房产测量若干问题的解决方案

房产测量外业数据采集及面积计算是影响房产测量精度的重要因素,就实际工作中在这两个方面容易出现的问题提出了相应的解决方法。     

THE EXTRACTION OF HOUSE DISTRIBUTION BASED ON PHOTOGRAMMETRY METHOD:TAKING THE COUNTRYSIDE IN THE WEST OF CHINA FOR EXAMPLE

The key parameters of houses such as distribution, area and height play an important role for urban-rural planning, earthquake emergency and disaster mitigation. The computer automatic extraction method is an effective way to acquire large area house information using satellite-borne or airborne optical remote-sensing images. However, because of the similarity of spectral characters for different land cover types or the influence of snow coverage, the classification accuracy of house type using traditional spectral based method can be decreased. To acquire the accurate houses distribution, a method based on the height information is proposed using unmanned aerial vehicle(UAV)in this study. With UAV flying at the height of 100m above ground, the route of the UVA was planned with the heading direction overlap of 77% and side direction overlap of 50%for the nearby pictures. Taking Qionghalajun Village in Xinjiang Uygur Autonomous Region for example, 69 pictures of the study area were obtained with DJI Phantom 3 professional. With those pictures input into the EasyUAV software, the Digital Elevation Model(DEM), Digital Surface Model(DSM), and Digital Orthophoto Map(DOM)were acquired based on photogrammetry method using the overlapped optical remote-sensing images of UAV. After that, the house distribution and height were acquired with the differences between DSM and DEM images larger than 2.6m. To eliminate the influences of disintegrated pixels on the house extraction, mainly caused by the trees or noise point, the classification aggregation tool of ENVI software was used with the disintegrated pixels' area less than 4m². Compared with visual interpretation result, the user accuracy and mapping accuracy of the house extraction method proposed in this study is 88.69% and 97.42%, respectively. In addition, to evaluate the performance of the proposed method, the result of traditional supervised classification method using DOM data acquired previously was compared with the result of new method. The results show that the new method is more accurate the user accuracy and mapping accuracy of the supervised classification method, which is 43.23% and 85.30%, respectively. Besides the study area in this study, the performance of the proposed method will be evaluated at the other places in the further study.     

STUDY ON THE MRF-BASED METHOD FOR DAMAGED BUILDINGS EXTRACTION FROM THE SINGLE-PHASE SEISMIC IMAGE

Earthquake events are one of the most extraordinarily serious natural calamities, which not only cause heavy casualties and economic losses, but also various secondary disasters. Such events are devastating, and have far-reaching influences. As the main disaster bearing body in earthquake, buildings are often seriously damaged, thus it can be used as an important reference for earthquake damage assessment. Identifying damaged buildings from post-earthquake images quickly and accurately is of real importance, which has guidance meaning to rescue and emergency response. At present, the assessment of earthquake damage is mainly through artificial field investigation, which is time-consuming and cannot meet the urgent requirements of rapid emergency response. Markov Random Field(MRF)combines the neighborhood system of pixels with the prior distribution model to effectively describe the dependence between spatial pixels and pixels, so as to obtain more accurate segmentation results. The support vector machine(SVM)model is a simple and clear mathematical model which has a solid theoretical basis; in addition, it also has unique advantages in solving small sample, nonlinear and high-dimensional pattern recognition problems. Thus, in this paper, a Markov random field-based method for damaged buildings extraction from the single-phase seismic image is proposed. The framework of the proposed method has three components. Firstly, Markov Random Field was used to segment the image; then, the spectral and texture features of the post-earthquake damaged building area are extracted. After that, Support Vector Machine was used to extract the damaged buildings according to the extracted features. In order to evaluate the proposed method, 5 areas in ADS40 earthquake remote sensing image were selected as experimental data, this image covers parts of Wenchuan City, Sichuan Province, where an earthquake had struck in 2008. And in order to verify the applicability of this method to different resolution images, an experimental area was selected from different resolution images obtained by the same equipment. The experimental results show that the proposed method has good performance and could effectively identify the damaged buildings after the earthquake. The average overall accuracy of the selected experimental areas is 93.02%. Compared with the result extracted by the widely used eCognition software, the proposed method is simpler in operation and can improve the extraction accuracy and running time significantly. Therefore, it has significant meaning for both emergency rescue work and accurate disaster information providing after earthquake.     

墙体开洞影响下房屋砖砌体结构地震易损性分析

为获取可靠的墙体开洞影响下房屋砖砌体结构地震易损性分析结果,采用ABAQUS有限元分析软件构建房屋砖砌体结构墙体模型,设置合理的墙体模型参数和数值模拟参数;对比模拟数值与以往研究的测试值,证明所构建模型参数取值合理;将截取的峰值段江油地震波作为上述模型的地震动输入,根据测得的房屋砖砌体结构的力学变化数据,分析房屋砖砌体结构的地震易损性。分析结果表明:地震情况下,随着墙体开洞率的增加,墙体荷载能力下降、墙体水平承载力增长幅度降低、墙体相对刚度退化率增加;墙体开洞数量越多,房屋砖砌体结构侧向刚度下降越快。因此分析得出墙体开洞率大、墙体开洞数量多,房屋砖砌体结构的地震易损性越显著。     

木构架承重-空斗墙围护民居抗震加固振动台试验研究

木构架承重-空斗墙围护民居大量分布在我国南方农村地区,该类民居整体性较差,历次地震中该类民居破坏较严重。采取高延性混凝土ECC面层加固围护空斗墙,扁钢、角钢及薄钢板增强木构架节点,穿墙钢筋捆绑木构架与围护墙体等加固措施。设计了1/2缩尺模型进行振动台试验,通过调整输入地震波峰值加速度来考虑不同水准地震烈度,分析了围护空斗墙损伤,探讨了模型频率与阻尼比变化特性,对比了围护空斗墙体与木构架加速度放大系数和位移包络值,并验证了二者在地震中的变形协调性。试验结果表明:（1）围护墙体仅在外侧出现明显裂缝,内侧ECC面层与墙体始终未脱离且未出现裂缝,围护墙整体性仍可得到一定保障;（2）木构架与钢加固件连接部位仅发生轻微破坏,木构架没有出现明显损伤;（3）木构架与围护墙体之间出现滑移,整体上二者协同抗震变形性能良好。该系列措施的加固效果较理想,适用于该类民居的抗震加固。     

汶川地震应急监测评估方法研究

以汶川地震灾害应急遥感监测评估过程为例,介绍了利用遥感技术等手段对巨灾灾情进行应急监测评估的技术方法,并重点对四川、陕西和甘肃3省受灾较重的152个县(市、区)进行了应急评估.结果表明,汶川地震房屋倒损严重,受灾人口分布点多面广,受灾程度总体上与断裂带分布呈明显对应关系,山区受灾重于平原,农村重于城镇.四川省汶川、北川、青川、绵竹等12个县(市、区)受灾极为严重,甘肃省文县和陕西省勉县等受灾相对较重,利用地面调查数据验证,证明了评估结果具有较高的准确性.提出了基于遥感数据研判、空间分析外推技术的自下向上、逐级汇总的应急评估技术路线,能够发挥遥感数据的优势,也能保证应急评估的时效性,同时有利于组织大规模协同运行与综合结果生成,具有良好的科学性和可操作性,特别适合于巨灾灾情遥感应急评估工作.     

花卉塑料大棚降温效果分析

本文对花卉塑料大棚夏季降温试验进行了分析,结果表明:采用直接阻挡太阳辐射的降温方法、棚膜外或棚膜内地面喷水的降温方法,其降温效果均好。这为成都地区花卉塑料大棚周年生产的科学管理提供了依据。     

对GZRS房产测绘系统分摊模式的探讨

结合实际工作对广州市房产面积测算目前使用的GZRS绘图系统的分摊模式进行了详细的分析,说明了只有正确理解各个分摊模式的概念,才能使测量成果质量得到保证。     

房屋共有建筑面积分摊模型的优化设计与实现

本文从共有建筑面积分摊模型入手,明确了异产毗邻房屋中功能区、共有建筑面积的概念和确认方法,阐述了其分摊过程中的逻辑关系,为房屋共有建筑面积的分摊计算提供了新的思路。     

某核电站循环水泵房结构的地震反应分析

文中运用动力时程反应分析方法,针对某百万千瓦级核电厂,利用Ansys对循环水泵房结构进行了抗震分析。针对循环水泵房结构场地岩性、结构特点,分别考虑不同设计水位、运行和检修情况、波浪压力、静动水压力和土压力以及地震荷载的组合工况,对结构进行了抗震性能计算分析,得到结构构件各个截面上内力包络,该成果对循环水泵房结构设计具有参考价值和指导意义。