Reduced order observer based identification of base isolated buildings

The objective of this study is to identify system parameters from the recorded response of base isolated buildings, such as USC hospital building, during the 1994 Northridge earthquake. Full state measurements are not available for identification. Additionally, the response is nonlinear due to the yielding of the lead-rubber bearings. Two new approaches are presented in this paper to solve the aforementioned problems. First, a reduced order observer is used to estimate the unmeasured states. Second, a least squares technique with time segments is developed to identify the piece-wise linear system properties. The observer is used to estimate the initial conditions needed for the time segmented identification. A series of equivalent linear system parameters are identified in different time segments. It is shown that the change in system parameters, such as frequencies and damping ratios, due to nonlinear behavior of the lead-rubber bearings, are reliably estimated using the presented technique. It is shown that the response was reduced due to yielding of the lead-rubber bearings and period lengthening.     

Co-seismic gravity changes in the Koyna-Warna region: Implications of mass redistribution

Koyna-Warna Region (KWR) is one of the known sites for reservoir triggered seismicity. The continued triggered seismicity over the five decades is restricted to a region of about 600–700 sq. km, which provides a unique opportunity to monitor geophysical anomalies likely to be associated with seismicity of the region. Present study confers temporal gravity changes recorded by gPhone and GRACE satellite and interprets observed changes in conjunction with seismological, geodetic (cGPS) observations and groundwater level measurements. GRACE data suggest that seasonal vertical deformation due to hydrological loading is ～ 2 cm, which corroborates with continuous GPS observations. Seasonal hydrological loading of the region, which is in a phase of reservoir loading, might be influencing the critically stressed KWR leading to the seasonal seismicity of the region. The gPhone gravity data distinctly show co-seismic gravity signals for eight earthquakes of M_w > 2 and gravity anomalies show positive correlation on a logarithmic scale with earthquake released energy. To investigate the cause of gravity changes, an estimate is made for 14^th April 2012 earthquake for M_w 4.8 using fault dislocation model. The recorded gravity changes of 189 μGal by gPhone located at a distance of 28 km from the hypocentre is much more than the estimate of ～0.1 μGal calculated for M_w 4.8 Koyna earthquake. Therefore, it is inferred that co-seismic gravity signals for eight earthquakes are primarily caused due to redistribution of mass at shallow depth.     

The spatial and temporal characteristics of the seasonal precipitation over India

Three extreme cases of seasonal precipitation over 31 contiguous meteorological subdivisions of India were decomposed into orthogonal components using eigenvector technique to examine their spatial and temporal behaviour. The first two eigenvectors combined were found to represent the seasonal precipitation over India to a sufficient high degree of accuracy retaining 90–95 percent of the total variance. These two components show high spatial similarity in all the three cases of the precipitation examined.The first component is characterized by a coherent variation over the area with large coherent variation over the north-east India, Central India and the west coast of India. The coefficients of the component show annual behaviour with the peak values generally reached during July. This component is representative of the summer monsoon (June–September) mode.The second component characterizes out of phase variation in precipitation between Central India, adjoining parts of the area, and peninsular India. The coefficients of the component show the semi-annual oscillation. It appears that the role of the second eigenvector might be to represent regionality of the seasonal march of the monsoon rain.     

Automated Approach for Extraction of Oil Spill from SAR Imagery

Oil spill pollution is a major environmental concern since it has most dangerous and hazardous effects on marine environment. Periodic monitoring by detecting oil spills along with its movement, helps in efficient clean-up and recovery operations. Over the past few years, Synthetic Aperture Radar (SAR) based remote sensing has received considerable attention for monitoring and detecting oil spill due to its unique capabilities to provide wide-area observation in all weather conditions. However, the interpretation of marine SAR imagery is often ambiguous, since it is difficult to separate oil spill from look-alike features. The objective behind our study was to extract probable oil spill candidates automatically from SAR imageries containing oil spill incidences, where new methods based on over-segmentation and amalgamate approach is used for this purpose. The methodology is all about over segmenting the entire image based on its statistics and amalgamating relevant segments at later point of time to represent actual dark features as probable oil spill candidates. Under the dependency on SAR imageries alone, the approach does not take care of the separation of look-alike features which can be addressed subsequently by the consideration of associated synchronous external data resources such as optical data, wind and ocean parameters (Zhao et al. in Opt Express 22(11):13755–13772, 2014; Espedal and Wahl in Int J Remote Sens 20(1):49–65, 1999). The approach is carried out on a set of RISAT-1 imagery containing oil spill incidences and the extracted oil spill areas are in well agreement with the visually interpreted output with kappa coefficient greater than 0.70 and overall classification accuracy greater than 80%.     

A study of the empirical functions of the height fields over India and their relation with the rainfall

The empirical orthogonal functions have been obtained for the individual summer monsoon (June through September) months using the grid point values of monthly 700 mb geopotential heights over Indian region. The data for 21 summer monsoon months for the years 1958 to 1978 have been used in the present computation. The major variance reduction is due to the first three dominant functions accounting over 80% of the total variance in each month. The variance reduction only due to the first function ranges from 45 to 65%. The first function has in-pbase oscillation throughout the area indicating that the area under study is homogeneous and the centre of the oscillation lies over northwest India. The amplitudes of the first function also show generally quasipers stence in their sign within a season. The second function has two centres of action over the region of monsoon trough which are in phase. The third function has also two centres oriented in the east-west direction but they are in the opposite phase. Fairly large values of correlation coefficients between the patterns of the different monsoon months suggest that the patterns for these months corresponding to the first and the second functions respectively are quite similar. The patterns for these months also evolve with time in a related way. The spectrum analysis to the time series of amplitudes indicates the presence of the quasi-periodicity of 3 years during these monsoon months. The amplitudes corresponding to the dominant functions are found to be significantly related with the rainfall of central and western parts of India     

Equations of motion of the restricted problem of (2 + 2) bodies when primaries are magnetic dipoles and minor bodies are taken as electric dipoles

In this problem of the restricted (2 + 2) bodies we have considered two magnetic dipoles of masses M ₁ and M ₂(M ₁ > M ₂) moving in circular Keplarian orbit about their centre of mass. Two minor bodies of masses m ₁, m ₂(m _j< M ₂) are taken as electric dipoles in the field of rotating magnetic dipoles. These minor bodies interact with each other but do not perturb the primaries.We have found equations of motions which differ from that of Goudas and Petsagouraki's (1985).     

Analysis of aerosol and carbon monoxide characteristics over Arabian Sea during crop residue burning period in the Indo-Gangetic Plains using multi-satellite remote sensing datasets

In this study, we have used multi-satellite data to retrieve aerosol loadings and carbon monoxide (CO) pollution over the Arabian Sea, caused due to anthropogenic activities over the Indo-Gangetic Plains (IGP) in India. Relatively high aerosol and CO loadings during 9–14 November 2007 over Arabian Sea were attributed to crop residues burning in the IGP and fireworks during Diwali festival. Aerosol index (AI) obtained from ozone monitoring instrument (OMI) and CO from measurements of pollution in the troposphere instrument (MOPITT). CO showed higher values over the Arabian Sea suggesting long-range transport of anthropogenic aerosols and trace gases from the continental to Arabian Sea region.     

Some Haematological Effects of Crude Oil on Freshwater Catfish,Heteropneustes fossilis (BLOCH)

The exposure of catfish, Heteropneustes fossilis to different concentrations (200, 500, 700, 1000, 1500, 2000 ppm) of crude oil extract for a varying period (for up to 48 h in lethal extract and 360 h in sublethal one) resulted into a number of haematological changes. All the parameters taken here were found to have been increased except the haemoglobin level which fell down to 14.3 % in an acute lethal concentration (2000 ppm) after 48 h of exposure. The haematocrit value increased significantly (12 %) in 2000 ppm. The blood sugar level showed hyperglycemia in all the concentrations. The increase in ascorbic acid (28 %) was pronounced in higher concentrations. Changes occurring in different parameters seemed to be reversible as all the parameters returned to their normal levels after returning the fish to normal media, except the nuclear swelling which did not resume the normal functioning even after a prolonged treatment (1 month or more) in the recovery jar. The haematological effects shown by the crude oil resembled partly those kept in severe hypoxic conditions and partly to the fishes poisoned by heavy metals (Cu and Zn). On the basis of results obtained in this investigation, crude oil may be categorised as a complex toxic agent.     

Empirical assessment of adaptation to climate change impacts of mountain households: development and application of an Adaptation Capability Index

The present study proposes an index to assess the potential for adaptation to climate change for households in the mountainous regions. The index provides a realistic approach to recognize social and natural factors which contribute to successful adaptation and addresses several household functions, such as social networking, livelihood strategy, adjustment strategies, resource availability and accessibility. The proposed Adaptation Capability Index (ACI) is analytically defined, mathematically formulated and field tested on mountainous households in urban and semi-urban regions of the Uttarakhand Himalaya in India. To gather data on the topic relevant to the ACI, a household scale questionnaire was developed and administered to 120 heads of households through face-to-face interviews. The results highlight higher adaptive capability of urban households and low adaptation capacity of rural households due to poor farm productivity, low accessibility and availability of resources and technological input. Future programs and policies must include and implement regulations to remedy attributive factors responsible for higher adaptation. This paper may be applicable to other mountainous regions and may provide insights for effective adaptation strategies to climate change.     

Prediction of spatial soil organic carbon distribution using Sentinel-2A and field inventory data in Sariska Tiger Reserve

Dynamic and vigorous top soil is the source for healthy flora, fauna, and humans, and soil organic matters are the underpinning for healthy and productive soils. Organic components in the soil play significant role in stimulating soil productivity processes and vegetation development. This article deals with the scientific demand for estimating soil organic carbon (SOC) in forest using geospatial techniques. We assessed distribution of SOC using field and satellite data in Sariska Tiger Reserve located in the Aravalli Hill Range, India. This study utilized the visible and near-infrared reflectance data of Sentinel-2A satellite. Three predictor variables namely Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, and Renormalized Difference Vegetation Index were derived to examine the relationship between soil and SOC and to identify the biophysical characteristic of soil. Relationship between SOC (ground and predicted) and leaf area index (LAI) measured through satellite data was examined through regression analysis. Coefficient of correlation (R ²) was found to be 0.95 (p value < 0.05) for predicted SOC and satellite measured LAI. Thus, LAI can effectively be used for extracting SOC using remote sensing data. Soil organic carbon stock map generated through Kriging model for Landsat 8 OLI data demonstrated variation in spatial SOC stocks distribution. The model with 89% accuracy has proved to be an effective tool for predicting spatial distribution of SOC stocks in the study area. Thus, optical remote sensing data have immense potential for predicting SOC at larger scale.