A strong motion database for the chiba seismometer array and its engineering analysis

A three-dimensional seismometer array was installed in the Chiba Experiment Station of the Institute of Industrial Science, University of Tokyo in 1982. The array system consists of 44 three-component accelerometers densely placed both on the ground surface and in boreholes. A complementary system for the measurement of ground and buried pipe strains was also installed at the same site. The array system has been successfully in operation, and more than 160 earthquakes have been recorded. Considering a wide use of these seismograms, the Chiba array database has recently been created comprising twenty-seven major events. This paper describes the Chiba array system and its strong motion database. Results of engineering analysis using the selected records are also presented.     

1998 Adana-Ceyhan (Turkey) Earthquake and a Preliminary Microzonation Based on Liquefaction Potential for Ceyhan Town

A moderate earthquake (M_s = 6.2) occurred in the Cukurova region in the southern part of Turkey, on 27 June 1998. It resulted in loss of 145 lives and significant damage particularly in the settlements close to the epicenter at the south of Ceyhan town. Widespread liquefaction and associated sand boils, ground fissures and ground deformations due to lateral spreading occurred during this earthquake. In this study, main characteristics of the earthquake are presented and liquefaction throughout the site was assessed. An attempt was also made to establish preliminary microzonation maps for Ceyhan using the data from liquefaction susceptibility analyses. The results of the analyses indicated that the data from the liquefied sites were within the empirical bounds suggested by the field-performance evaluation method. Fortunately, most of the riversides were used for agricultural purposes alone, damage to structures from liquefaction and associated ground failures were rather limited. Preliminary assessments indicated that at depths of about 5 m the liquefaction potential of thin sand layers tends to diminish.     

Palaeomagnetically defined rotations of fault-bounded continental blocks in the North Anatolian Shear Zone, North Central Anatolia

The 1200 km-long North Anatolian Transform Fault connects the East Anatolian post-collisional compressional regime in the east with the Aegean back-arc extensional regime to the west. This active dextral fault system lies within a shear zone reaching up to 100 km in width, and consists of southward splining branches. These branches, which have less frequent and smaller magnitude earthquake activity compare to the major transform, cut and divide the shear zone into fault delimited blocks. Comparison of palaeomagnetic data from 46 sites in the Eocene volcanics from different blocks indicate that each fault-bounded block has been affected by vertical block rotations. Although clockwise rotations are dominant as expected from dextral fault-bounded blocks, anticlockwise rotations have also been documented. These anticlockwise rotations are interpreted as due to anticlockwise rotation of the Anatolian Block, as indicated by GPS measurements, and the effects of unmapped faults or pre-North Anatolian Fault tectonic events.     

Astrophysical Molecules AlD and CaH: Transition Probabilities and Dissociation Energy

The Franck-Condon (FC) factors and r-centroids for the bands systemC ¹ Σ ⁺ → X ¹ Σ ⁺ of AlD and E ² Π → X ² Σ ⁺ of CaH have been evaluated by means of a reliable numerical integration procedure by using a suitable potential. The dissociation energy, D _e, for the electronic ground states of AlD and CaH have been estimated by the curve fitting method to the RKRV experimental potential curve turning out to be 3.01 eV and 2.32 eV, respectively. This revised version was published online in July 2006 with corrections to the Cover Date.     

Liquefaction-related building damage in Adapazari during the Turkey earthquake of August 17, 1999

The goal of this paper is to present especially the source and the type of liquefaction-related failures of those buildings which satisfied the structural codes of buildings and practices but experienced settlement, tilting and overturning in Adapazari during the Turkey earthquake of August 17, 1999. In this context, the Adapazari region is first evaluated in terms of geological setting, tectonics, seismicity and liquefaction susceptibility based on in situ and laboratory test data. In addition, the number of stories, types of buildings and their related failures have been mapped accordingly. Furthermore, laboratory model tests are conducted to enforce and/or confirm the type of building's failures with particular reference to their geometrical shape and the number of stories assuming that the models representing buildings satisfy the structural codes of buildings and practices.     

Automatic extraction of sparse trees from high-resolution ortho-images

Obtaining information about tree species distribution in agricultural lands is a topic of interest for various applications, such as tree inventory, forest management, agricultural land management, crop estimation, etc. This information can be derived from images obtained from modern remote sensing technology, which is the most economical way as compare to field surveys covering large geographic areas. Therefore, in this study, a new method is proposed for extraction and counting of sparse and regular distributed individual pistachio trees from agricultural areas on large scale from high-resolution digital ortho-photo maps, which were obtained using an airborne sensor (Ultracam-X). The input images were first smoothed by applying Gaussian filter to reduce the impact of noise. Normalized difference vegetation indices (NDVI) were then derived to obtain vegetation areas followed by Otsu’s global thresholding algorithm to obtain candidate tree areas. Further, connected component (CC) analysis was applied to segregate each object. Morphological processing was performed to fill holes within tree objects and get smooth contours, which were obtained by using the Moore-neighbor tracing method (MNTM) for each CC, while geometrical constraints were applied to undermine possible non-tree elements from output image. To further improve the segmentation results for sparse trees, a new method was applied, called quadratic local analysis (QLA). QLA helped to segment the trees, which were missed by the Otsu method due to low contrast and resulted in improved accuracy (3–6%). The obtained results were compared with well-known support vector machine (SVM) classifier. Proposed method produced slightly better results (1–5%) than SVM for extraction of pistachio trees and obtained accuracy for QLA and SVM were 96 and 91% for region 1, while 91 and 90% for region 2 respectively.     

Probabilistic seismic hazard assessment for Lake Van basin,Turkey

The seismic hazard for the Lake Van basin is computed using a probabilistic approach, along with the earthquake data from 1907 to present. The spatial distribution of seismic events between the longitudes of 41–45° and the latitudes of 37.5–40°, which encompasses the region, indicates distinct seismic zones. The positions of these zones are well aligned with the known tectonic features such as the Tutak-Çald?ran fault zone, the Özalp fault zone, the Geva? fault zone, the Bitlis fault zone and Karl?ova junction where the North Anatolian fault zone and East Anatolian fault zone meet. These faults are known to have generated major earthquakes which strongly affected cities and towns such as Van, Mu?, Bitlis, Özalp, Muradiye, Çald?ran, Erci?, Adilcevaz, Ahlat, Tatvan, Geva? and Gürp?nar. The recurrence intervals of M _s ≥ 4 earthquakes were evaluated in order to obtain the parameters of the Gutenberg–Richter measurements for seismic zones. More importantly, iso-acceleration maps of the basin were produced with a grid interval of 0.05 degrees. These maps are developed for 100- and 475- year return periods, utilizing the domestic attenuation relationships. A computer program called Sistehan II was utilized to generate these maps.     

Long-term trend analysis using discrete wavelet components of annual precipitations measurements in Marmara region (Turkey)

The purpose of this study is to determine the possible trends in annual total precipitation series by using the non-parametric methods such as the wavelet analysis and Mann-Kendall test. The wavelet trend (W-T) analysis is for the first time presented in this study. Using discrete wavelet components of measurement series, we aimed to find which periodicities are mainly responsible for trend of the measurement series. We found that some periodic events clearly affect the trend of precipitation series. 16-yearly periodic component is the effective component on Bal?kesir annual precipitation data and is responsible for producing a real trend founded on the data. Also, global wavelet spectra and continuous wavelet transform were used for analysis to precipitation time series in order to clarify time-scale characteristics of the measured series. The effects of regional differences on W-T analysis are checked by using records of measurement stations located in different climatic areas. The data set spans from 1929 to 1993 and includes precipitation records from meteorological stations of Turkey. The trend analysis on DW components of the precipitation time series (W-T model) clearly explains the trend structure of data.     

Modelling evapotranspiration using discrete wavelet transform and neural networks

This study combines wavelet transforms and feed‐forward neural network methods for reference evapotranspiration estimation. The climatic data (air temperature, solar radiation, wind speed, relative humidity) from two stations in the United States was evaluated for estimating models. For wavelet and neural network (WNN) model, the input data was decomposed into wavelet sub‐time series by wavelet transformation. Later, the new series (reconstructed series) are produced by adding the available wavelet components and these reconstructed series are used as the input of the WNN model. This phase is pre‐processing of raw data and the main different of the WNN model. The performance of the WNN model was compared with classical neural networks approach [artificial neural network (ANN)], multi‐linear regression and Hargreaves empirical method. This study shows that the wavelet transforms and neural network methods could be applied successfully for evapotranspiration modelling from climatic data. Copyright © 2009 John Wiley & Sons, Ltd.