基于双张影像的城市建筑物高度提取方法

针对现有城市建筑物高度提取方法存在的问题,提出一种基于双张影像的城市建筑物高度简易提取方法。利用高分辨率遥感影像和建筑物立面影像,分别提取样本建筑物的阴影长度和高度,采用最小二乘法解算出影像阴影和建筑物高度的相关公式,通过阴影长度反算出建筑物的高度,从而实现大批量建筑物高度数据的获取。通过建模实例和测量对比实验表明,方法具有操作简单、快速的特点,能满足较高的精度要求,具有一定的应用价值。     

基于MapStar软件在作业应用中的问题探讨

MapStar软件是在数字摄影测量的基础上进行采集、编绘及属性建库;达到了建库与出图并举,基本上实现了生产一体化的作业过程。着重分析了建库数据的质量检查、修改等质量管理工作,为完善MapStar软件提出了建议。     

Results of the ISPRS benchmark on urban object detection and 3D building reconstruction

For more than two decades, many efforts have been made to develop methods for extracting urban objects from data acquired by airborne sensors. In order to make the results of such algorithms more comparable, benchmarking data sets are of paramount importance. Such a data set, consisting of airborne image and laserscanner data, has been made available to the scientific community by ISPRS WGIII/4. Researchers were encouraged to submit their results of urban object detection and 3D building reconstruction, which were evaluated based on reference data. This paper presents the outcomes of the evaluation for building detection, tree detection, and 3D building reconstruction. The results achieved by different methods are compared and analysed to identify promising strategies for automatic urban object extraction from current airborne sensor data, but also common problems of state-of-the-art methods.     

A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds

In the task of 3D building model reconstruction from point clouds we face the problem of recovering a roof topology graph in the presence of noise, small roof faces and low point densities. Errors in roof topology graphs will seriously affect the final modelling results. The aim of this research is to automatically correct these errors. We define the graph correction as a graph-to-graph problem, similar to the spelling correction problem (also called the string-to-string problem). The graph correction is more complex than string correction, as the graphs are 2D while strings are only 1D. We design a strategy based on a dictionary of graph edit operations to automatically identify and correct the errors in the input graph. For each type of error the graph edit dictionary stores a representative erroneous subgraph as well as the corrected version. As an erroneous roof topology graph may contain several errors, a heuristic search is applied to find the optimum sequence of graph edits to correct the errors one by one. The graph edit dictionary can be expanded to include entries needed to cope with errors that were previously not encountered. Experiments show that the dictionary with only fifteen entries already properly corrects one quarter of erroneous graphs in about 4500 buildings, and even half of the erroneous graphs in one test area, achieving as high as a 95% acceptance rate of the reconstructed models.     

Change detection on LOD 2 building models with very high resolution spaceborne stereo imagery

Due to the fast development of the urban environment, the need for efficient maintenance and updating of 3D building models is ever increasing. Change detection is an essential step to spot the changed area for data (map/3D models) updating and urban monitoring. Traditional methods based on 2D images are no longer suitable for change detection in building scale, owing to the increased spectral variability of the building roofs and larger perspective distortion of the very high resolution (VHR) imagery. Change detection in 3D is increasingly being investigated using airborne laser scanning data or matched Digital Surface Models (DSM), but rare study has been conducted regarding to change detection on 3D city models with VHR images, which is more informative but meanwhile more complicated. This is due to the fact that the 3D models are abstracted geometric representation of the urban reality, while the VHR images record everything. In this paper, a novel method is proposed to detect changes directly on LOD (Level of Detail) 2 building models with VHR spaceborne stereo images from a different date, with particular focus on addressing the special characteristics of the 3D models. In the first step, the 3D building models are projected onto a raster grid, encoded with building object, terrain object, and planar faces. The DSM is extracted from the stereo imagery by hierarchical semi-global matching (SGM). In the second step, a multi-channel change indicator is extracted between the 3D models and stereo images, considering the inherent geometric consistency (IGC), height difference, and texture similarity for each planar face. Each channel of the indicator is then clustered with the Self-organizing Map (SOM), with “change”, “non-change” and “uncertain change” status labeled through a voting strategy. The “uncertain changes” are then determined with a Markov Random Field (MRF) analysis considering the geometric relationship between faces. In the third step, buildings are extracted combining the multispectral images and the DSM by morphological operators, and the new buildings are determined by excluding the verified unchanged buildings from the second step. Both the synthetic experiment with Worldview-2 stereo imagery and the real experiment with IKONOS stereo imagery are carried out to demonstrate the effectiveness of the proposed method. It is shown that the proposed method can be applied as an effective way to monitoring the building changes, as well as updating 3D models from one epoch to the other.     

古建筑测绘成果管理系统设计与实现

本文以古建筑档案管理工作需求为基础,兼顾古建筑展示需要,介绍了基于Flex开发的南通市文保单位及历史建筑管理信息系统。重点介绍了系统的设计原理和具体实现方法。结果表明该系统可较好地管理古建筑测量数据,展示古建筑测绘成果。     

房屋测量常见问题及解决方式探讨

房屋测量技术能为房屋提供准确的数据,和我们的日常生活息息相关。本文就房屋测量中常见的问题及解决方式进行阐述。     

“地、楼、房”一体化建库技术研究

房地一体化是土地管理和房屋管理信息化的一个重要思路。从数据层面来看,房地一体化应当是土地、楼栋和房屋的一体化。本文在对广州市地、楼、房建设试点实践的基础上,总结了地、楼、房一体化建库所需要的原始数据资料、建库的流程和方法,并对建库的关键技术和要点进行了分析。     

Geometric structure simplification of 3D building models

The complexity of building models directly affects the application efficiencies of 3D urban maps. To address the challenges of building models with various structures, we propose a structural simplification method in this paper. The geometric structures of building models are classified into three categories: embedded structures, compositional structures, and connecting structures, which can be extracted separately through convex/concave analysis. Some specific rules are proposed for the simplification of geometric structures, and the building models are suggested to be simplified progressively. The robustness and efficiency of the method are demonstrated by experiments, and the applications of the Levels of detail of the building models are illustrated.     

利用机载LiDAR点云提取复杂城市建筑物面域

机载LiDAR技术为探测建筑物提供了大量三维点云坐标.为了能从植被中有效识别建筑物面域,首先利用渐进式TIN加密法识别非地面点云,经过移除低于地面3 m的点云和孤立点云后生成菲地面点云的二值化格网,依据自定义的分割算子打断建筑物和植被间的可能连接;然后通过区域生成算法以高差阈值来聚类二者的面域,并使用大坡度密度阈值来提取建筑物的面域;最后使用形态学闭算子填充面域孔洞并平滑其边缘.选取3个典型的复杂城市区域进行测试,结果显示,各区域的提取质量与完成率均高于91％,表明该算法能够达到自动识别建筑物的目的.