Constrained 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-ICID LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 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 in), 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. Index Terms-Remote sensing, digital

Regional Differences in the Influence of Irrigation on Climate

A global climate model experiment is performed to evaluate the effect of irrigation on temperatures in several major irrigated regions of the world. The Community Atmosphere Model, version 3.3, was modified to represent irrigation for the fraction of each grid cell equipped for irrigation according to datasets from the Food and Agriculture Organization. Results indicate substantial regional differences in the magnitude of irrigation-induced cooling, which are attributed to three primary factors: differences in extent of the irrigated area, differences in the simulated soil moisture for the control simulation (without irrigation), and the nature of cloud response to irrigation. The last factor appeared especially important for the dry season in India, although further analysis with other models and observations are needed to verify this feedback. Comparison with observed temperatures revealed substantially lower biases in several regions for the simulation with irrigation than for the control, suggesting that the lack of irrigation may be an important component of temperature bias in this model or that irrigation compensates for other biases. The results of this study should help to translate the results from past regional efforts, which have largely focused on the United States, to regions in the developing world that in many cases continue to experience significant expansion of irrigated land.

Regional differentiationnext term in previous termbull sperm plasma membranesnext term

previous termBull spermnext term heads and tails have been separated by proteolytic digestion (trypsin) and previous termplasma membranesnext term have been isolated, using discontinuous sucrose density gradient centrifugation. previous termPlasma membranenext term bound Ca2+-ATPase is shown to be associated mostly with the tail previous termmembranes.next term Pyrene excimer fluorescence and diphenylhexatriene fluorescence polarization experiments indicate a more fluid lipid phase in the tail region. Differences in surface charge distribution have been found, using 1-anilinonaphthalene-8-sulfonate and Tb3+ as fluorescent probes.

Identity for harmonic oscillator brackets

An identity satisfied by the harmonic oscillator (Talmi-Moshinsky) brackets is derived from two equivalent methods for evaluating an integral often encountered in cluster model studies.

Regional differentiation in bull sperm plasma-membranes

Bull sperm heads and tails have been separated by proteolytic digestion (trypsin) and plasma membranes have been isolated, using discontinuous sucrose density gradient centrifugation. Plasma membrane bound Ca2+-ATPase is shown to be associated mostly with the tail membranes. Pyrene excimer fluorescence and diphenylhexatriene fluorescence polarization experiments indicate a more fluid lipid phase in the tail region. Differences in surface charge distribution have been found, using 1-anilinonaphthalene-8-sulfonate and Tb3+ as fluorescent probes.

Regional variation in the composition and structure of mixed-species bird flocks in the Western Ghats and Sri Lanka

Mixed-species bird flocks are attractive models for the investigation of geographical variation in animal communities, as they represent a subset of the avifauna in most forested regions of the world. Yet studies of the regional variation in flock size and the composition of flocks are few, due to the predominance of studies carried out at single study site. Here, we review nine studies of mixed-species flocks conducted at 16 sites along the Western Ghats in India and in Sri Lanka. We find that flock size varies as much within this region as it does globally, with observation time being a confounding variable. Flock composition, however, is predictably related to elevation. Flocks at high elevations (>1200 m) in the Western Ghats strongly resemble flocks at high elevations in the mountain ranges of Sri Lanka in their composition, especially at the family level. We compare these flocks to flocks of other regions and make recommendations on study methodology that can facilitate comparisons across studies.

Generalization of Dynkin's Identity and Some Applications

Let X(t) be a right continuous temporally homogeneous Markov pro- cess, Tt the corresponding semigroup and A the weak infinitesimal genera- tor. Let g(t) be absolutely continuous and r a stopping time satisfying E.( S f I g(t) I dt) < oo and E.( f " I g'(t) I dt) < oo Then for f e 9iJ(A) with f(X(t)) right continuous the identity Exg(r)f(X(z)) - g(O)f(x) = E( 5 " g'(s)f(X(s)) ds) + E.( 5 " g(s)Af(X(s)) ds) is a simple generalization of Dynkin's identity (g(t) 1). With further restrictions on f and r the following identity is obtained as a corollary: Ex(f(X(z))) = f(x) + k! Ex~rkAkf(X(z))) + n-1E + (n ) )!.E,(so un-1Anf(X(u)) du). These identities are applied to processes with stationary independent increments to obtain a number of new and known results relating the moments of stopping times to the moments of the stopped processes.

Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in downscaling

Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However,studies have shown that climate change may manifest in terms of changes in frequencies of occurrence of the leading modes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster-Shafer (D-S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (''cluster linking'') and scaled by the GCM performance with respect to the associated cluster for the present period (''frequency scaling''). The D-S theory was chosen for its ability to express beliefs in some hypotheses, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The methodology is tested for predicting monsoon streamflow of the Mahanadi River at Hirakud Reservoir in Orissa, India. The results show an increasing probability of extreme, severe, and moderate droughts due to limate change. Significantly improved agreement between GCM predictions owing to cluster linking and frequency scaling is seen, suggesting that by linking regional impacts to natural regime frequencies, uncertainty in regional predictions can be realistically quantified. Additionally, by using a measure of GCM performance in simulating natural regimes, this uncertainty can be effectively constrained.

A matrix identity and perturbation expressions

An identity expressing formally the diagonal and off-diagonal elements of an inverse of a matrix is deduced employing operator techniques. Several well-known perturbation expressions for the self-energy are deduced as special cases. A new approximation and other applications following from the above formalism are briefly indicated through illustrations from a perturbed harmonic oscillator, chemisorption approximations and Kelly's result in the problem of electron correlation.

Both Surface Proteins (VP4 and VP7) of an Asymptomatic Neonatal Rotavirus Strain (1321) Have High Levels of Sequence Identity with the Homologous Proteins of a Serotype 10 Bovine Rotavirus

The nucleotide sequence of genes 4 and 9, encoding the outer capsid proteins VP4 and VP7 of a serotype 10 tissue culture-adapted strain, 1321, representative of asymptomatic neonatal rotaviruses isolated from neonates in Bangalore, India, were determined. Comparison of nucleotide and deduced amino acid sequences of 1321 VP4 and VP7 with previously published sequences of various serotypes revealed that both genes were highly homologous to the respective genes of serotype 10 bovine rotavirus, B223. The VP4 of 1321 represents a new human P serotype and the 1321 and related strains represent the first description of neonatal rotaviruses that appear to derive both surface proteins from an animal rotavirus.

Identity, energetics, dynamics and environment of interfacial water molecules in a micellar solution

The structure and energetics of interfacial water molecules in the aqueous micelle of cesium perfluorooctanoate have been investigated, using large-scale atomistic molecular dynamics simulations, with the primary objective of classifying them. The simulations show that the water molecules at the interface fall into two broad classes: bound and free, present in a ratio of 9:1. The bound water molecules can be further categorized on the basis of the number of hydrogen bonds (one or two) that they form with the surfactant headgroups. The hydrogen bonds of the doubly hydrogen-bonded species are found to be, on the average, slightly weaker than those in the singly bonded species. The environment around interfacial water molecules is more ordered than that in the bulk. The surface water molecules have substantially lower potential energy, because of interaction with the micelle. In particular, both forms of bound water have energies that are lower by �2.5-4.0 kcal/ mol. Entropy is found to play an important role in determining the relative concentration of the species.

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.