The Yosemite Butterflies: Color Plates

This compilation of butterfly illustrations for the Yosemite region is intended primarily as a supplement to the text publication on Yosemite butterflies (Davenport, 2004, and Davenport, 2007, 2nd edition). Taxonomic interpretations and names follow these documents. Common names and authors of the scientific names are given in the text publication. This color plates publication also functions as a stand-alone document for naturalists and lepidopterists with need for reference illustrations only. Butterflies were selected from Ken Davenport’s private collection to illustrate most species and subspecies for the Yosemite region. If good quality specimens were available from within the region, we often used those. Most of the photography was done by Charles Grisham. In other cases Jim Brock, Howard Grisham, Norbert Kondla, Richard Meyer, John Pasko, Andrew Warren, Michael Leski, and Crispin Guppy provided needed specimens or photographs. Most of the illustrated specimens were photographed under indirect natural light to maintain color fidelity. Most were also photographed using the ‘glass plate’ method to produce shadow-free images. Digital cameras were used for all illustrations. Norbert Kondla edited the raw images and assembled them into life size plate format. Paint Shop Pro was used for image editing and Microsoft Word was used for plate assembly. Specimen localities given are mostly from within California, United States. All specimens illustrated were collected by Kenneth Davenport unless otherwise noted

Remote Sensing of Earth Resources System Capabilities V.S. Design Constraints

There is new evidence that global earth resources satellite net will be practical. This paper weighs recent advances in remote sensing to pinpoint the dominant constraints. The data and sensor systems interfacing requirements are critically reviewed. It is shown that conventional optics constraints can be relaxed, with the newer systems, based on multi-spectral imagery and statistical processing methods. The most powerful computational methods use algorithms based on a Gaussian assumption for the species vector in feature space, but biases in the imagery limit their efficiency. A rationale is proposed: improving the observational network calibrating efficiency will also improve the photogrammetric removal of imagery biases, and thereby increase signature detection efficiency. The author discloses an unexpected finding: while conventional resolution degrades with satellite altitude, signature detectability should improve since calibration improves dramatically with altitude. A unique global network is then described than can exploit these new developments. The scope of this subject is so broad that despite the paper\u27s length (sixty pages), a quantitative treatment is not practical; the author uses a combination of classical analysis, bibliographic research, and conservative technological assumptions based on the current state-of-the-art

Keeping Our Love Alive

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