Plant species diversity along an altitudinal gradient of Bhabha Valley in western Himalaya

The present study highlights the rich species diversity of higher plants in the Bhabha Valley of western Himalaya in India. The analysis of species diversity revealed that a total of 313 species of higher plants inhabit the valley with a characteristic of moist alpine shrub vegetation. The herbaceous life forms dominate and increase with increasing altitude. The major representations are from the families Asteraceae, Rosaceae, Lamiaceae and Poaceae, suggesting thereby the alpine meadow nature of the study area. The effect of altitude on species diversity displays a hump-shaped curve which may be attributed to increase in habitat diversity at the median ranges and relatively less habitat diversity at higher altitudes. The anthropogenic pressure at lower altitudes results in low plant diversity towards the bottom of the valley with most of the species being exotic in nature. Though the plant diversity is less at higher altitudinal ranges, the uniqueness is relatively high with high species replacement rates. More than 90 % of variability in the species diversity could be explained using appropriate quantitative and statistical analysis along the altitudinal gradient. The valley harbours 18 threatened and 41 endemic species, most of which occur at higher altitudinal gradients due to habitat specificity.     

Advancing fracture fragility assessment of pre-Northridge welded column splices

A refined probabilistic assessment of seismic demands and fracture capacity of welded column splice (WCS) connections in welded steel moment resisting frames (WSMRFs) is presented. Seismic demand assessment is performed through cloud-based nonlinear time history analysis (NLTHA) for two case-study structures, i.e., a 4- and a 20- story WSMRFs. Results from NLTHA are used to derive fracture fragility of WCS connections. To this aim, the study investigates (1) optimal ground-motion intensity measures for conditioning probabilistic seismic demand models in terms of global (i.e., maximum inter-story drift ratio) and local (i.e., peak tensile stress in the flange of WCSs) engineering demand parameters of WSMRFs; (2) the effect of ground-motion vertical components on the longitudinal flange stress of WCS connections and their resulting fracture fragility; and (3) the effect of WCS capacity uncertainties on the fracture fragility estimates of those connections. For the latter case, an advanced finite element fracture mechanics-based approach proposed by the authors is employed to capture aleatory and epistemic uncertainties affecting fracture capacities. The focus is on pre-Northridge WCS connections featuring partial joint penetration and brittle materials, making them highly vulnerable to seismic fracture. Fracture fragility results for the case-study structures are compared and discussed, highlighting the importance of the considered issues on fragility estimates, particularly in the case of high-rise structures. Findings from the study contribute shedding some light on the influence of seismic demand and capacity uncertainties on the assessment of fracture fragility of WCS connections. These findings can guide similar performance-based assessment exercises for WSMRFs to inform, for instance, the planning and design of retrofitting strategies for those vulnerable connections.     

Analysis of stability of earthen dams in kachchh region, Gujarat, India

The Kachchh region of Gujarat, India bore the brunt of a disastrous earthquake of magnitude M_w = 7.6 that occurred on January 26, 2001. The major cause of failure of various structures including earthen dams was noted to be the presence of liquefiable alluvium in the foundation soil. Results of back-analysis of failures of Chang, Tappar, Kaswati and Rudramata earth dams using pseudo-static limit equilibrium approach presented in this paper confirm that the presence of liquefiable layer contributed to lesser factors of safety leading to a base type of failure that was also observed in the field. Following the earthquake, earth dams have been rehabilitated by the concerned authority and it is imperative that the reconstructed sections of earth dams be reanalyzed. It is also increasingly realized that risk assessment of dams in view of the large-scale investment made and probabilistic analysis is necessary. In this study, it is demonstrated that the probabilistic approach when used in conjunction with deterministic approach helps in providing a rational solution for quantification of safety of the dam and in the estimation of risk associated with the dam construction.     

Geospatial Ontology Development and Semantic Analytics

Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we define. SWETO (Semantic Web Technology Evaluation Ontology) and geospatial extension SWETO‐GS are examples of these ontologies. The Geospatial Semantics Analytics (GSA) framework incorporates: (1) the ability to automatically and semi‐automatically tract metadata from syntactically (including unstructured, semi‐structured and structured data) and semantically heterogeneous and multimodal data from diverse sources; and (2) analytical processing that exploits these ontologies and associated knowledge bases, with integral support for what we term spatiotemporal thematic proximity (STTP) reasoning and interactive visualization capabilities. This paper discusses the results of our geospatial ontology development efforts as well as some new semantic analytics methods on this ontology such as STTP.     

The source of the great Assam earthquake — an interplate wedge motion

The source of the Assam earthquake of Aug. 15, 1950 is revealed from amplitude observations of surface and body waves at Pasadena, Tokyo and Bergen. Seiches' amplitudes in Norway, initial P motions throughout the world, aftershocks and landslides distribution, PP/P ratio at Tokyo, R/L ratio and directivity at Pasadena, are also used. The ensuing fault geometry and kinematics is consistent with the phenomenology of the event and the known geology of the source area. It is found that a progressive strike-slip rupture with velocity 3 km/sec took place on a fault of length 250 km and width 80 km striking 330–337° east of north and dipping 55–60° to ENE. The use of exact surface-wave theory and asymptotic body-wave theory which takes into account finiteness and absorption, rendered an average shear dislocation of 35 m. A three-dimensional theory for the excitation of seiches in lakes by the horizontal acceleration of surface waves was developed. It is confirmed that Love waves near Bergen generated seiches with peak amplitude up to 70 cm depending strongly on the width of the channel.It is believed that the earthquake was caused by a motion of the Asian plate relative to the eastern flank of the Indian plate where the NE Assam block is imparted a tendency of rotation with fracture lines being developed along its periphery.Comparison with other well-studied earthquakes shows that although the magnitude of the Assam event superseded that of all earthquakes since 1950, its potency U₀dS (700,000 m × km²) was inferior to that of Alaska 1964 (1,560,000 m × km²) and Chile 1960 (1,020,000 m × km²).     

Sand dunes as a major proximal dust source for late Pleistocene loess in the Negev Desert, Israel

Grain size analyses of three hilltop, primary eolian loess sequences in the Negev desert, southern Israel, show a bimodal grain-size distribution at 50-60 μm and 3-8 μm. Using analyses of mineralogy and OSL ages we demonstrate that the coarse mode is composed mostly of quartz grains and its relative magnitude increases regionally with time, suggesting an enhancement of a time-transgressive proximal dust source compared to a distal, Saharan fine-grain dust. The only proximal dust source for large amount of coarse silt quartz grains is the sands that advanced into Sinai and the Negev concurrently with the loess accretion during the late Pleistocene as a result of the exposure of the Mediterranean shelf. We therefore propose that the coarse silt quartz grains were formed through eolian abrasion within the margins of an advancing sand sea. This relationship between desert sand seas as a source for proximal coarse dust and desert margin loess deposits can be applicable to other worldwide deserts such as Northern Africa, China and Australia.     

Probabilistic demand and fragility assessment of welded column splices in steel moment frames

An assessment of seismic demands and capacities of welded column splice (WCS) connections in steel moment frames is presented. For demand assessment, nonlinear dynamic analyses are conducted for two case‐study buildings, that is, a 4‐story and a 20‐story moment frame. Results from the nonlinear dynamic analyses are assessed through a probabilistic seismic demand analysis (PSDA) framework to characterize recurrence rates of longitudinal flange stress in these connections. The PSDA is applied in two contexts. First, in the context of WCS connections constructed prior to the M 6.7 1994 Northridge earthquake, the PSDA is combined with sophisticated finite element‐based fracture mechanics analysis to compute the mean annual frequencies of fracture in these connections. The pre‐Northridge WCS are especially critical because they feature partial joint penetration and brittle materials that compromise their resistance to fracture. The analysis indicates that the mean annual frequencies of fracture in these connections may be unacceptably high for both the 4‐story and the 20‐story frames. This warrants a serious and urgent consideration of retrofit strategies. These findings are attributed to the brittleness of the pre‐Northridge splices (as indicated by the fracture mechanics simulations), as well as the force‐controlled nature of these components, wherein low‐intensity ground motions contribute disproportionately to fracture risk, as evidenced by fracture risk disaggregation. Second, in the context of new construction, the PSDA provides meaningful stress magnitudes for design. Currently, WCS connections employ complete joint penetration welds with the intent to develop the smaller column flange in yielding. The PSDA conducted in this study suggests that this requirement may be too stringent because stress demands in the splices corresponding even to high return periods (e.g., 2475 years) are significantly lower (~40 ksi), as compared with the stress required to yield the column (~55 ksi). Limitations of the study are outlined. Copyright © 2015 John Wiley & Sons, Ltd.     

Sugarcane crop identification from LISS IV data using ISODATA,MLC, and indices based decision tree approach

Image classification is one of the crucial techniques in detecting the crops from remotely sensed data. Crop identification and discrimination provide an important basis for many agricultural applications with various purposes, such as cropping pattern analysis, acreage estimation, and yield estimation. Accurate and faster estimation of crop area is very essential for projecting yearly agriculture production for deciding agriculture policies. Remote sensing is a technique that allows mapping of large areas in a fast and economical way. In many applications of remote sensing, a user is often interested in identifying the specific crop only while other classes may be of no interest. Indian Remote Sensing Satellite (IRS-P6) LISS IV sensor image of spatial resolution 5.8 m has been used to identify the sugarcane crop for the Chhapar village of Muzaffarnagar District, India. Classification of satellite data is one of the primary steps for information extraction for crop land identification. In recent years, decision tree approach to image analysis has been developed for the assessment and improvement of traditional statistically based image classification. In this study, ISODATA, MLC, and vegetation indices based decision tree approaches are used for classifying LISS IV imagery. The 11 vegetation index images have been generated for decision tree classification. All the three methods are compared and it is found that the best performance is given by the decision tree method. Vegetation indices based decision tree method for sugarcane classification, the user’s accuracy, producer’s accuracy, overall accuracy, and kappa coefficient were found 88.17, 86.59, and 87.93% and 0.86 respectively.     

Development of machine vision-based ore classification model using support vector machine (SVM) algorithm

The product of the mining industry (ore) is considered to be the raw material for the metal industry. The destination policy of the raw materials of iron mine is highly dependent on the class of iron ores. Thus, regular monitoring of iron ore class is the urgent need at the mine for accurately assigning the destination policy of raw materials. In most of the iron ore mines, decisions on ore class are made based on either visual inspection by the geologist or laboratory analyses of the ores. This process of ore class estimation is time consuming and also challenging for continuous monitoring. Thus, the present study attempts to develop an online vision-based technology for classification of iron ores. A laboratory-scale transportation system is designed using conveyor belt for online image acquisition. A multiclass support vector machine (SVM) model was developed to classify the iron ores. A total of 2200 images were captured for developing the ore classification model. A set of 18 features (9-histogram-based colour features in red, green and blue (RGB) colour space and 9-texture features based on intensity (I) component of hue, saturation and intensity (HSI) colour space) were extracted from each image. The performance of the SVM model was evaluated using four confusion matrix parameters (sensitivity, accuracy, misclassification and specificity). The SVM model performance was also compared with the other methods like K-nearest neighbour, classification discriminant, Naïve Bayes, classification tree and probabilistic neural network. It was observed that the SVM classification model performs better than the other classification methods.     

Influence of wave climate on architecture and landscape characteristics of Posidonia oceanica meadows

Seagrass meadow characteristics, including distribution, shape, size and within‐meadow architectural features, may be influenced by various physical factors, including hydrodynamic forces. However, such influences have hardly been assessed for meadows of the ecologically important and endemic Mediterranean seagrass Posidonia oceanica. The distribution of P. oceanica meadows at five sites in the Maltese Islands was mapped to a depth of c. 15 m using a combination of aerial photography and SCUBA diving surveys. Estimates of wind‐generated wave energy and energy attenuated by depth were computed using the hydrodynamic model WEMo (Wave Exposure Model). Metrics for P. oceanica landscape features were calculated using FRAGSTATS for replicate 2500 m² subsamples taken from the seagrass habitat maps in order to explore the influence of wave dynamics at the landscape scale. Data on within‐meadow architectural attributes were collected from five sites and analysed for relationships with wave energy. The results indicate that landscape and architectural features of P. oceanica meadows located within the 6–11 m depth range are significantly influenced by wave climate. Posidonia oceanica meadows tend to be patchier and have low overall cover, more complex patch shapes and reduced within‐patch architectural complexity along a wave exposure gradient from low to high energy. The findings from the present study provide new insight into the influence of hydrodynamic factors on the natural dynamism of P. oceanica meadow landscape and architecture, which has implications for the conservation and management of the habitat.