Korean coastal water depth/sediment and land cover mapping (1:25,000) by computer analysis of LANDSAT imagery

Computer analysis was applied to single date LANDSAT MSS imagery of a sample coastal area near Seoul, Korea equivalent to a 1:50,000 topographic map. Supervised image processing yielded a test classification map from this sample image containing 12 classes: 5 water depth/sediment classes, 2 shoreline/tidal classes, and 5 coastal land cover classes at a scale of 1:25,000 and with a training set accuracy of 76%. Unsupervised image classification was applied to a subportion of the site analyzed and produced classification maps comparable in results in a spatial sense. The results of this test indicated that it is feasible to produce such quantitative maps for detailed study of dynamic coastal processes given a LANDSAT image data base at sufficiently frequent time intervals

The S=1/2 chain in a staggered field: High-energy bound-spinon state and the effects of a discrete lattice

We report an experimental and theoretical study of the antiferromagnetic S=1/2 chain subject to uniform and staggered fields. Using inelastic neutron scattering, we observe a novel bound-spinon state at high energies in the linear chain compound CuCl2 * 2((CD3)2SO). The excitation is explained with a mean-field theory of interacting S=1/2 fermions and arises from the opening of a gap at the Fermi surface due to confining spinon interactions. The mean-field model also describes the wave-vector dependence of the bound-spinon states, particularly in regions where effects of the discrete lattice are important. We calculate the dynamic structure factor using exact diagonalization of finite length chains, obtaining excellent agreement with the experiments.Comment: 16 pages, 7 figures, accepted by Phys. Rev.

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed

Periods of modular forms on Γ0(N)\Gamma_0(N) and products of Jacobi theta functions

Generalizing a result of [15] for modular forms of level one, we give a closed formula for the sum of all Hecke eigenforms on $\Gamma_0(N)$, multiplied by their odd period polynomials in two variables, as a single product of Jacobi theta series for any squarefree level $N$. We also show that for $N=2$,3 and 5 this formula completely determines the Fourier expansions of all Hecke eigenforms of all weights on $\Gamma_0(N)$