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This report and related software and figures are available via anonymous ftp from "an-dreas.wr.usgs.gov" (130.118.49.1) in directory "~ftp/pub/outgoing/evans/OFR_98_109". Use your e-mail address as login password. All files are either ASCII PostScript® or binary Gerber® plot files originating from a PC. Use binary/#; for the Gerber® files and compressed files, asciiftp for uncompressed PostScript®. Introduction The severity of earthquake ground shaking varies tremendously over very short distances (Figures la-c). Within a distance of as little as 1 km from the nearest station, one knows little more than what can be obtained from an attenuation relation, given only distance from the fault rupture and the geology of the site. For example, if some station measures 0.5 g peak ground acceleration (PGA), then at a distance of 1 km from that site, under otherwise identical conditions, the shaking has one chance in three of being under 0.36 g or over 0.70 g, based on the curve shown in Figures \a,c. Similarly, pseudovelocity (PSV) response spectra have a 5% chance of differing by 2x at 1 km distance (Figure \b). This variance can be the difference between moderate and severe damage. CO o BJF93 O Si cT p o S. D = by definition ^ BJF93 = Boore et al. (1993) receiver sigma * sqrt(2) = BJF93 * (1-exp(-sqrt(1.33 * xi)) (eyeball fit) D = sliding bins of 20 (o = sliding bins of 10) 012345 Interstation Distance (median £, km) Figure 1. The spatial variability of strong ground motion, expressed as the log-normal standard deviation (a) between neighboring stations separated by ^ km. These results are compiled from the literature, in some instances recast or evaluated by the author. Sources cited on Figures, (a) Peak ground acceleration. Hence, there are critical needs, both in emergency response and in mitigation (prediction of shaking strength, building codes, structural engineering), to sample ground shaking densely enough to identify individual neighborhoods suffering localized, strong shaking. These needs imply a spatially dense network of strong-motion seismographs, probably numbering thousands of sites in an urban region the size of the San Francisco Bay Area, California (Figure Ic). It has not been economically feasible to field that many instruments, since existing ones cost many thousands of dollars apiece. For example, there are currently just a few dozen digital free-field instruments in the Bay Area. This paper is one step toward a solution to this conundrum. I demonstrate that a recently …

The design and performance of a low-cost strong-motion sensor using the ICS-3028 micromachined accelerometer