Garner Valley Downhole Array Subsurface Imaging Dataset

Garner Valley Downhole Array Subsurface Imaging Dataset是由弗吉尼亚理工学院暨州立大学等机构在2019年采集的大型地下成像数据集。该数据集包含196个三组件节点站，以14x14网格布局，间距5米，用于记录由振动卡车和仪器化大锤产生的主动源数据以及包含环境噪声的被动波场数据。数据集适用于主动源和被动波场的三维成像，以及其他地下表征技术，如水平到垂直频谱比(HVSR)、多通道表面波分析(MASW)和微震阵列测量(MAM)。数据集的创建旨在解决高空间分辨率下三维浅层地下工程材料性质表征的需求，特别是在工程分析中的应用。

The Garner Valley Downhole Array Subsurface Imaging Dataset is a large-scale subsurface imaging dataset collected in 2019 by Virginia Polytechnic Institute and State University (Virginia Tech) and other institutions. This dataset consists of 196 three-component node stations arranged in a 14×14 grid with a spacing of 5 meters, which records active-source data generated by vibratory trucks and instrumented sledgehammers, as well as passive wavefield data containing ambient noise. It is applicable to three-dimensional imaging of active-source and passive wavefields, as well as other subsurface characterization techniques including Horizontal-to-Vertical Spectral Ratio (HVSR), Multichannel Analysis of Surface Waves (MASW), and Microseismic Array Measurement (MAM). The dataset was developed to address the need for characterizing three-dimensional shallow subsurface engineering material properties at high spatial resolution, especially for applications in engineering analysis.