基于重力测点和段差变化的前郭5.8级震群研究与三维反演     

王同庆  张品  刘金钊  陈兆辉  张双喜  朱传东 《大地测量与地球动力学》2019,39(5):469-475

利用东北地区近几年流动重力观测数据，分析前郭5.8级震群周边重力点值的时序变化特征，并基于重力段差变化对东北地区整体和局部重力变化引入能够反映异常显著性程度的指标量G和C值，最后对前郭5.8级震群前的重力场动态变化作三维密度反演。结果表明：1）前郭5.8级震群发震构造两侧的局部重力变化具有较明显的差异性，其变化趋势可作为识别构造活化或解耦运动的标志；2）显著性指标量G和C值能够为地震重力前兆的定量描述提供新思路；3）震前重力变化的反演结果显示地震发生在质量运移的过渡区域，垂向反演结果对本次地震的震源深度有一定的揭示意义。  相似文献   

Swelter in the city: Urban greenery and its effects on temperature in Guwahati,India     

Monjit Borthakur  Anup Saikia  Kiran Sharma 《Singapore journal of tropical geography》2020,41(3):341-366

Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub-urban areas with 50 per cent greenery.  相似文献   

基于手机数据的北京市城市与近郊交互模式挖掘     

彭卉  杜云艳  易嘉伟  刘张  王会蒙 《地球信息科学学报》2019,21(1):97-106

在城镇化进程中,城市与近郊之间通过职住、货运、游憩等活动产生越来越紧密的交互联系,对于这些交互联系的准确识别和定量刻画,是理解城乡空间关系的重要手段,也能为城市的资源有效配置与合理规划提供重要的现状信息。本文通过对全北京在一日之内的手机信令数据所反映的人群移动轨迹的深入分析,融合城市的POI信息形成顾及人类活动时空信息的空间交互类型推断。以北京市为例,对城市中心与近郊之间远距离的强交互进行定性、定量和定位的探索。本文发现了北京市多尺度下空间交互模式和距离衰减规律,判断了城乡异常交互类型,对比了城乡之间和城市内部的交互模式的异同,以及基于交互类型视角提取了城乡异常交互的空间特征。研究认为,基于手机信令数据,利用停留点提取和高斯核密度估计的空间交互类型推断有效地发现了北京市周末的远距离出行类型特点,提取了其空间交互强度和空间特征,揭示了基于人类活动的北京市周末城乡交互模式。  相似文献   

基于改进的向后-向前选择法粗差定位与估值算法     

柴双武  杨晓琴 《大地测量与地球动力学》2019,39(5):538-543

对传统的向后-向前选择法粗差定位方法进行改进，即在原有基础上加入对平差模型的整体检验，计算统计量的相关系数，通过对偏相关系数的检验来定位统计量相关的粗差观测值。通过模拟粗差算例证明，该算法能够准确定位多维粗差，有效改善粗差定位转移的现象，且粗差估值结果比较可靠。  相似文献   

Formation of Carbon-Enhanced Metal-Poor RR Lyrae Stars     

《Chinese Astronomy and Astrophysics》2020,44(1):61-69

Carbon-enhanced metal-poor (CEMP) stars are considered to be related to the first generation of stars, and responsible for the chemical evolution of the early Galaxy. More than half of them are in binaries, and could be explained by the binary evolution, but the formation channel of them is still not fully understood. Among the hundreds of CEMP stars, there are nine CEMP RR Lyrae stars identified, and at least seven of which are very likely not binaries. The usual binary star evolution channel is difficult to produce such a single star, particularly that of carbon enrichment. One way in which such a single star might be produced is the merger of a helium white dwarf with a Hertzsprung gap (HG) star. We use a stellar evolution program to calculate the models of the merger remnants, and find that the models can reproduce the observed distribution of these CEMP single RR Lyrae stars in terms of surface temperature, gravity, and carbon abundance. Hence, it is extremely possible that the helium white dwarf and HG star merger model is one of the formation channels of the metal-poor carbon-rich RR Lyrae stars.  相似文献   

利用卫星遥感海面温度、高度联合反演南海北部三维温度场     

汤博  侯一筠  殷玉齐  胡珀 《海洋科学》2019,43(11):1-10

利用历史观测得到的温度剖面数据,通过严格筛选和插值,建立了南海北部的气候态垂向温度剖面。随后,利用回归统计分析的方法构建了海面温度异常(SSTA)、海面高度异常(SSHA)联合扩展温度剖面的经验回归模型,并采用卫星遥感得到的SST和SSH数据扩展了南海北部的三维海洋温度场,其时间分辨率为天,空间分辨率为0.25°×0.25°。通过与观测数据的对比研究,扩展得到的温度场可以较为准确地反映南海北部温度剖面的结构特征,并且能有效地体现出一些中尺度变化过程。结果表明,本研究反演得到的三维温度扩展场是较为可靠的,它可以作为海洋数值模型的初始场,实现现场观测数据和卫星遥感数据的互补,有助于更好地分析南海北部温度场的三维结构及变化特征。  相似文献   

基于国家海洋治理和全球气候变化的我国海洋灾害防治          下载免费PDF全文

齐庆华 《海洋开发与管理》2019,36(2):17-23

为建立和完善现代化的海洋灾害防治体系,提高我国海洋治理和应对全球气候变化的能力,文章以全球治理和国家治理为背景,在明确致灾因子、承灾体、灾害以及灾害风险和管理等基本概念及其内涵的基础上,分析全球气候变化背景下我国海洋灾害及其风险的特征以及海洋灾害防治的关键性和基础性科学问题,并提出我国构建海洋灾害防治体系的建议。研究结果表明:在全球气候变化的影响下,我国沿海地区的海洋灾害风险复杂多变且有所提升;提出以群-环-域为主体的体系架构,研究全球气候变化与区域海洋的响应和反馈、全球气候变化背景下海洋灾害与风险的特征和规律以及综合海洋灾害风险评估和海洋灾害防治等问题;在我国构建海洋灾害防治体系的过程中,应加强科学研究以及技术和信息支撑、促进区域和全球联动联防以及提高全社会对海洋灾害的认知和防范水平。  相似文献   

Research on the Methods of Performance Monitoring and Evaluation for Active Hydrogen Maserstwo     

《Chinese Astronomy and Astrophysics》2019,43(2):292-304

Active hydrogen maser is the main frequency standard for establishing and maintaining the time scale. It has the characteristics of high short-term stability and low phase noise. At present, it plays an increasingly important role in the international atomic time (TAI) and various local time scales. Firstly, in combination with the internal state parameters of an active hydrogen maser, the correlation between the internal state parameters and the comparison data of a hydrogen maser is analyzed, and a method for the performance monitoring of a hydrogen maser is proposed. Secondly, according to the characteristics of hydrogen maser performance, a method for evaluating the performance of a hydrogen maser is given. The hydrogen maser performance includes mainly two aspects, namely the frequency stability and predictability. The performances of two types of active hydrogen masers (CH1-75 and MHM-2010) are evaluated by this method. The correlation analysis of the atomic clock state parameters and comparison data shows that the state parameter monitoring can effectively predict the variation of the hydrogen maser performance. The evaluation results of atomic clock frequency stability and predictability show that the atomic clock with a higher medium-and-long term frequency stability has a better predictability. There are two methods for the predictability evaluation, one is based on the data published by BIPM (Bureau International des Poids et Measures), and another one is based on the quadratic model. Both methods are consistent with the weights published by BIPM. Therefore, the two methods can be used as a quantitative method to evaluate the predictability of a hydrogen maser.  相似文献   

基于历史TLE的空间目标轨道预报误差演化规律研究     

许晓丽  熊永清 《天文学报》2019,60(4):26-38

北美防空司令部(North American Aerospace Defense Command, NORAD)发布的双行根数(Two Line Element, TLE)是广大航天工作者最常用的轨道根数,与其对应的轨道模型是SGP4/SDP4 (Simplified General Perturbation Version 4/Simplified Deep-space Perturbation Version 4)解析模型.由于TLE中并没有包含相应的轨道精度信息,编目轨道的应用范围受到很大的限制.基于Space-Track网站发布的历史TLE数据和配套的SGP4/SDP4动力学模型,采用定轨标预报的方法统计并生成了大量目标轨道的预报误差,通过对预报轨道的时间区间划分给出了每个目标的预报误差随预报时间变化的拟合系数,并进一步对不同类型轨道预报误差的演化规律和特征进行了分类讨论,给出了4种轨道类型目标的轨道预报误差随时间演化的平均解析模型,为拓展双行根数的应用提供有价值的参考.  相似文献   

Study of Star/Galaxy Classification Based on the XGBoost Algorithm     

《Chinese Astronomy and Astrophysics》2019,43(4):539-548

Machine learning has achieved great success in many areas today. The lifting algorithm has a strong ability to adapt to various scenarios with a high accuracy, and has played a great role in many fields. But in astronomy, the application of lifting algorithms is still rare. In response to the low classification accuracy of the dark star/galaxy source set in the Sloan Digital Sky Survey (SDSS), a new research result of machine learning, eXtreme Gradient Boosting (XGBoost), has been introduced. The complete photometric data set is obtained from the SDSS-DR7, and divided into a bright source set and a dark source set according to the star magnitude. Firstly, the ten-fold cross-validation method is used for the bright source set and the dark source set respectively, and the XGBoost algorithm is used to establish the star/galaxy classification model. Then, the grid search and other methods are used to adjust the XGBoost parameters. Finally, based on the galaxy classification accuracy and other indicators, the classification results are analyzed, by comparing with the models of function tree (FT), Adaptive boosting (Adaboost), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Stacked Denoising AutoEncoders (SDAE), and Deep Belief Nets (DBN). The experimental results show that, the XGBoost improves the classification accuracy of galaxies in the dark source classification by nearly 10% as compared to the function tree algorithm, and improves the classification accuracy of sources with the darkest magnitudes in the dark source set by nearly 5% as compared to the function tree algorithm. Compared with other traditional machine learning algorithms and deep neural networks, the XGBoost also has different degrees of improvement.  相似文献