资源三号卫星在区域地质灾害应急监测中的应用——以山西省为例

遥感技术已成为当前应对突发地质灾害应急监测的一种重要技术手段。本文将资源三号卫星遥感影像应用于区域地质灾害应急监测中,研究了资源三号卫星区域RPC参数的修正方法,并联合DEM和控制点建立了区域影像快速正射纠正的方法流程;利用长治地区的资源三号卫星影像进行了正射纠正试验与分析,总体满足区域地质灾害应急监测对遥感影像的精度要求。利用该方法制作完成的地质灾害区域遥感影像已应用于山西省突发地质灾害遥感监测指挥系统项目中并取得了较好的应用效果。     

UAV航测和TLS技术在广钢遗址测绘建模中的应用

联合应用地面三维激光扫描技术和无人机航测技术采集了广钢炼钢遗址空间数据,并进行了现状测绘与三维建模。三维激光扫描获取遗址内外高精度点云数据;无人机航测获取遗址顶部点云及周边地形DSM和DOM,将航摄DSM数据拟合到激光点云上,使得航摄DSM精度达到12.6cm,且弥补了激光点云的漏洞;采用融合的点云数据测制了平立剖测绘图,建立了三维模型。上述两种技术优势互补,形成了一种高效率、高精度、全方位的历史遗迹测量与建模的解决方案。     

情境建模下的LBS智能信息服务推送方法

为满足移动互联网用户的个性化信息服务需求,引入用户兴趣模型匹配技术,提出了一种基于情境建模下的LBS智能信息推送服务模式,通过构建位置过滤模块、用户兴趣模型匹配及智能信息分类模块,实现了对推送信息的层层过滤,并同时结合反馈处理部分的修正功能实时改进推送模型的精度,从而提高了信息服务的质量和效率,使推荐的信息资源更加符合用户的实际需要。原型系统的实际应用表明了该方法的有效性。     

开放式地理实体关系抽取的Bootstrapping方法

从网络文本中抽取地理实体间空间关系和语义关系要求高时效性和强鲁棒性。本文提出一种开放式地理实体关系的自动抽取方法,通过bootstrapping技术统计词语的词性、位置和距离特征来计算语境中词语权值,据此确定描述地理实体关系的关键词,最终组织成结构化实例,并使用百度百科和Stanford CoreNLP开展了试验。研究结果表明,本文方法能自动挖掘自然语言的部分词法特征,无须领域专家知识和大规模标注语料,适用于未知关系类型的信息抽取任务;较之经典的Frequency、TFIDF和PPMI频率统计方法,精度和召回率分别提升约5%和23%。     

井上下一体化三维信息管理与应急系统构建

基于构建的地质体和特殊构造的混合真实网格模型、巷道纹理自动添加及不同巷道交叉拼接技术,实现了集工业广场与井巷、地质体及采掘工作面于一体的井上下三维表达;利用多判据融合技术,研发了基于井下定位传感网的人员逃生避险线路规划与决策支持系统,实现了井下人员避灾疏散、逃生自救等功能。示范应用表明,该系统显著提高了煤矿安全生产管理与应急决策的信息化和科学化水平。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.     

智能手机音频信号与MEMS传感器的紧耦合室内定位方法

基于智能手机内置的传感器,开展了音频信号和MEMS传感器的紧组合室内定位研究.首先,将时频分析技术用于音频信号TOA估计,提出了一种基于短时傅里叶变换和优化互相关方法的两步估计方法.之后,研究了一种基于音频T DOA和行人航迹推算的紧组合定位算法,静态测试的平均定位精度为0.238 m,相比最小二乘方法提高了38.66...     

基于XML影像数据搜索算法的研究

从海量影像数据中查找所需数据是正射影像制作中的一个重要步骤,本文利用天绘影像提供的XML文件自动提取坐标信息,根据图号自动计算图幅角点坐标,研究了自动识别点和面位置关系的算法,实现了根据图号自动搜索天绘影像数据,根据天绘影像数据自动搜索参考影像数据的功能.     

地面激光扫描技术在建筑变形测量中的应用探讨

已有不少文献针对激光扫描在建筑变形测量中的应用进行了研究,但是国家和行业尚无三维激光扫描技术规程出台。本文通过应用调研、扫描仪的标称精度统计分析,以及具有针对性的试验,明确了激光扫描测量建筑变形的作业方法,确立了选用仪器精度、扫描测量的测回数、标靶入射角度等技术指标,为激光扫描技术在建筑变形测量中的工程应用提供了参考依据。