Mapping hydrothermally altered rocks in the Northern Grapevine Mountains, Nevada and California with the airborne imaging spectrometer

Seven flightlines of Airborne Imaging Spectrometer (AIS) data were analyzed for an area of hydrothermally altered rocks. The data were reduced to reflectance relative to an average spectrum, and an automated procedure was used to produce a color coded image displaying absorption band information. Individual spectra were extracted from the AIS images to determine the detailed mineralogy. Two alteration types were mapped based upon mineralogy identified using the AIS data. The primary alteration type is quartz sericite pyrite alteration which occurs in northwest-trending zones in quartz monzonite porphyry. The AIS data allow identification of sericite (muscovite) based upon a strong absorption feature near 2.21 micron and weaker absorption features near 2.35 and 2.45 micron. The second alteration type occurs as a zone of argillic alteration associated with a granitic intrusion. Montmorillonite was identified based on a weak to moderate absorption feature near 2.2 micron and the absence of the two absorption features at longer wavelengths characteristic of sericite. Montmorillonite could be identified only where concentrations of sericite did not mask the montmorillonite spectrum

On the particle paths and the stagnation points in small-amplitude deep-water waves

In order to obtain quite precise information about the shape of the particle paths below small-amplitude gravity waves travelling on irrotational deep water, analytic solutions of the nonlinear differential equation system describing the particle motion are provided. All these solutions are not closed curves. Some particle trajectories are peakon-like, others can be expressed with the aid of the Jacobi elliptic functions or with the aid of the hyperelliptic functions. Remarks on the stagnation points of the small-amplitude irrotational deep-water waves are also made.Comment: to appear in J. Math. Fluid Mech. arXiv admin note: text overlap with arXiv:1106.382

Environmental and Health Disparities in Appalachian Ohio: Perceptions and Realities

Background. Appalachia is a region of the United States that faces significant environmental and health disparities. Understanding these disparities and the social determinants that contribute to them will help public health practitioners make better decisions. The purpose of this research is two-fold. First, through secondary data analysis, we document environmental and health disparities as well as demographic and economic conditions that may contribute to these disparities between Appalachian and non-Appalachian Ohio. Second, we examine perceptions of environmental health practitioners about the differences in environmental conditions between Appalachian and non-Appalachian Ohio. Methods. We gathered secondary data about economics, health, and the environment from the Ohio Department of Health, Healthy Ohio Community Profiles, the U.S. Environmental Protection Agency, and the U.S. Census. In addition, we conducted an online survey of 76 environmental health professionals across Ohio. Results. The secondary data indicates that there are significant differences between Appalachian and non-Appalachian Ohio in terms of socioeconomic, health, and environmental indicators. In addition, environmental health professionals perceive worse environmental conditions in the Appalachian region and indicate that there are environmental and health disparities found in this part of the state that do not exist elsewhere. Conclusions. The results contribute to understanding environmental and health conditions that contribute to health disparities in the Appalachian region as well as suggest approaches for public health practitioners to reduce these disparities

Age and growth of spiny dogfish (Squalus acanthias) in the Gulf of Alaska: analysis of alternative growth models

Ten growth models were fitted to age and growth data for spiny dogfish (Squalus acanthias) in the Gulf of Alaska. Previous studies of spiny dogfish growth have all fitted the t0 formulation of the von Bertalanffy model without examination of alternative models. Among the alternatives, we present a new two-phase von Bertalanffy growth model formulation with a logistically scaled k parameter and which estimates L0. A total of 1602 dogfish were aged from opportunistic collections with longline, rod and reel, set net, and trawling gear in the eastern and central Gulf of Alaska between 2004 and 2007. Ages were estimated from the median band count of three independent readings of the second dorsal spine plus the estimated number of worn bands for worn spines. Owing to a lack of small dogfish in the samples, lengths at age of small individuals were back-calculated from a subsample of 153 dogfish with unworn spines. The von Bertalanffy, two-parameter von Bertalanffy, two-phase von Bertalanffy, Gompertz, two-parameter Gompertz, and logistic models were fitted to length-at-age data for each sex separately, both with and without back-calculated lengths at age. The two-phase von Bertalanffy growth model produced the statistically best fit for both sexes of Gulf of Alaska spiny dogfish, resulting in L∞ = 87.2 and 102.5 cm and k= 0.106 and 0.058 for males and females, respectively

Automated extraction of absorption features from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data

Automated techniques were developed for the extraction and characterization of absorption features from reflectance spectra. The absorption feature extraction algorithms were successfully tested on laboratory, field, and aircraft imaging spectrometer data. A suite of laboratory spectra of the most common minerals was analyzed and absorption band characteristics tabulated. A prototype expert system was designed, implemented, and successfully tested to allow identification of minerals based on the extracted absorption band characteristics. AVIRIS spectra for a site in the northern Grapevine Mountains, Nevada, have been characterized and the minerals sericite (fine grained muscovite) and dolomite were identified. The minerals kaolinite, alunite, and buddingtonite were identified and mapped for a site at Cuprite, Nevada, using the feature extraction algorithms on the new Geophysical and Environmental Research 64 channel imaging spectrometer (GERIS) data. The feature extraction routines (written in FORTRAN and C) were interfaced to the expert system (written in PROLOG) to allow both efficient processing of numerical data and logical spectrum analysis