New Framework of Combining Observations with Topographic Slope to Estimate VS30 and Its Application on Building a VS30 Map for Mainland China

变异函数 钻孔 地质学 中国大陆 克里金 空间分析 地图学 统计 中国 地理 数学 遥感 古生物学 考古
作者
Jian Zhou,Xiaojun Li,Xuemin Tian,Guangyin Xu
出处
期刊:Bulletin of the Seismological Society of America [Seismological Society of America]
卷期号:112 (4): 2049-2069 被引量:15
标识
DOI:10.1785/0120210227
摘要

ABSTRACT We propose a new framework of VS30 proxy based on Cokriging method and apply the framework to build a VS30 map for mainland China. This framework utilizes the VS30–topographic slope correlation in the cross-semivariogram to benefit VS30 estimation and has the following benefits: (1) the estimation results are consistent with the measurement data; (2) the estimation uncertainty can be represented by error variance at each unsampled location according to the spatial structure of VS30 and topographic slope; (3) the result map does not have artificial boundaries; and (4) the estimation results can reflect the spatial relation between VS30 and topographic slope and the spatial relation of local spatial environment of topographic slope. We quantify the performance of this framework and compare it with that of three other topographic slope-based VS30 proxy models, including original models developed from exogenous data and models developed from China local data. The result shows that the framework proposed in this article has the best performance. The framework is applied to 7797 borehole VS30 measurements to build a VS30 map for mainland China. The map can capture the high VS30 values in regions where the geological conditions are dominated by flat-lying rocks. Moreover, we consider the effect of sample bias that comes from oversampling of borehole profiles in flat terrain regions when applying borehole data in the proposed framework. We utilize the relation of VS30 and topographic slope to quantify this bias, and use a distance-related data spatial declustering method to eliminate it.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
ding应助结实小猫咪采纳,获得10
1秒前
13988548568完成签到,获得积分10
1秒前
1秒前
der完成签到,获得积分10
2秒前
宇宙第一帅完成签到,获得积分10
2秒前
wan发布了新的文献求助10
2秒前
研友_VZG7GZ应助galaxy采纳,获得10
3秒前
3秒前
2025zmx完成签到,获得积分10
3秒前
LX应助科研通管家采纳,获得20
3秒前
3秒前
思源应助科研通管家采纳,获得10
3秒前
大个应助科研通管家采纳,获得10
3秒前
隐形曼青应助深情的热狗采纳,获得10
3秒前
godblessyou应助科研通管家采纳,获得10
3秒前
feng应助科研通管家采纳,获得20
4秒前
yyy发布了新的文献求助10
4秒前
丘比特应助科研通管家采纳,获得10
4秒前
灵泽发布了新的文献求助10
4秒前
大模型应助科研通管家采纳,获得10
4秒前
ddd应助科研通管家采纳,获得10
4秒前
烟花应助科研通管家采纳,获得10
4秒前
CodeCraft应助科研通管家采纳,获得10
4秒前
半生发布了新的文献求助10
4秒前
4秒前
godblessyou应助科研通管家采纳,获得10
4秒前
4秒前
cc小木屋应助科研通管家采纳,获得20
4秒前
斯文败类应助科研通管家采纳,获得10
4秒前
orixero应助科研通管家采纳,获得30
4秒前
852应助科研通管家采纳,获得30
4秒前
feng应助科研通管家采纳,获得20
4秒前
godblessyou应助科研通管家采纳,获得10
4秒前
godblessyou应助科研通管家采纳,获得10
4秒前
5秒前
5秒前
5秒前
5秒前
5秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6493084
求助须知:如何正确求助?哪些是违规求助? 8290568
关于积分的说明 17691341
捐赠科研通 5585230
什么是DOI,文献DOI怎么找? 2915545
邀请新用户注册赠送积分活动 1892630
关于科研通互助平台的介绍 1750980