The present work shows the implementation of a data collection strategy for characterizing large amounts of buildings efficiently by the conduction of remote surveys on 360° panoramic images and aerial photographs. A set of 7,296 buildings from the Latin American city of San José, Costa Rica were studied and characterized from a structural engineering point of view, obtaining information like occupancy type, height, type of lateral load resisting system, and structural irregularities, among others. Also, an estimation of the error of the remote surveys was performed, by contrasting its results with the ones of field (in situ) surveys applied on a subset of 556 structures denominated “control buildings.” The results show that for San José buildings, the predominant occupancy type, height, type, and material of the lateral load resisting system are, respectively, residential, one or two storey, wall type of confined-reinforced masonry. The overall precision level estimated for the remote surveys was 75 %, which the authors consider acceptable and an improvement when compared to more popular surveys, for example, the field surveys carried out during a population and housing census that typically have an estimated precision level of 50 %. The results proved the adopted strategy to be a promising one, albeit subject to improvements to increase its precision and reduce the implementation time.
In this paper, a new seismic site classification for the Costa Rican Strong-Motion Network (CRSMN) is proposed. The soil profile classification of the Costa Rican Seismic Code based on the average shear-wave velocity of the top 30 m (VS30) is used as a reference. The site fundamental period (Tf) is included as a parameter to complement the existing characterization. For this, the VS30 measurements from 52 accelerometric stations are related to the site fundamental period obtained through horizontal-to-vertical spectral ratios (HVSR) using ground motion records from the Costa Rican Strong-Motion Database. The H/V ratios are estimated with 5% damped acceleration response spectra and with traditional Fourier amplitude spectra from the S-wave window. From the relation between VS30 and Tf, different ranges of Tf are assigned to the existing soil profile classification and a graph with three-lines and four-areas is proposed to classify the stations of the CRSMN.
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