{'fraction_non_alphanumeric': 0.020301244269810084, 'fraction_numerical': 0.016371971185330715, 'mean_word_length': 5.47457627118644, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Terrain‐Based Site‐Conditions Map of California with Implications for the Contiguous United States

Abstract We present an approach based on geomorphometry to predict material properties and characterize site conditions using the V S 30 parameter (time‐averaged shear‐wave velocity to a depth of 30 m). Our framework consists of an automated terrain classification scheme based on taxonomic criteria (slope gradient, local convexity, and surface texture) that systematically identifies 16 terrain types from 1‐km spatial resolution (30 arcsec) Shuttle Radar Topography Mission digital elevation models (SRTMDEMs). Using 853 V S 30 values from California, we apply a simulation‐based statistical method to determine the mean V S 30 for each terrain type in California. We then compare the V S 30 values with models based on individual proxies, such as mapped surface geology and topographic slope, and show that our systematic terrain‐based approach consistently performs better than semiempirical estimates based on individual proxies. To further evaluate our model, we apply our California‐based estimates to terrains of the contiguous United States. Comparisons of our estimates with 325 V S 30 measurements outside of California, as well as estimates based on the topographic slope model, indicate our method to be statistically robust and more accurate. Our approach thus provides an objective and robust method for extending estimates of V S 30 for regions where in situ measurements are sparse or not readily available.