基于三维激光扫描仪的校园建筑物建模研究

三维激光扫描仪可以连续、自动、快速获取目标物表面的采样点数据。论述三维激光扫描仪工作原理、数据处理流程。以校园建筑物为例,给出三维数据获取、数据处理、模型建立的基本方法和结果。探讨采用点云数据进行数字校园的方法。     

不同激光扫描数据组拼接的一种新方法

激光扫描测量技术在三维城市建模领域的应用具有良好的发展前景。但是,不同精度的扫描数据组的拼接是目前需要解决的主要问题之一,本文对不同精度的数据组的拼接进行了实验性研究,并提出了一种新方法。     

三维激光扫描仪平缓地形分区扫描方法研究

三维激光扫描仪对平缓地形扫描作业时,存在点密度不均匀、冗余数据多、有效扫描半径小等限制。为减少上述限制,提高作业效率,在深入分析三维激光扫描仪工作原理的基础上,提出分区扫描方法:根据到扫描仪中心距离的不同,将扫描范围分为若干环状区域,每个环状区域分别对应不同的竖直扫描夹角,各区域基于扫描点密度均衡的原则,设置不同的扫描参数。试验结果表明:竖直扫描角度分别为88°~89°、85°~88°、70°~85°、45°~70°的分区扫描方法为较理想的方法,与整体扫描方式相比,前者在作业效率、有效扫描半径等方面均有明显优势,数据点密度分布得到很大改善,利用效率明显提高。     

A shape-based segmentation method for mobile laser scanning point clouds

Segmentation of mobile laser point clouds of urban scenes into objects is an important step for post-processing (e.g., interpretation) of point clouds. Point clouds of urban scenes contain numerous objects with significant size variability, complex and incomplete structures, and holes or variable point densities, raising great challenges for the segmentation of mobile laser point clouds. This paper addresses these challenges by proposing a shape-based segmentation method. The proposed method first calculates the optimal neighborhood size of each point to derive the geometric features associated with it, and then classifies the point clouds according to geometric features using support vector machines (SVMs). Second, a set of rules are defined to segment the classified point clouds, and a similarity criterion for segments is proposed to overcome over-segmentation. Finally, the segmentation output is merged based on topological connectivity into a meaningful geometrical abstraction. The proposed method has been tested on point clouds of two urban scenes obtained by different mobile laser scanners. The results show that the proposed method segments large-scale mobile laser point clouds with good accuracy and computationally effective time cost, and that it segments pole-like objects particularly well.     

Automated matching of multiple terrestrial laser scans for stem mapping without the use of artificial references

Terrestrial laser scanning has been widely used to analyze the 3D structure of a forest in detail and to generate data at the level of a reference plot for forest inventories without destructive measurements. Multi-scan terrestrial laser scanning is more commonly applied to collect plot-level data so that all of the stems can be detected and analyzed. However, it is necessary to match the point clouds of multiple scans to yield a point cloud with automated processing. Mismatches between datasets will lead to errors during the processing of multi-scan data. Classic registration methods based on flat surfaces cannot be directly applied in forest environments; therefore, artificial reference objects have conventionally been used to assist with scan matching. The use of artificial references requires additional labor and expertise, as well as greatly increasing the cost. In this study, we present an automated processing method for plot-level stem mapping that matches multiple scans without artificial references. In contrast to previous studies, the registration method developed in this study exploits the natural geometric characteristics among a set of tree stems in a plot and combines the point clouds of multiple scans into a unified coordinate system. Integrating multiple scans improves the overall performance of stem mapping in terms of the correctness of tree detection, as well as the bias and the root-mean-square errors of forest attributes such as diameter at breast height and tree height. In addition, the automated processing method makes stem mapping more reliable and consistent among plots, reduces the costs associated with plot-based stem mapping, and enhances the efficiency.     

Correction of laser scanning intensity data: Data and model-driven approaches

Most airborne and terrestrial laser scanning systems additionally record the received signal intensity for each measurement. Multiple studies show the potential of this intensity value for a great variety of applications (e.g. strip adjustment, forestry, glaciology), but also state problems if using the original recorded values. Three main factors, a) spherical loss, b) topographic and c) atmospheric effects, influence the backscatter of the emitted laser power, which leads to a noticeably heterogeneous representation of the received power. This paper describes two different methods for correcting the laser scanning intensity data for these known influences resulting in a value proportional to the reflectance of the scanned surface. The first approach – data-driven correction – uses predefined homogeneous areas to empirically estimate the best parameters (least-squares adjustment) for a given global correction function accounting for all range-dependent influences. The second approach – model-driven correction – corrects each intensity independently based on the physical principle of radar systems. The evaluation of both methods, based on homogeneous reflecting areas acquired at different heights in different missions, indicates a clear reduction of intensity variation, to 1/3.5 of the original variation, and offsets between flight strips to 1/10. The presented correction methods establish a great potential for laser scanning intensity to be used for surface classification and multi-temporal analyses.     

Precise, automatic and fast method for vanishing point detection

A new automated approach for vanishing point detection in images of urban scenes is described. This method is based on the theorem of Thales. The main contribution of this paper is the automatic and simultaneous detection of all vanishing points of the image, achieved by converting this problem into the detection of circles in a complex cloud of points, in which each point corresponds to a segment and is associated with an uncertainty. This extraction of circles uses a RANSAC method, modified to improve its speed by using accumulation techniques (Hough transform or otherwise). This robust estimation is then refined by least squares error propagation using the individual variances of each segment. The algorithm is robust, its accuracy is optimised and it is entirely automatic. Its successful operation has been tested on a large number of images of varied urban scenes.     

支持向量机的建筑物激光脚点提取方法

本文提出了一种基于全色波段航空影像和激光雷达数据的建筑物检测方法.如何从激光点云数据中提取出建筑物激光脚点,是建筑物三维重建和轮廓提取的难点问题之一.植被密集区域以及与建筑物紧密相邻的树木的激光点很难与建筑物激光点区分开.本文利用支持向量机对单个激光点的特征进行两分类,特征向量包括激光点的高程、高程变化信息以及与激光点...     

基于三维激光扫描数据的构筑物三角构网模型

三维激光扫描可以快速获得表面物体的三维空间的点云数据,但其数据量比较大,此外要利用这些点云数据表示构筑物表面,还需要建立表面数学模型。首先分析了激光扫描数据的采集原理和数据基本特点,具体给出了表面平面三角网生长算法,在此模型的基础上,利用三角形构成面后法线间夹角为判断依据,提出了空间三角构网的模型,并针对数据的复杂性和物体表面的不规则性,提出空间分区三角构网的方法,并以同济大学孔子头像为例给出了具体的实现方法。     

基于机载激光扫描数据提取建筑物的研究现状

机载激光扫描系统是集成了GPS、惯性导航系统(INS)和扫描激光测距系统并利用飞机作为运行平台,来获取地面的三维位置,进而快速生成数字表面模型(DSM)。随着机载扫描激光测距系统的不断完善和发展,获取城市DSM数据也变得越来越快速,而且方便和经济可靠,地面激光点的密度也大大提高。目前国外激光扫描系统的激光点密度一般都达到了1～20点/m2,因此利用机载激光扫描系统获取的城市DSM提取建筑物也渐渐受到重视。利用激光扫描数据提取建筑物可以分为两大类,第一类是单纯以获取的机载激光测距数据来提取建筑物,第二类是融合激光测距数据和其他相关信息的建筑物提取,如融合航空影像、融合IKONOS高分辨率卫星影像来提取建筑物。本文对国际上利用机载激光扫描测距数据进行建筑物提取的最新研究进展进行了一些分析,同时也给出了应用我国研制的机载激光扫描数据提取建筑物的试验研究和初步结果。     

Inter-comparison of remote sensing platforms for height estimation of mango and avocado tree crowns

To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R² = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R² = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km² due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R² = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R² = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km²–100 km²). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R² = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R² = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.     

Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods

This study compares the accuracies of diameter at breast height (DBH) estimations by three initial (minimum bounding box, centroid, and maximum distance) and two refining (Monte Carlo and optimal circle) circle-fitting methods The circle-fitting algorithms were evaluated in multi-scan mode and a simulated single-scan mode on 157 European beech trees (Fagus sylvatica L.). DBH measured by a calliper was used as reference data. Most of the studied circle-fitting algorithms significantly underestimated the mean DBH in both scanning modes. Only the Monte Carlo method in the single-scan mode significantly overestimated the mean DBH. The centroid method proved to be the least suitable and showed significantly different results from the other circle-fitting methods in both scanning modes. In multi-scan mode, the accuracy of the minimum bounding box method was not significantly different from the accuracies of the refining methods The accuracy of the maximum distance method was significantly different from the accuracies of the refining methods in both scanning modes. The accuracy of the Monte Carlo method was significantly different from the accuracy of the optimal circle method in only single-scan mode. The optimal circle method proved to be the most accurate circle-fitting method for DBH estimation from point clouds in both scanning modes.     

Detecting pruning of individual stems using Airborne Laser Scanning data captured from an Unmanned Aerial Vehicle

Modern forest management involves implementing optimal pruning regimes. These regimes aim to achieve the highest quality timber in the shortest possible rotation period. Although a valuable addition to forest management activities, tracking the application of these treatments in the field to ensure best practice management is not economically viable. This paper describes the use of Airborne Laser Scanner (ALS) data to track the rate of pruning in a Eucalyptus globulus stand. Data is obtained from an Unmanned Aerial Vehicle (UAV) and we describe automated processing routines that provide a cost-effective alternative to field sampling. We manually prune a 500 m² plot to 2.5 m above the ground at rates of between 160 and 660 stems/ha. Utilising the high density ALS data, we first derived crown base height (CBH) with an RMSE of 0.60 m at each stage of pruning. Variability in the measurement of CBH resulted in both false positive (mean rate of 11%) and false negative detection (3.5%), however, detected rates of pruning of between 96% and 125% of the actual rate of pruning were achieved. The successful automated detection of pruning within this study highlights the suitability of UAV laser scanning as a cost-effective tool for monitoring forest management activities.     

三维激光扫描的龙柱倾斜观测方法

针对城市高耸建筑物倾斜观测作业时间长、信息量少的问题,将三维激光扫描技术应用到城市高耸建筑物变形监测领域,探讨对无观测标志、不可或不便攀登的城市高耸建筑物进行倾斜观测的施测方法。以龙柱为例,制定了可行的测量方案,并采用高斯曲面拟合算法对其表面进行拟合,精确计算出龙柱的倾斜量,且与全站仪倾斜观测结果进行对比。结果表明,该方法可以快速、全面的获取观测对象的整体信息,且能够满足高耸建筑物倾斜观测的精度要求。     

旧城改造中建筑物立面快速提取方法

旧城改造目前面临诸多问题,如传统的测量手段不仅测量效率低,而且对于结构比较复杂的建筑物无法精确地获取建筑物立面的全部信息,施测不全面,建模效率低等。首先利用三维激光扫描技术获取建筑物精细、整体的点云数据,借助多个建模平台联合作业的方式,结合现场照片进行复杂建筑物的三维重建,从而获取目标建筑物各个方向的立面信息。经过大量验证和对比分析,该方法可以快速获得建筑物精确、真实、全面的立面信息,提高工作效率,为智慧城市的建设和规划提供详细可靠的信息支持。     

Calibration of area based diameter distribution with individual tree based diameter estimates using airborne laser scanning

Diameter distribution is essential for calculating stem volume and timber assortments of forest stands. A new method was proposed in this study to improve the estimation of stem volume and timber assortments, by means of combining the Area-based approach (ABA) and individual tree detection (ITD), the two main approaches to deriving forest attributes from airborne laser scanning (ALS) data. Two methods, replacement, and histogram matching were employed to calibrate ABA-derived diameter distributions with ITD-derived diameter estimates at plot level. The results showed that more accurate estimates were obtained when calibrations were applied. In view of the highest accuracy between ABA and ITD, calibrated diameter distributions decreased its relative RMSE of the estimated entire growing stock, saw log and pulpwood fractions by 2.81%, 3.05% and 7.73% points at best, respectively. Calibration improved pulpwood fraction significantly, which contributed to the negligible bias of the estimated entire growing stock.     

Change detection in urban areas by object-based analysis and on-the-fly comparison of multi-view ALS data

The use of helicopters as a sensor platform offers flexible fields of application due to adaptable flying speed at low flight levels. Modern helicopters are equipped with radar altimeters, inertial navigation systems (INS), forward-looking cameras and even laser scanners for automatic obstacle avoidance. If the 3D geometry of the terrain is already available, the analysis of airborne laser scanner (ALS) measurements may also be used for terrain-referenced navigation and change detection. In this paper, we present a framework for on-the-fly comparison of current ALS data to given reference data of an urban area. In contrast to classical difference methods, our approach extends the concept of occupancy grids known from robot mapping. However, it does not blur the measured information onto the grid cells. The proposed change detection method applies the Dempster–Shafer theory to identify conflicting evidence along the laser pulse propagation path. Additional attributes are considered to decide whether detected changes are of man-made origin or occurring due to seasonal effects. The concept of online change detection has been successfully validated in offline experiments with recorded ALS data streams. Results are shown for an urban test site at which multi-view ALS data were acquired at an interval of 1 year.     

三维激光扫描技术在历史建筑立面测绘中的应用北大核心CSCD

随着现代化科技手段的进步与更新,利用三维激光扫描实景复制新型技术原理替代传统式单点立面测绘的技术手段,对历史建筑进行保护,能最大化节省人工成本,提高工作效率。能够将细节、精度、效率统一达到产能最大化,也能提供更高级且全面的原始数据存档及成果交付方式,不断更新历史建筑数字化的技术标准。     

一种SPOT影像快速纠正的方法

本文提出SPOT影像的一种快速正射纠正法,该方法采用分块内插算法和加速措施可以快速地完成SPOT影像的正射纠正。理论分析和实验结果都证实,在采用合理的分块尺寸的条件下,该方法可以保持传统方法正射纠正影像的精度基本不变,在精度损失的极小范围内实现SPOT影像的快速正射纠正。