Journal of Geotechnical Studies

Change Detection in Israel Using NDVI of 2015 and 2025: A Geospatial Study

Loknadh Rambilli, Dr. Usha Chirala — Wed, 28 Oct 2026 00:00:00 +0000

Increasing climatic variability and human development pressures are reshaping Vegetation across landscapes. In Israel, where Vegetation varies from Mediterranean landscapes in the North to arid regions in the south, ongoing spatial assessments are essential to identify significant shifts in vegetation greenness across these diverse environments. This study examines changes in Vegetation over a decade in Israel, from late 2015 to late 2025, utilizing Sentinel-2 satellite imagery. By generating Normalized Difference Vegetation Index (NDVI) composites within fixed autumn periods, the study applies a seven-class spectral framework to represent Israel's wide array of vegetation conditions more accurately. The results show extensive shifts in land greenness over the 10 years, with about 40% of classified regions moving into lower vegetation-density categories, while the total classified area remained stable. These insights highlight the effectiveness of NDVI-based change detection in recognizing large-scale changes in vegetation conditions. The spatial patterns identified in this study lay the groundwork for addressing vegetation stress and change, aiding in further evaluations of drought impacts and informing strategies for land use and environmental resource management.

Comparative Consistency Assessment of TensorFlow, PLAXIS, and YADE for Foundation Suitability in Heterogeneous Ground

Sudarshan Auji, Rajesh G. C., Deepak Thapa — Wed, 09 Sep 2026 00:00:00 +0000

Foundation decisions in geologically variable ground are often made from a limited number of boreholes, which means that the interpretation between investigated locations can be uncertain. This study re-examines the existing Khare Khola geotechnical dataset from Okhaldhunga, Nepal, through a comparative consistency framework. Four investigated boreholes (BH-1 to BH-4) are used as the observed site basis, while two intermediate locations (BH-5 and BH-6) are evaluated from TensorFlow predictions. PLAXIS finite element results and YADE discrete element results are then interpreted independently and compared in terms of bearing capacity, settlement behavior, stress-deformation conditions, and resulting foundation recommendations. The observed ground changes from dense granular soil at BH-1 toward soft to medium-stiff clay at BH-4, with interpreted bearing capacity decreasing from about 250 to 100 kN/m². TensorFlow estimates approximately 225 kN/m² at BH-5 and 160 kN/m² at BH-6. PLAXIS reports corresponding ultimate capacities of about 225 and 160 kN/m², with settlement ranges of 10–20 mm and 30–50 mm, respectively. YADE gives approximately 225–240 kN/m² for BH-5 and 140–160 kN/m² for BH-6. Despite differences in modeling assumptions, all three approaches identify BH-5 as comparatively favorable for a shallow foundation and BH-6 as a more settlement-sensitive location requiring load-dependent foundation selection. The study therefore argues that the practical value of using several computational approaches lies in the consistency of the engineering decision rather than in exact numerical agreement. Where the methods converge, confidence in preliminary foundation selection increases; where the decision remains borderline, conservative design or additional investigation is warranted.

Evaluation of Drilled and Grouted Soil-Nailed Slope Stability through Automated Modelling and Parametric Analysis

Mon, 07 Sep 2026 00:00:00 +0000

Soil nailing is a commonly practiced geotechnical technique for stabilizing slopes and excavations, achieved by installing closely spaced grouted steel bars. This study examined soil-nailed slope stability using numerical and analytical approaches, considering nail length, spacing, inclination, and soil properties. Finite Element Method (FEM) simulations in PLAXIS 2D, based on the Mohr-Coulomb model, were conducted to analyze soil-nail interactions under static loads. A comprehensive literature review and parametric studies of over 137,200 configurations, automated using Python, produced design charts for soil types such as clayey sand and silty sand. The results emphasized soil cohesion (56.71%) and excavation depth (20.10%) as the most critical parameters, with nail length (7.32%) also being significant. Granular soils, such as silty and clayey sand, achieved higher success rates (75.76%) than fine-grained silty clay (5%), underscoring the importance of soil type. The reliability of the numerical modelling approach was verified and validated by comparing the obtained results with established theoretical concepts and literature. Recommendations highlight the necessity of site-specific investigations, construction monitoring, and the integration of numerical modelling with empirical data to improve soil nail wall design. This provides a national framework for safe and efficient slope stabilization, particularly in rugged terrain such as that of Nepal.

Experimental Evaluation of Waste-LDPE Strips for Improving Pavement Subgrade Soil

Nikhil Kushwaha, Guru Sharan Mishra — Tue, 08 Sep 2026 00:00:00 +0000

This study evaluates randomly distributed Low-Density Polyethylene (LDPE) strips as reinforcement for three pavement-subgrade soils. Cleaned milk-pouch plastic was cut to a 5 mm width, and the planned experimental domain covered 1%–4% LDPE by dry soil mass and aspect Ratios (AR) of 2, 4, 6, and 8. The complete numerical record available for verification comprises the dosage series at AR 6 together with strength checks at the selected condition; complete numerical results for AR 2, 4, and 8 are not reported. Standard compaction, four-day soaked CBR, and UCS responses were evaluated, while the reported triaxial parameters were treated as supplementary because the underlying principal-stress records were unavailable for independent recalculation. Soaked CBR increased from 4.25%, 5.82%, and 3.40% in untreated Soils A, B, and C to 8.46%, 12.74%, and 6.28% at 3% LDPE with 5 mm × 30 mm strips (AR 6), corresponding to gains of 99.1%, 118.9%, and 84.7%. MDD losses at this condition were 1.23%, 0.81%, and 1.90%, and UCS increased by 121.8–184.6%. CBR declined at 4% LDPE in all three soils. Accordingly, 3% LDPE at AR 6 is identified as the best common verified condition within the complete AR 6 dataset, not as a globally proven geometry optimum. Replicate-level observations were unavailable; therefore, the reported percentage changes are descriptive and are not presented as statistically significant differences. Further replicated testing across AR 2, 4, and 8, together with durability and field validation, is required before general specification.