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Thesis Advisor陈曦 ; 杨辽
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline测绘工程
Keyword建筑物三维信息提取 数据滤波 建筑物表面模型 容积率
Abstract点云是在同一空间坐标系下表达目标空间分布和表面特性的海量点的集合。倾斜航空影像密集匹配生成的点云数据与LiDAR(Light Detection and Ranging,LiDAR)点云数据相似,均包含地物的三维坐标信息。与后者相比,前者不包含多次回波信息和回波强度信息,但成本远低于后者。如何从点云数据中获取感兴趣地物如建筑物等的三维模型是目前国内外研究的热点问题。由于航空影像密集匹配点云数据中存在噪声和树木遮挡,故利用其生成的三维模型存在边缘模糊和边界矛盾表达等问题。而且目前大多数航空摄影测量数字产品的制作到DSM、4D产品以及三维模型就截止,很少有进一步的分析。基于此,本论文对如何优化倾斜影像点云数据生成无边界模糊和表达矛盾等问题做出了研究,并进一步利用建筑物屋顶三维信息估算研究区内不同区域的容积率。 本文以吐鲁番市区以及周围约150平方公里倾斜航空密集匹配生成的点云数据为研究对象,针对点云数据存在较多噪声和不感兴趣地物如树木、汽车等,分析了点云数据分割和分类的区别与联系、建筑物提取的几种方法和主要的数据滤波方法,研究了如何利用航空影像密集匹配点云数据的特征生成不存在边界模糊和其他地物干扰的城市建筑物数字表面模型,另外基于建筑物屋顶三维信息估算城市不同区域的容积率。主要取得以下进展: (1)提取建筑物屋顶三维信息。建筑物的屋顶三维信息包括高度信息和面积信息。通过计算nDSM的坡向图和坡度图,获取每个像元的坡度值,加上高度阈值、纹理信息、形状阈值的限制,获取潜在建筑物区域。利用最小二乘平面拟合法获得屋顶平面,最后利用类似K-means方法优化建筑物边界,生成优化后的准确建筑物边界。与几种传统的边缘检测算子提取出的建筑物边界进行对比,发现后者易受到各种其他地物的干扰,将各种地物的边缘全部检测出来。通过将点云数据和拟合屋顶平面结合显示,结合角点高程定性对比,本文方法得到的建筑物三维信息具有较高的平面和高程精度。 (2)BDSM(Building Digital Surface Model,BDSM)生成。利用逐点内插法,生成DEM的无约束D-三角网。以提取的建筑物边界为约束边,将其嵌入DEM生成的无约束D-三角网,生成约束D-三角形。用建筑物边界裁剪点云数据生成的无约束D-三角网,得到仅含建筑物区域的三角网,最终将建筑物三角网和地面约束D-三角网拼合,生成边界清晰和准确BDSM。 (3)城市容积率计算。利用得到的建筑物屋顶三维信息,结合不同地块面积,计算研究区内不同地块容积率。与研究区实际对比分析,估算结果符合城市建筑物分布规律。与阴影法相比,本文的研究方法精度更高。 本文着重于点云优化生成城市建筑物表面模型和城市容积率的提取,对进一步精确建筑物模型生成有一定意义,可以为城市建设和规划部门提供更快速的数据显示和更新方式,有一定的理论和实践意义。
Other AbstractPoint cloud is a collection of mass points that express target spatial distribution and surface properties in the same space coordination. Point cloud generated by density matching of oblique aerial images is similar with point cloud from LiDAR(Light detection and Ranging, LiDAR), both of which include three-dimensional coordinates information of features. Compared with the latter, the former doesn’t contain the information of multi-echoes and echo intensity, but its cost is much lower than the latter. It is a hot issue in current research how to gain interesting features’ three-dimension model, for instance buildings, from point cloud. Due to noise and tree blocks in point cloud from oblique aerial images, three-dimension coming from them have problems such as the blur edges and contradictory expression of boundaries and so on. Besides most of digital productions of aerial photography currently stop at DSM,4D production and the three-dimension model buildings, there is little further analysis. Based on this, how to optimize point cloud from oblique aerial images to generate models with obvious edges and logical boundaries is studied in this thesis, further research was done to estimate floor area ratio of different regions in study area using three-dimension information of building roofs. The research object is point cloud from oblique aerial images around Turpan city of which the area is about 150 kilometer, against where there are much noise and uninteresting features like trees and cars, this paper analyze the difference and contact between segmentation and classification of point cloud, several methods to extract buildings and main ways of data filters, study how to product building digital surface model of cities, which get rid of blur edges and disturbing from other features, making use of characteristics of point cloud from oblique aerial images. In addition, based on the three-dimension information of building roofs, floor area ratio of different regions in city is estimated. The main study works are as follows: (1) Extraction of three-dimension information of building roofs. Three-dimension information of building roofs includes height and area information. Potential building areas are gained through slope value by calculating aspect image and slope image of nDSM(normalized Digital Surface Model, nDSM), affiliating constrains of height threshold, texture information and shape threshold. Roof planes are gained in advantage of least-squares fitting plane. Finally K-means is used to optimize building boundaries, producing accurate building boundaries. Compared to the result of several traditional edge detectors, the latter is disturbed by all kinds of other features whose edges are detected. Through combination showcase of point cloud and fitting roof planes, quantitative comparison combining corner height, method in this paper has higher horizontal and elevation accuracy in three-dimension information of building. (2) Produce of BDSM(Building Digital Surface Model, BDSM).Unconstrained D-triangulation of DEM(Digital Elevation Model, DEM) is generated by method of point-to-point interpolation. Considering the extracted building boundaries as the constrained edges, embedding them into unconstrained D-triangulation, we get constrained D-triangulation. Triangulations only covering building areas gained through cutting out DSM-triangulation by edges of buildings. In the end BDSM with obvious edges can be got by combining triangulation of building with unconstrained triangulation of DEM. (3) Calculation of floor area ratio of city. Floor area ratio of different regions in study area is calculated with three-dimension information and area of different districts. The experimental result, which is in line with the distribution regulation, compared to shadow –based method, has a higher accuracy through field-proven. This paper focuses on the BDSM through optimizing of point cloud and extraction of city’s floor area ration, which are of importance to further build of accurate building model. The work done in this paper offers a more rapid way to display and update data for urban construction and planning department, which has a certain meaning both theoretically and practically.
Subject Area测绘工程
Document Type学位论文
Recommended Citation
GB/T 7714
赵翠哓. 倾斜摄影点云数据优化与容积率估算[D]. 北京. 中国科学院大学,2016.
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