General seismic wave and phase detection software driven by deep learning

We developed an automatic seismic wave and phase detection software based on PhaseNet, an efficient and highly generalized deep learning neural network for P- and S-wave phase picking. The software organically combines multiple modules including application terminal interface, docker container, data visualization, SSH protocol data transmission and other auxiliary modules. Characterized by a series of technologically powerful functions, the software is highly convenient for all users. To obtain the P- and S-wave picks, one only needs to prepare three-component seismic data as input and customize some parameters in the interface. In particular, the software can automatically identify complex waveforms (i.e. continuous or truncated waves) and support multiple types of input data such as SAC, MSEED, NumPy array, etc. A test on the dataset of the Wenchuan aftershocks shows the generalization ability and detection accuracy of the software. The software is expected to increase the efficiency and subjectivity in the manual processing of large amounts of seismic data, thereby providing convenience to regional network monitoring staffs and researchers in the study of Earth's interior.     

Fault detection by reflected surface waves based on ambient noise interferometry

Detecting subsurface fault structure is important for evaluating potential earthquake risks associated with active faults. In this study, we propose a new method to detect faults using reflected surface waves observed in ambient noise cross correlation functions. Ambient noise tomography using direct surface waves obtained from ambient noise interferometry has been widely used to characterize active fault zones. In cases where a strong velocity contrast exists across the fault interface, fault-reflected surface waves are expected. We test this idea using a linear array deployed in the Suqian segment of Tanlu fault zone in Eastern China. The fault-reflected surface waves can be clearly seen in the cross-correlation functions of the ambient noise data, and the spatial position of the fault on the surface is close to the stations where the reflected signals first appear. Potentially reflected surface waves could also be used to infer the dip angle, fault zone thickness and the degree of velocity contrast across the fault by comparing synthetic and observed waveforms.     

动态PPP定位中周跳自动探测与处理策略

周跳的自动探测与有效处理是动态PPP定位中关键和棘手的问题.本文提出利用L1、L2、L4、L5历元间差分,并联合doppler积分综合探测与定位周跳.对准确判定发生周跳的卫星,不进行周跳的固定和修复,而是将其作为新升起的卫星重新估计模糊度.这一处理策略避免了周跳修复不准对整个定位精度的影响,当保证不少于4颗卫星连续跟踪时,PPP动态定位的精度是稳定的.实验结果表明：在相对比较恶劣的动态环境下,动态PPP定位精度可以达到0.1~0.2 m水平.     

煤矿井下定向钻孔中电阻率探测技术与应用

受高瓦斯/承压奥灰水威胁的工作面开采前,一般采取定向钻进技术在工作面底板开展压裂或注浆工程保障开采安全。利用底板定向钻孔开展孔中探测工作,可更加精细揭露工作面内隐伏构造,还可实现“一孔多用”。为解决定向钻孔内的探测问题,提出一种在水平定向钻孔中进行直流电阻率法探查的方法。定向钻孔施工完毕后,退出定向钻孔施工的通缆钻杆,送入内平钻杆,将孔中高密度电缆通过钻杆尾端特制水便送入钻孔,使孔中电缆平铺于钻孔中,在定向钻孔水平段,进行孔内直流电阻率法径向探测。在理论上通过数值模拟研究层状介质下单孔测量工作模式的接收信号衰减规律、视电阻率曲线变化特征、顶底板岩性对测量结果的影响等,并采用单孔测量数据对孔旁异常范围进行反演定位。数值模拟研究表明,孔中电阻率探测方法对隐伏的异常体有良好的探测效果。通过在陕西韩城某矿井下实际煤层底板探测试验,对研究区2个定向抽采钻孔孔中探测数据进行处理,反演结果异常区与工作面内隐伏小断层位置吻合,验证了定向钻孔中电缆布置的可行性和定向钻孔内通过孔内径向和孔间透视探测隐伏构造的可靠性。      

南平市公路运输危险化学品污染事件的研究

对2004-2007年在福建省南平市行政区域内发生的公路运输危险品污染事件进行统计分析,研究结果表明：南平市4年间共发生26起公路运输危险化学品事故,每年平均6．5起．其中夜间发生事故的比率为57．7％,夏季发生事故的比率为34．6％,35～45岁驾驶员年龄段事故发生率高达59．1％,驾龄在11～15年的为事故多发驾龄段,其发生率为45．5％,发生在弯道的事故占61．5％,超载发生事故的可能性为44．0％,占总数65．4％的事故对环境产生污染．205国道南平段发生危险化学品运输事故的概率为0．0124次／（a·km）,发生危险化学品泄漏事件的可能性为0．0142次／（a·km）,发生危险化学品1t以上大规模连续泄漏事件的概率为0．0098次／（a·km）．     

Geometric-based approach for integrating VGI POIs and road networks

Integrating heterogeneous spatial data is a crucial problem for geographical information systems (GIS) applications. Previous studies mainly focus on the matching of heterogeneous road networks or heterogeneous polygonal data sets. Few literatures attempt to approach the problem of integrating the point of interest (POI) from volunteered geographic information (VGI) and professional road networks from official mapping agencies. Hence, the article proposes an approach for integrating VGI POIs and professional road networks. The proposed method first generates a POI connectivity graph by mining the linear cluster patterns from POIs. Secondly, the matching nodes between the POI connectivity graph and the associated road network are fulfilled by probabilistic relaxation and refined by a vector median filtering (VMF). Finally, POIs are aligned to the road network by an affine transformation according to the matching nodes. Experiments demonstrate that the proposed method integrates both the POIs from VGI and the POIs from official mapping agencies with the associated road networks effectively and validly, providing a promising solution for enriching professional road networks by integrating VGI POIs.     

基于GWR模型的道路网络对森林碳密度干扰的地理变异

以闽江上游地区为例,在分析三明市2007—2016年森林碳密度时空动态的基础上,采用常规的以及改进后的道路网络测度指标,应用缓冲区分析方法和地理加权回归（Geographically Weighted Regression,GWR）模型,从线上和面上分别探讨道路网络对森林碳密度干扰的地理变异规律。结果表明：① 碳密度受到道路网络的较大影响,路网影响域内外碳密度的大小排序为：路网影响域内＜整个研究区＜路网影响域外;多条道路影响域重叠区的碳密度(26.330 Mg/hm²)明显低于单条道路影响域的碳密度(37.406 Mg/hm²);不同等级道路影响域的碳密度由大到小依次为县道＞高速＞省道＞其它道路＞国道＞乡道。道路网络对2007—2016年碳密度的降低也有明显影响。② GWR模型的分析结果表明,路网对碳密度的影响程度随着样点的变化而变化,具有“空间非平稳性”。碳密度随着路网密度的增加而降低,而随着离道路距离的增加而增加。③ 研究区西北部和中部,GWR的回归系数及相关系数均较大,表明这2个区域道路对碳密度影响大且解释力皆较强。     

基于GIS的宁夏路网空间特征研究

宁夏回族自治区作为我国唯一的省级回族集聚地区,是一个很独特的地理-人口-交通单元,也是连接华北和西北的重要节点.以宁夏的交通路网数据为基础,通过设置阻抗改进网络分析法,并结合成本距离算法和GIS空间分析计算2011、2017年和2023年的县(区)可达性,研究全区路网的空间结构特征,并提出路网发展的决策建议.研究表明:...     

ETM+卫星影像极地云层检测及分析

云一直是遥感图像预处理和分析中的一大难点,本文在分析南极地区成像特点的基础上,试图利用增强型主题成像传感器(ETM+)获取影像的多波段特点,对南极格罗夫山地区ETM+卫星影像进行云的检测。结果表明,该方法不仅能比较成功地检测极地云层像元,而且能有效地去除部分厚云的影响。