[1] Acquiring spatially continuous ground-surface displacement fields from Terrestrial Laser Scanners (TLS) will allow better understanding of the physical processes governing landslide motion at detailed spatial and temporal scales. Problems arise, however, when estimating continuous displacement fields from TLS point-clouds because reflecting points from sequential scans of moving ground are not defined uniquely, thus repeat TLS surveys typically do not track individual reflectors. Here, we implemented the cross-correlation-based Particle Image Velocimetry (PIV) method to derive a surface deformation field using TLS point-cloud data. We estimated associated errors using the shape of the cross-correlation function and tested the method's performance with synthetic displacements applied to a TLS point cloud. We applied the method to the toe of the episodically active Cleveland Corral Landslide in northern California using TLS data acquired in June 2005-January 2007 and January-May 2010. Estimated displacements ranged from decimeters to several meters and they agreed well with independent measurements at better than 9% root mean squared (RMS) error. For each of the time periods, the method provided a smooth, nearly continuous displacement field that coincides with independently mapped boundaries of the slide and permits further kinematic and mechanical inference. For the 2010 data set, for instance, the PIV-derived displacement field identified a diffuse zone of displacement that preceded by over a month the development of a new lateral shear zone. Additionally, the upslope and downslope displacement gradients delineated by the dense PIV field elucidated the non-rigid behavior of the slide.
The stability of many large landslides is determined in part by deformation along buried, often inaccessible, slip surfaces. Factors such as infiltrating rainfall on the slip surface lead to stability changes. Yet characterizing the depth and shape of this slip surface is challenging. Here we examine the hypothesis that the subsurface slip geometry can be constrained by ground surface displacements in concert with two, mechanically distinct, forward models. We estimate a 3-D ground displacement field for the slow-moving Cleveland Corral landslide in California using repeat terrestrial laser scanner data. We test the efficacy of two models to estimate slip depth and slip magnitude of the slide-a 2-D balanced cross-section method and an elastic dislocation model. The estimated slip surface depth using both methods matches in situ observations from shear rods installed in the slide within the ±0.45 m misfit indicating that these are valuable approaches for investigating landslide geometry and slip behavior.
The Kathmandu Valley lies in a synclinal basin filled up by fluvio-lacustrine sediments of Pleistocene age. Sundhara and Jamal lie at the core of Kathmandu City. The area is mostly occupied by public buildings. This paper primarily deals with distribution and engineering and geotechnical properties such as allowable bearing capacity of soil at Sundhara and Jamal area. For the purpose of identification of geotechnical properties of subsurface strata for multistoreyed buildings, data of borehole logging from fifteen drill holes and laboratory test of disturbed and undisturbed soil samples was used for the investigation. In the laboratory, index and mechanical properties such as grain size, natural moisture content, specific gravity, Atterberg limits, penetration resistance, cohesion, uniaxial compressive strength, angle of shearing, rate of consolidation, and settlement were evaluated. According to the National Building Code of India, the Kathmandu Valley is located in Seismic Zone V, and the recommended coefficient of horizontal acceleration for this zone is 0.08 g. Based on the present study of geotechnical properties of subsurface strata, it is recommended to increase the coefficient by up to 50 per cent for important structures. For multi-storeyed building, the tentative allowable bearing capacity for different types of foundation (strip, isolated. and raft) at different depths are determined as per the average parameters valid for the whole area.
The study examined the income distribution and effects of income on food expenditure, non-food expenditure and savings of households. The survey data was used, and Gini-coefficient was derived from observing the income distribution across households of different income classes. Engel coefficient was used to estimate the income elasticity of the expenditure on food items. This study found significant disparities in the income of rich and poor households with a high Gini Index. Also, it found significant variations in food consumption patterns across different income classes. The proportion of food basket share of a household declined with an increase in income. Similarly, the proportion of the budget share of food items shifted to other non-food items with increased income. According to the findings, lower income households had a higher elasticity of food expenditure than higher income households, complying with Engel’s law. The results of this study are noteworthy because they would provide crucial policy recommendations and a foundation for future research.
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