Potential of High-Resolution Satellite Data in the Context of Vulnerability of Buildings

High-resolution space-borne remote sensing data are investigated for their potential to extract relevant parameters for a vulnerability analysis of buildings in European countries. For an evaluation of large earthquake scenarios, the number of parameters in models for vulnerability is reduced to a minimum of relevant information such as the type of building (age, material, number of storeys) and the geological and spatial context. Building-related parameters can be derived from remote sensing data either directly (e.g. height) or indirectly based on the recognition of the urban structure type in which the buildings are located. With the potential of a fully- or semi-automatic inventory of the buildings and their parameters, high-resolution satellite data and techniques for their processing are a useful supporting tool for the assessment of vulnerability.     

Streams in the Harz National Parks (Germany) — a hydrochemical and hydrobiological evaluation

Between 1995 and 2001, 16 measuring points at small and medium sized brooks in the Harz National Parks were sampled. The samples have been evaluated by means of hydrochemistry and macroinvertebrate biology. Although nearly all streams are largely uncontaminated by oxygen-consuming substances, they are settled only by a small number of macroinvertebrate species. There is a clear correlation between this number and pH. The reduction in species number with decrease of pH is mainly caused by the absence of most Ephemeroptera, some Coleoptera and Trichoptera. Comparing biological evaluation of acidity with physico-chemical measurements, a unacceptable underestimation was found. The reason could be that different sensitivities to acidification between regional populations seem to exist.

Despite of the low species number, there is a very specific macroinvertebrate fauna that emphasizes the conservation value of the Harz National Parks.     

Uncertainty in Coal Property Valuation in West Virginia: A Case Study

Interpolated grids of coal bed thickness are being considered for use in a proposed method for taxation of coal in the state of West Virginia (United States). To assess the origin and magnitude of possible inaccuracies in calculated coal tonnage, we used conditional simulation to generate equiprobable realizations of net coal thickness for two coals on a 7 min topographic quadrangle, and a third coal in a second quadrangle. Coals differed in average thickness and proportion of original coal that had been removed by erosion; all three coals crop out in the study area. Coal tonnage was calculated for each realization and for each interpolated grid for actual and artificial property parcels, and differences were summarized as graphs of percent difference between tonnage calculated from the grid and average tonnage from simulations. Coal in individual parcels was considered minable for valuation purposes if average thickness in each parcel exceeded 30 inches. Results of this study show that over 75% of the parcels are classified correctly as minable or unminable based on interpolation grids of coal bed thickness. Although between 80 and 90% of the tonnages differ by less than 20% between interpolated values and simulated values, a nonlinear conditional bias might exist in estimation of coal tonnage from interpolated thickness, such that tonnage is underestimated where coal is thin, and overestimated where coal is thick. The largest percent differences occur for parcels that are small in area, although because of the small quantities of coal in question, bias is small on an absolute scale for these parcels. For a given parcel size, maximum apparent overestimation of coal tonnage occurs in parcels with an average coal bed thickness near the minable cutoff of 30 in. Conditional bias in tonnage for parcels having a coal thickness exceeding the cutoff by 10 in. or more is constant for two of the three coals studied, and increases slightly with average thickness for the third coal.     

Self‐purification in Upland and Lowland Streams

Ecological investigations at four streams in Saxony‐Anhalt have shown that there are considerable differences between the self‐purification power of upland and lowland streams. This result is reflected in chemistry and in microbiology. The structure of the bottom substrate mainly influences the degree of self‐purification in connection with rate of flow and flow velocity. The results and differences are demonstrated using the example of Katzsohlbach in the landscape unit “Mittel‐ and Unterharz” and the stream Olbe in the landscape unit “Magdeburger Börde”.     

Visual classification of very fine-grained sediments: Evaluation through univariate and multivariate statistics

Classifying very fine-grained rocks through fabric elements provides information about depositional environments, but is subject to the biases of visual taxonomy. To evaluate the statistical significance of an empirical classification of very fine-grained rocks, samples from Devonian shales in four cored wells in West Virginia and Virginia were measured for 15 variables: quartz, illite, pyrite and expandable clays determined by X-ray diffraction; total sulfur, organic content, inorganic carbon, matrix density, bulk density, porosity, silt, as well as density, sonic travel time, resistivity, and -ray response measured from well logs. The four lithologic types comprised: (1) sharply banded shale, (2) thinly laminated shale, (3) lenticularly laminated shale, and (4) nonbanded shale. Univariate and multivariate analyses of variance showed that the lithologic classification reflects significant differences for the variables measured, difference that can be detected independently of stratigraphic effects. Little-known statistical methods found useful in this work included: the multivariate analysis of variance with more than one effect, simultaneous plotting of samples and variables on canonical variates, and the use of parametric ANOVA and MANOVA on ranked data.     

Binary coefficients: A theoretical and empirical study

Binary coefficients can be assigned to several categories on the basis of algebraic and conceptual properties. The phi coefficient of association is related algebraically to the chi-square statistic for 2-by-2 contingency tables, and use of this coefficient in cluster analysis permits the objective, nonarbitrary partitioning of objects among groups on the basis of previously selected levels of significant, positive association. Similarity, matching, and distance coefficients possess neither conceptual nor operational statistical meaning for many geological data sets. The weighted pair group method and flexible clustering strategy may give an overly conservative partitioning of objects among groups. Clustering by the unweighted pair group method, using the phi coefficient, is recommended for the analysis of biostratigraphic and paleoecologic presence—absence data.     

Star Formation in Violent and Normal Evolutionary Phases

Mergers of massive gas-rich galaxies trigger violent starbursts that - over timescales of > 100 Myr and regions > 10 kpc - form massive and compact star clusters comparable in mass and radii to Galactic globular clusters. The star formation efficiency is higher by 1–2 orders of magnitude in these bursts than in undisturbed spirals, irregulars or even BCDs. We ask the question if star formation in these extreme regimes is just a scaled-up version of the normal star formation mode of if the formation of globular clusters reveals fundamentally different conditions. This revised version was published online in September 2006 with corrections to the Cover Date.