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One of the most intense geomagnetic storms of recent times occurred on 10–11 May 2024. With a peak negative excursion of Sym‐H below −500 nT, this storm is the second largest of the space era. Solar wind energy transferred through radiation and mass coupling affected the entire Geospace. Our study revealed that the dayside magnetopause was compressed below the geostationary orbit (6.6 RE) for continuously ∼6 hr due to strong Solar Wind Dynamic Pressure (SWDP). Tremendous compression pushed the bow‐shock also to below the geostationary orbit for a few minutes. Magnetohydrodynamic models suggest that the magnetopause location could be as low as 3.3RE. We show that a unique combination of high SWDP (≥15 nPa) with an intense eastward interplanetary electric field (IEFY ≥ 2.5 mV/m) within a super‐dense Interplanetary Coronal Mass Ejection lasted for 409 min–is the key factor that led to the strong ring current at much closer to the Earth causing such an intense storm. Severe electrodynamic disturbances led to a strong positive ionospheric storm with more than 100% increase in dayside ionospheric Total Electron Content (TEC), affecting GPS positioning/navigation. Further, an HF radio blackout was found to occur in the 2–12 MHz frequency band due to strong D‐ and E‐region ionization resulting from a solar flare prior to this storm. Plain Language Summary: Life and a habitable atmosphere are sustained on Earth thanks to the protective and far‐stretched magnetic shield around the Earth, known as the Magnetosphere, which protecting the humanosphere from the hazardous solar wind particles that are continuously emanated from the Sun. However, massive solar wind ejections from the Sun often disturb the Earth's magnetosphere and affect mankind and critical space‐ and ground‐based technological infrastructure. When higher amounts of the solar wind traveling with supersonic speeds impact, the Earth's magnetosphere compresses significantly, and the crucial satellites in space become directly exposed to hazardous solar wind. Further, strong and rapid disturbances in the geomagnetic field and ionosphere could significantly affect the operations of various technical systems on ground, like electrical power grids, GNSS‐based precise navigation, etc. The strongest geomagnetic storm of the past three decades has recently occurred on 10–11 May 2024. This study investigates the solar sources and the possible mechanisms responsible for the occurrence of such an intense geomagnetic storm and also details the drastic reconfiguration of Earth's magnetosphere and significant ionospheric disturbances observed during this storm. Key Points: Strong SWDP caused a highly compressed magnetosphere with magnetopause pushed below geostationary orbit (6.6 RE) continuously for 6 hrThe highly compressed magnetosphere led an intense ring current at much closer distance to the EarthA super‐dense ICME with high SWDP (>15 nPa) and IEFY (>2.5 mV/m) sustaining for 409 min ‐ a key factor responsible for this intense storm [ABSTRACT FROM AUTHOR]

Slope stability is essential for mitigating landslides and erosion risks, especially during heavy rainfall. Vegetation significantly enhances slope stability through soil reinforcement and erosion control. Plant roots stabilize the soil matrix, reducing the likelihood of shallow landslides. However, vegetation's impact varies, with different types potentially influencing slope stability differently—some may even worsen instability under specific conditions. Evidence shows that both rigid and flexible vegetation types improve erosion resistance and slope stability, making them a cost-effective stabilization strategy. Plant water uptake increases matric suction and results in drier slopes, further reinforcing the stability. The mechanical effects of roots, which enhance soil cohesion, combined with the hydrological benefits of improved water management, are crucial for maintaining slope integrity. The present research emphasizes the importance of integrating vegetation into slope management strategies to mitigate landslide risks effectively. Additional measures, including geotechnical advancements, policy development, and community involvement, will complement these efforts. Thus, a comprehensive understanding of vegetation's diverse impacts and root structures, alongside advanced numerical analysis methods, is crucial for optimizing vegetation-based slope stabilization and enhancing safety in landslide-prone areas. In this paper, the authors thoroughly examine and review the state-of-the-art slope stability analysis techniques. Different methods of slope stabilization concerning vegetation have been covered such as RAR, Root Morphology and Density Distribution, root tensile strength and biomechanics, Numerical Analysis, and Limit Equilibrium approaches are the categories under which these techniques are divided.

There are various classification techniques available which produce desired results. However, some of the land use/land cover (LU/LC) classes are not discernible in such classifications. The present study attempts for improving LU/LC classification accuracy by applying data fusion techniques. For this, we considered combinations of: (1) Synthetic Aperture Radar (SAR) multi-looked intensity and optical, (2) backscatter with optical and (3) terrain corrected backscatter with optical data. The fusion of terrain corrected backscatter with optical has been considered in this study to negate the effect of topographic undulations on backscatter. The classification accuracy for combinations of cross-polarised terrain corrected backscatter data with Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2) (90.33%), co-polarised terrain corrected backscatter data with AVNIR-2 (89.66%), cross-polarised backscatter data with AVNIR-2 (89.0%) and cross-polarised multi-look intensity with AVNIR-2 (87.0%) were found to be better than classified outputs of AVNIR-2 data alone (84.6%), combinations of co-polarised backscatter and AVNIR-2 data (82.7%) and co-polarised multi-look intensity with AVNIR-2 data (80.1%), and combinations of multi-date terrain corrected backscatter (80.66%), multi-date co-polarised backscatter (80.0%) and multi-date co-polarised multi-look intensity (79.0%). The highest accuracy achieved in LU/LC classification is with cross-polarised terrain corrected backscatter with AVNIR-2 (90.33%) data. Data fusion techniques can be an alternative for LU/LC classification. [ABSTRACT FROM AUTHOR]