近30 a内蒙古阿拉善盟不同生态系统土地利用动态遥感监测

 利用遥感和GIS空间分析技术,以近30 a内蒙古阿拉善盟两期 Landsat MSS/TM遥感数据为主要信息源,通过目视解译方法提取了农田、林地、草地、水体与湿地、建设用地、荒漠等6种生态系统的25类土地利用现状数据,在此基础上进行了土地利用的动态变化分析。结果表明：近年荒漠生态系统用地达85.59%,其次是草地生态系统用地,占12.76%;近30 a土地利用变化最明显的特征是农田、林地、水域与湿地及建设用地增加80 263 hm²,占总土地面积的0.34%,草地和荒漠生态系统用地减少相应面积,总体土地利用相对变化量不大,仅为0.68%。     

劈裂真空法加固软土地基的效果分析

针对常规真空预压法加固软土地基中存在的问题,介绍了最新研制开发的气压劈裂真空预压法及其施工工艺,并通过现场试验段测试结果分析了劈裂真空法加固软土地基的效果。测试结果表明,较常规真空预压法而言,劈裂真空法可以提高真空荷载向深层土体中的传递效率和加速超静孔隙水压力的消散,既可改善深层软土的加固效果又可加速地基固结,缩短工程工期;劈裂真空法加固地基的沉降效率大于常规真空预压法处理地基,沉降易于收敛,有利于工后沉降的控制。通过加固前后孔压静力触探试验测试结果对比和取样室内试验土性参数变化分析,论证了劈裂真空法加固深层软土地基的有效性和优越性。     

超小净距隧道爆破振动现场监测及动力响应分析研究

以南京地铁超小净距隧道为工程背景,结合国内外现有研究成果和规范,研究确保小净距先行隧道安全稳定的后行隧道爆破施工控制技术。以现代信息化施工理论为依据,充分运用现场监控量测,对先行隧道爆破质点振动速度进行监测分析和施工中爆破采用减振和隔振两方面控制技术;最终现场监测结果表明,优化后的循环进尺、段最大装药量与分段爆破差等爆破参数设计合理,该爆破设计在施工中未对先行隧道安全产生较大影响;同时,通过三维数值模拟计算,得到先行隧道壁面的质点振动速度随时间的变化规律,所得最大振速符合规范要求,也再次验证了优化后的爆破设计是合理的。通过数据分析得出隧道边墙的切向和径向振速比拱脚相应振速大,爆破面前方先行洞衬砌受爆破振动的影响稍大于后方衬砌,临近爆破点的左线隧道衬砌表面振动大于远离爆破点的衬砌表面振动。该研究成果为本工程施工提供了科学依据与技术指导,也可为类似隧道工程的爆破掘进工程在理论和施工方法上提供参考借鉴。     

岩溶塌陷光纤传感试验装置的标定试验

根据岩溶土洞(塌陷)变形演化特点,分析土体与传感光纤之间的力学关系,简化塌陷力学模型,加工塌陷模拟试验装置并进行试验。首先通过对光纤加载和卸载来模拟土洞形成过程顶板荷载的变化及分析传感光纤相应的变形和轴向应变特点,然后研究了土洞规模变化对光纤传感监测的影响。研究表明:在土洞形成过程中,因土洞规模和上覆土层荷载不一而导致的应力场的分布变化,以及不同光缆对应力场变化响应灵敏性的差异,是影响分布式光纤传感技术在岩溶土洞中应用的关键因子。文中所标定的光纤传感试验装置能较好地显示岩溶土洞形成演化过程中的应变变化特征,说明分布式光纤传感技术可应用于岩溶土洞的监测预警。      

Numerical inversion of deformation caused by pressure sources: application to Mount Etna (Italy)

The interpretation of geodetic data in volcanic areas is usually based on analytical deformation models. Although numerical finite element (FE) modelling allows realistic features such as topography and crustal heterogeneities to be included, the technique is not computationally convenient for solving inverse problems using classical methods. In this paper, we develop a general tool to perform inversions of geodetic data by means of 3-D FE models. The forward model is a library of numerical displacement solutions, where each entry of the library is the surface displacement due to a single stress component applied to an element of the grid. The final solution is a weighted combination of the six stress components applied to a single element-source. The pre-computed forward models are implemented in a global search algorithm, followed by an appraisal of the sampled solutions. After providing extended testing, we apply the method to model the 1993–1997 inflation phase at Mt Etna, documented by GPS and EDM measurements. We consider four different forward libraries, computed in models characterized by homogeneous/heterogeneous medium and flat/topographic free surface. Our results suggest that the elastic heterogeneities of the medium can significantly alter the position of the inferred source, while the topography has minor effect.     

Automatic classification of dome instabilities based on Doppler radar measurements at Merapi volcano, Indonesia: Part I

Monitoring lava dome instabilities is crucial to efficiently monitor active dome building volcanoes. The Doppler radar technique provides a unique opportunity to gather information about the number of instability events occurring at the growing dome and about the dynamic processes that take place during different types of instabilities. So far, three different kinds of processes have been identified: sliding material, gravitational break-offs and explosive outbursts. In addition, Doppler radars provide rain measurements, which can be used to investigate possible correlations between rainfall and dome activity. Two radar systems have been installed at Merapi volcano in October 2001 and January 2005 to continuously monitor dome instabilities. Due to the large number of instability events that occur during times of high activity, manual processing and analysis of instability events is not practical for monitoring purposes. Therefore, an automatic classification system has been developed, which is capable of identifying different kinds of instabilities as well as rainfall. Two different kinds of classifier models have been applied: (1) neural network and (2) K-nearest-neighbour classifier model. Both classify Doppler spectra according to the underlying dynamic process, that is, rain, sliding material, gravitational break-off or explosive outburst. The classifiers are able to identify disturbances, which have no physical source, but are merely artefacts from the radar device itself. Because radar events are sequences of Doppler spectra, a rule set has been defined, which finally determines the event class. All classifiers have been trained and tested on independent data sets to estimate the classification performance. The overall classification rate is about 90 per cent. Discrimination of instabilities and non-volcanic events reaches about 98 per cent accuracy.     

Stable inversions for complete moment tensors

The seismic moment tensors for certain types of sources, such as volcanic earthquakes and nuclear explosions are expected to contain an isotropic component. Some earlier efforts to calculate the isotropic component of these sources are flawed due to an error in the method of Jost & Herrmann. We corrected the method after Herrmann & Hutchensen and found great improvement in the recovery of non-double-couple moment tensors that include an isotropic component. Tests with synthetic data demonstrate the stability of the corrected linear inversion method, and we recalculate the moment tensor solutions reported in Dreger et al. for Long Valley caldera events and Dreger & Woods for Nevada Test Site nuclear explosions. We confirm the findings of Dreger et al. that the Long Valley volcanic sources contain large statistically significant isotropic components. The nuclear explosions have strikingly anomalous source mechanisms, which contain very large isotropic components, making it evident that these events are not tectonic in origin. This indicates that moment tensor inversions could be an important tool for nuclear monitoring.     

Synchronizing seismic networks with ambient noise

The technique of retrieving Green's functions by pairwise correlation of a random wavefield is used to estimate the stability of the timing system of a seismic network. The method is demonstrated with data from a network consisting of stations with four independent clocks and GPS-receivers. For a two years period, daily measurements of the timing error of each of the four systems are obtained. These measurements can be used to correct the timing of the data in periods without GPS reception. The accuracy of this method can exceed the precision of the internal station clocks already after a single day of uncorrected drift.     

江苏数字地震台网地震速报软件

介绍江苏数字地震台网地震速报软件功能及在江苏数字地震台网地震速报工作中的应用,该软件实现了实时数据的收集,对地震三要素快速准确地处理,提高了工作效率,在地震监测工作中发挥了重要作用。     

Anomalous CO2 content in the Gallicano thermo-mineral spring (Serchio Valley,Italy) before the 21 June 2013, Alpi Apuane earthquake (M = 5.2)

Since late 2002, a continuous automatic monitoring network is operating in Tuscany, Central Italy, to investigate the geochemical response of selected aquifers to local seismic activity. The monitoring is aimed at identifying possible earthquake geochemical precursors. The network is currently constituted by six stations, all equipped with sensors for the measurement of temperature, pH, redox potential, electrical conductivity, CO₂ and CH₄ dissolved concentration, that have been installed in the areas of highest seismic risk of the region. By combining geochemical data gathered from the automatic station of Gallicano (Garfagnana, Northern Tuscany), and obtained via chemical analyses of spring water samples collected during periodic field surveys in the area surrounding this station, the most significant aspects of the deep fluid circulation paths feeding the Gallicano thermo-mineral system have been investigated, and the geochemical baseline of the Gallicano spring defined. The CO₂ continuous signal recorded by the Gallicano automatic station has been then processed over the period 2003–2013 in the search for anomalies possibly related to local seismic activity. A substantial anomaly in CO₂ content has been observed at Gallicano in conjunction with the Alpi Apuane earthquake (M = 5.2) of 21 June 2013.