Contrained linear spectral unmixing technique for regional land cover mapping using MODIS data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up- to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat- TM/ETM+, IRS-1C/D LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (~ 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 m), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end- members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications.

Doubly spectral stochastic finite element method (DSSFEM) for random field problems

Uncertainties in complex dynamic systems play an important role in the prediction of a dynamic response in the mid- and high-frequency ranges. For distributed parameter systems, parametric uncertainties can be represented by random fields leading to stochastic partial differential equations. Over the past two decades, the spectral stochastic finite-element method has been developed to discretize the random fields and solve such problems. On the other hand, for deterministic distributed parameter linear dynamic systems, the spectral finite-element method has been developed to efficiently solve the problem in the frequency domain. In spite of the fact that both approaches use spectral decomposition (one for the random fields and the other for the dynamic displacement fields), very little overlap between them has been reported in literature. In this paper, these two spectral techniques are unified with the aim that the unified approach would outperform any of the spectral methods considered on their own. An exponential autocorrelation function for the random fields, a frequency-dependent stochastic element stiffness, and mass matrices are derived for the axial and bending vibration of rods. Closed-form exact expressions are derived by using the Karhunen-Loève expansion. Numerical examples are given to illustrate the unified spectral approach.

Beta-structure of polypeptides in non-aqueous solutions. II. Side-chain orientation

The specific side-chain orientations of the phenyl group in the polypeptides poly-S-benzyl-L-cysteine, poly-S-carbobenzoxy-L-cysteine and poly-O-carbobenzoxy-L-serine in the beta-structure have been studied by spectral measurements in solutions. All the three polypeptides exhibit aromatic CD bands, indicating the asymmetric placement of the side-chain phenyl rings when the polypeptide backbone takes up the antiparallel beta-structure. Supporting evidence for this is derived from n.m.r. spectra of the polypeptides, which show upfield shift of the phenyl protons due to the stacking of the aromatic rings. Molecular model building studies reveal the stacking of alternate phenyl groups along the polypeptide chain.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

An improved sapce phasor based current hysteresis controller with reduced switching frequency variations using variable parabolic bands

A current error space phasor based simple hysteresis controller is proposed in this paper to control the switching frequency variation in two-level pulsewidth-modulation (PWM) inverter-fed induction motor (IM) drives. A parabolic boundary for the current error space phasor is suggested for the first time to obtain the switching frequency spectrum for output voltage with hysteresis controller similar to the constant switching frequency voltage-controlled space vector PWM-based IM drive. A novel concept of online variation of this parabolic boundary, which depends on the operating speed of motor, is presented. A generalized technique that determines the set of unique parabolic boundaries for a two-level inverter feeding any given induction motor is described. The sector change logic is self-adaptive and is capable of taking the drive up to the six-step mode if needed. Steady-state and transient performance of proposed controller is experimentally verified on a 3.7-kW IM drive in the entire speed range. Close resemblance of the simulation and experimental results is shown.

Spectral Efficiency of Channel-Aware Schedulers in Non-identical Composite Links with Interference

Accurate system planning and performance evaluation requires knowledge of the joint impact of scheduling, interference, and fading. However, current analyses either require costly numerical simulations or make simplifying assumptions that limit the applicability of the results. In this paper, we derive analytical expressions for the spectral efficiency of cellular systems that use either the channel-unaware but fair round robin scheduler or the greedy, channel-aware but unfair maximum signal to interference ratio scheduler. As is the case in real deployments, non-identical co-channel interference at each user, both Rayleigh fading and lognormal shadowing, and limited modulation constellation sizes are accounted for in the analysis. We show that using a simple moment generating function-based lognormal approximation technique and an accurate Gaussian-Q function approximation leads to results that match simulations well. These results are more accurate than erstwhile results that instead used the moment-matching Fenton-Wilkinson approximation method and bounds on the Q function. The spectral efficiency of cellular systems is strongly influenced by the channel scheduler and the small constellation size that is typically used in third generation cellular systems.