisture is vital for Earth's environmental and energy cycles. However, it is still rare to have remote sensing soil moisture data with a long-term temporal extent, a global seamless spatial coverage, and a near-real-time update frequency. Here, we provided a global seamless soil moisture dataset from July 1981 to December 2022, matching CCI with SMAP through a novel soil moisture data bias correction method (fitting beta CDF matching, BCDF), and filling the gaps of corrected soil moisture through XGBoost Algorithms along with various soil moisture covariates. The new soil moisture dataset was abbreviated as GSSM and it has been validated with in situ observations, original CCI and SMAP data, and simulated gap areas. Results demonstrated that 1) the GSSM has similar accuracy with the SMAP and they are both more accurate than the original CCI data as compared with in situ observations at 399 global sites (averaged R=0.72, averaged ubRMSE<0.05); 2) the GSSM has the global spatial coverage, while filling the gaps of original CCI data through various soil moisture covariates (in artificial gaps verification, averaged R>0.86, averaged ubRMSE<0.04); 3) the GSSM has the same temporal variation characteristics with the original CCI dataset, while it can be combined with SMAP to obtain a long-term and near-real-time soil moisture dataset. Thus, GSSM provides long-term and seamless soil moisture data, paving the way for environmental disaster and water cycle process research. [ABSTRACT FROM AUTHOR]

Ground deformation associated with naturaland anthropogenic activities can be damaging for infrastructure and can cause enormous economic loss, particularly in developing countries which lack measuring instruments. Remote sensing techniques like interferometric synthetic aperture radar (InSAR) can thus play an important role in investigating deformation and mitigating geohazards. Rawalpindi and Islamabad are twin cities in Pakistan with a population of approximately 5.4 million, along with important government and private entities of national and international interest. In this study, we evaluate rapid paced subsidence in this area using a modified small baseline subset technique with Sentinel-IA imagery acquired between 2015 and 2022. Our results show that approximately 50 mm/year subsidence occurs in the older city of Rawalpindi, the most populated zone. We observed that subsidence in the area is controlled by the buried splays of the Main Boundary Thrust, one of the most destructive active faults in the recent past. We suggest that such rapid subsidence is most probably due to aggressive subsurface water extraction. It has been found that, despite provision of alternate water supplies by the district government, a very alarming number of tube wells are being operated in the area to extract ground water. Over 2017-2021, field data showed that near-surface aquifers up to 50-60 m deep are exhausted, and most of the tube wells are currently extracting water from depths of approximately 150-160 m. The dropping water level is proportional to the increasing number of tube wells. Lying downstream of tributaries originating from the Margalla and Murree hills, this area has a good monsoon season, and its topography supports recharge of the aquifers. However, rapid subsidence indicates a deficit between water extraction and recharge, partly due to the limitations inherent in shale and the low porosity near the surface lithology exposed in the area. Other factors amplifying the impacts are fast urbanization, uncontrolled population growth, and non-cultivation of precipitation in the area. [ABSTRACT FROM AUTHOR]

The reuse of leather waste is a global challenge because of the increase of leather products. In this paper, collagen fiber (CF) was extracted from leather waste and polyvinyl alcohol (PVA) gel membranes containing CF with high mechanical property are fabricated by freeze–thaw method. Results shows that the composite gel membrane maintains the helical structure of CF. The tensile strength of the PVA/3CF‐FW increases to 58.5 MPa, while its elongation at break increases to 365%. The swelling ratio increases with the addition of CF, and the PVA/7CF composite gel membrane has the highest swelling ratio, which is 11.65. However, the crystallinity reduced with the addition of CF. Compared to the pure 24PVA gel membrane and the PVA/GA gel membrane, the PVA/CF composite gel membrane prepared by freeze–thaw method has a better mechanical property. Highlights: Taking leather waste as raw material to extract collagen fiber.The gel membranes containing collagen fiber have hardly been reported.The gel membranes show good swelling ratio and mechanical properties. [ABSTRACT FROM AUTHOR]