A Model-Based Approach to Semi-Automated Reconstruction of Buildings from Aerial Images

Automated reconstruction of building objects from aerial images is a complex problem due to the diversity of buildings as well as noise and low contrast of images, which are the results of distant photography, atmospheric effects and poor illumination. In this paper, a semi-automated approach to the reconstruction of parametric building models from aerial images is presented, which works with line segments extracted from the image. The model is selected interactively from a library of parametric models. A perceptual grouping technique is used to select the most significant image lines in terms of relations such as proximity and parallelism. Model lines are searched for the same relations as in the grouped image lines, and the corresponding lines undergo a matching procedure, which determines whether or not a match can be found between the given model and image lines. An experiment with aerial images of flat-roof and gable-roof buildings is shown and its results indicate the robustness and efficiency of the proposed approach.     

2003年12月1日新疆昭苏6.1级地震烈度与房屋震害

介绍了2003年12月1日新疆昭苏6.1级地震的现场考察结果.该地震宏观震中位于受灾最重的兵团农四师76团11连西侧,极震区烈度为Ⅷ度;圈定出Ⅷ度、Ⅶ度和Ⅵ度3条等震线.此次考察还着重考察了震区各类典型建筑的受损特征,对受损原因作了初步分析,所取得的经验可供类似地区抗震设防和民房改造工作参考.     

Identification of structural parameters of multistorey shear buildings from modal data

A procedure has been presented in this paper to identify the structural parameters, viz. mass and stiffness matrices, from modal test data for multistorey shear buildings. The first two orders of modal data have been used by other researchers to estimate the global matrices where they depend only on measurable points which are less than the total number of structural degrees of freedom. The above method has been refined here by using Holzer criteria along with other numerical methods to estimate the global mass and stiffness matrices of the structure. This shows the methodology to be more efficient and accurate. The reliability of the procedure has been shown by examples of multistorey buildings. Copyright © 2004 John Wiley & Sons, Ltd.     

Three dimensional numerical simulation of residential building on shrink–swell soils in response to climatic conditions

Shrink–swell soils can cause distresses in buildings, and every year, the economic loss associated with this problem is huge. This paper presents a comprehensive system for simulating the soil–foundation–building system and its response to daily weather conditions. Weather data include rainfall, solar radiation, air temperature, relative humidity, and wind speed, all of which are readily available from a local weather station or the Internet. These data are used to determine simulation flux boundary conditions. Different methods are proposed to simulate different boundary conditions: bare soil, trees, and vegetation. A coupled hydro‐mechanical stress analysis is used to simulate the volume change of shrink–swell soils due to both mechanical stress and water content variations. Coupled hydro‐mechanical stress‐jointed elements are used to simulate the interaction between the soil and the slab, and general shell elements are used to simulate structural behavior. All the models are combined into one finite element program to predict the entire system's behavior. This paper first described the theory for the simulations. A site in Arlington, Texas, is then selected to demonstrate the application of the proposed system. Simulation results are shown, and a comparison between measured and predicted movements for four footings in Arlington, Texas, over a 2‐year period is presented. Finally, a three‐dimensional simulation is made for a virtual residential building on shrink–swell soils to identify the influence of various factors. Copyright © 2015 John Wiley & Sons, Ltd.     

超高层建筑GPS实时动态监测技术研究

在特高等级精密工程的测量范畴内,实现对超高层建筑的施工监测是一个非常重要的工作内容,GPS实时动态监测技术在监测中发挥着不可忽视的作用。本文首先对GPS监测技术做简要阐述,并分析了超高层建筑的特点;然后指出了GPS监测技术在施工监测中所发挥的作用;最后结合案例,具体分析了GPS监测技术在超高层建筑中的应用,以期为超高层建筑GPS实时动态监测技术的相关研究提供部分参考意见。     

基于 CCD 方法的超高层建筑周日摆动监测研究

对超高层建筑塔体进行周日摆动监测,为施工投点纠偏和选择合适投点时机提供科学依据,是施工控制网竖向传递的核心问题。文中针对现有方法在自动化采集及实时表达方面的不足,基于自适应阈值激光光斑中心定位方法,自主研发基于CCD的塔体摆动监测系统,并采用倾斜仪方法与之做同步比较研究。两种方法在广州市东塔施工第三方监测中互为检核验证,具有借鉴意义。     

塔里木溢流玄武岩火山通道的三维结构及其热成因气体释放

塔里木上奥陶统-志留系沉积地层中广泛发育早二叠世溢流玄武岩的火山通道相岩床-岩墙网络。三维地震数据解释结果显示,这些火山通道以平行围岩地层的岩床和斜切围岩地层的"碟状岩床"为主要特征。在玄武岩喷发过程中,火山通道岩浆的热量可以导致沉积围岩发生热接触变质并将沉积围岩中的有机质转化为"热成因气体"。在塔北英买2井区火山通道烘烤沉积围岩模型基础上,利用有限元热模拟方法确定了该区早二叠世玄武岩喷发时火山通道热烘烤影响范围随时间的变化。基于沉积围岩有机质丰度估算,该区热烘烤成因甲烷释放量可达11.3Gt(即113亿吨)。如果整个塔里木溢流玄武岩省具有与英买2地区相同的释放强度,则塔里木溢流玄武岩省活动期间释放的甲烷总量可达7062.5Gt,必然导致非常显著的环境效应。同时,玄武岩火山通道岩浆引起的热接触变质作用对已存在的油藏具有明显的破坏作用,塔里木盆地古生界总量约8~10Gt的油藏破坏和大量沥青的形成可能与此有关。     

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.     

基于逻辑回归的四川青川县区域滑坡灾害预警模型

四川省青川县滑坡灾害群发,点多面广,区域滑坡灾害预警是有效防灾减灾的重要手段,预警模型是成功预警的核心。由于研究区滑坡诱发机理复杂、调查监测大数据及分析方法不足等原因,传统区域地质灾害预警模型存在预警精度有限、精细化不足等问题。文章在青川县地质灾害调查监测和降水监测成果集成整理与数据清洗基础上,构建了青川县区域滑坡灾害训练样本集,样本集包括地质环境、降雨等27个输入特征属性和1个输出特征属性,涵盖了青川县近9年（2010—2018年）全部样本,数量达1 826个（其中,正样本613个,负样本1 213个）。基于逻辑回归算法,对样本集进行5折交叉验证学习训练,采用贝叶斯优化算法进行模型优化,采用精确度、ROC曲线和AUC值等指标校验模型准确度和模型泛化能力。其中,ROC曲线也称为“受试者工作特征”曲线;AUC值表示ROC曲线下的面积。校验结果显示,基于逻辑回归算法的模型训练结果准确率和泛化能力均较好（准确率94.3%,AUC为0.980）。开展区域滑坡实际预警时,按训练样本特征属性格式,输入研究区各预警单元27个特征属性,调用预先学习训练好的模型,输出滑坡灾害发生概率,根据输出概率分段确定滑坡灾害预警等级。当输出概率P≥40%且P<60%时,发布黄色预警;当输出概率P≥60%且P<80%时,发布橙色预警;当输出概率P≥80%时,发布红色预警。