基于Sentinel-1和D-InSAR的地表沉降地理国情监测技术研究

为推进合成孔径雷达差分干涉测量(D-InSAR,Differential Interferometric Synthetic Aperture Radar)技术在地表沉降地理国情监测中的应用,本文利用D-InSAR技术,以某矿区为研究对象,基于5景哨兵-1卫星(Sentinel-1)雷达影像,采用SARscape与Arc GIS软件相结合处理的方式得到了精准的成果数据,并结合实地水准观测结果对D-InSAR地表沉降监测的精度进行了对比分析。结果表明:利用D-InSAR技术进行地表沉降地理国情监测,具有较高的测量精度,且该技术具有大尺度连续覆盖能力、受天气干扰小、低成本等特点,在地理国情监测等相关领域有非常好的应用前景。     

基于多种测绘装备协同工作在白河滑坡灾害中的应用

无人机低空摄影测量技术在应对各类地质灾害方面有着明显优势。本文以安康市白河县茅坪镇山体滑坡灾害为例,介绍了灾害应急中两大无人机系统以及IBIS微形变监测设备所发挥的巨大作用,阐述了无人机飞行设计、现场快速影像处理技术、灾区三维模型构建技术以及潜在危险区域形变量实时监测,并通过获取的数据成果对灾情进行了分析。     

商业房产共用面积分摊模型的研究

针对房产测绘中复杂商业房产分摊数据计算量大、分摊对象不明确易产生纠纷的问题,本文在传统的房产共用面积分摊模型的基础上,提出了改进的共用面积分摊模型。该模型灵活地应用功能区的概念,将功能和用途都不同的套内面积整合在一起,合并成为一个功能区,有效地解决了复杂房产分摊问题,在复杂房产分摊方面较传统模型大大减少了数据计算量,可以更加直观地体现出共用面积的服务对象。     

SAGE测光巡天数据处理方法研究

元素丰度与星系演化(Stellar Abundance and Galactic Evolution,SAGE)是自主设计的能够准确计算恒星大气参数以及消光的新测光系统。对北天除银盘外共计约12 000 deg2的天区开展了SAGE系统测光巡天,计划获取约5亿颗恒星的高精度测光数据。单次曝光条件下100σ完备星等uSC～17. 3,vSAGE～16. 8(AB星等),这些为研究银河系提供宝贵的测光资料。介绍了巡天专用的数据处理程序的研究和开发,主要研究了针对单幅图像的快速自动化处理过程,重点介绍数据改正、天体测量校正、测光和流量定标过程,以及数据结果和数据质量检测等。     

基于容器技术的天文应用软件自动部署方法

平方千米阵列即将开始建设,各子工作包也进入关键设计评估阶段。基于云与容器技术是平方千米阵列科学数据处理器未来可能采用的平台技术。针对超大规模海量数据处理面临的天文应用软件快速部署、运行与实测要求,充分考虑天文应用软件运行环境复杂、云计算环境下超大规模计算集群部署困难等问题,系统研究并给出了一种使用容器技术的天文应用软件通用自动部署方法。以目前较为常用的可见度函数校准软件SAGECaL为例,首先分析了SAGECaL的相关特性和分布式部署方面存在的困难,进而给出了基于容器技术的SAGECaL分布式集群的自动部署方法。实验结果表明,自动部署方法极大地提高了SAGECaL分布式集群的部署效率,满足项目组承担平方千米阵列科学数据处理器相关测试工作所需要的基础平台部署与切换等需求,同时也为其它天文软件在云端的快速部署与执行提供了有益的思路。     

Test area of the SAGE survey

Sky surveys represent one of the most important efforts to improve developments in astrophysics,especially when using new photometric bands. We are performing the Stellar Abundance and Galactic Evolution(SAGE) survey with a self-designed SAGE photometric system, which is composed of eight photometric bands. The project mainly aims to study the stellar atmospheric parameters of ～0.5 billion stars in ～12 000 deg2 of the northern sky, which mainly focuses on Galactic astronomy, as well as some aspects of extragalactic astronomy. This work introduces the detailed data reduction process of the test field NGC 6791, including the data reduction of single-exposure images and stacked multi-exposure images, and properties of the final catalog.     

A PCA approach to stellar abundances I. testing of the method validity

The derivation of element abundances of stars is a key step in detailed spectroscopic analysis. A spectroscopic method may suffer from errors associated with model simplifications. We have developed a new method of deriving the various element abundances of stars based on the calibration established from a group of standard stars. We perform principal component analysis(PCA) on a homogeneous library of stellar spectra, and then use machine learning to calibrate the relationship between principal components and element abundances. By testing with spectral libraries S4 N and MILES, we find that our procedure provides good consistency when spectra from a homogeneous set of observations are used, and it could be expanded to stars with quite a wide range of stellar parameters, with both dwarfs and giants. Moreover, we discuss the four key factors that have a significant impact on the results of derived element abundances,including the resolution of the spectra, wavelength range, the signal-to-noise ratio(S/N) of spectra and the number of principal components adopted.     

Low-mass and high-mass supermassive black holes in radio-loud AGNs are spun-up in different evolution paths

How supermassive black holes(SMBHs) are spun-up is a key issue in modern astrophysics. As an extension to the study in Wang et al., here we address the issue by comparing the host galaxy properties of nearby(z 0.05) radio-selected Seyfert 2 galaxies. With the two-dimensional bulge+disk decompositions for the SDSS r-band images, we identify a dichotomy in various host galaxy properties for radio-loud SMBHs. By assuming that radio emission from the jet reflects a high SMBH spin, which stems from the well-known Blandford-Znajek mechanism of jet production, high-mass SMBHs(i.e., MBH 107.9 M⊙)have a preference for being spun-up in classical bulges, and low-mass SMBHs(i.e., MBH = 106-107 M⊙)in pseudo-bulges. This dichotomy suggests and confirms that high-mass and low-mass SMBHs are spun-up in different ways, i.e., a major "dry" merger and a secular evolution respectively.     

深度卷积神经网络支持下的遥感影像飞机检测

针对YOLOv3算法对小目标检测较差及出现较多漏检的问题,本文提出了一种优化的YOLOv3算法.首先使用K-means算法计算出与数据集相适用的锚框;其次将扩张卷积引入到YOLOv3网络,用来增强网络高层的感受野,改善小目标的检测效果;然后使用深度可分离卷积取代YOLOv3网络残差模块中的普通卷积,可减少计算量,从而得到一种新型卷积神经网络结构;最后在数据集上进行对比试验.结果表明,优化的YOLOv3算法能够检测出更多目标,降低漏检率,相比于YOLOv3算法,其召回率提高11.86%,F1-score提高2.99%.     

基于GPS新型L5信号的地表雪深反演研究

利用GPS多路径反射信号测量地表雪深具有全天候和高时空分辨率的特点,因此其可作为一种代替气象站监测雪深的新手段。然而,先前大多数研究仅使用了GPS L1和L2C波段信噪比数据探测积雪深度。为验证新型的L5信号在雪深反演方面的优越性,本文阐述了GPS-R技术反演雪深的原理,利用Lomb-Scargle周期图法所处理的受积雪表层影响的信噪比数据计算了频谱振幅强度,通过获取频谱特征值与天线高度的关系求解雪深值,最后分别与L1反演结果和实测雪深数据进行了对比。试验结果表明：与现有的GPS-R测量雪深结果相比,利用新型的L5反射信号反演地表雪深的精度更佳;采用GPS-R技术探测雪深对把握测站区域内的雪深变化情况和淡水资源储量具有重要价值。