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81.
This paper describes a geographic information system(GIS)-based method for observing changes in topography caused by the initiation, transport, and deposition of debris flows using highresolution light detection and ranging(LiDAR) digital elevation models(DEMs) obtained before and after the debris flow events. The paper also describes a method for estimating the volume of debris flows using the differences between the LiDAR DEMs. The relative and absolute positioning accuracies of the LiDAR DEMs were evaluated using a real-time precise global navigation satellite system(GNSS) positioning method. In addition, longitudinal and cross-sectional profiles of the study area were constructed to determine the topographic changes caused by the debris flows. The volume of the debris flows was estimated based on the difference between the LiDAR DEMs. The accuracies of the relative and absolute positioning of the two LiDAR DEMs were determined to be ±10 cm and ±11 cm RMSE, respectively, which demonstrates the efficiency of the method for determining topographic changes at an scale equivalent to that of field investigations. Based on the topographic changes, the volume of the debris flows in the study area was estimated to be 3747 m3, which is comparable with the volume estimated based on the data from field investigations. 相似文献
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84.
The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario. 相似文献
85.
A computational canopy volume (CCV) based on airborne laser scanning (ALS) data is proposed to improve predictions of forest biomass and other related attributes like stem volume and basal area. An approach to derive the CCV based on computational geometry, topological connectivity and numerical optimization was tested with sparse-density, plot-level ALS data acquired from 40 field sample plots of 500–1000 m2 located in a boreal forest in Norway. The CCV had a high correspondence with the biomass attributes considered when derived from optimized filtrations, i.e. ordered sets of simplices belonging to the triangulations based on the point data. Coefficients of determination (R2) between the CCV and total above-ground biomass, canopy biomass, stem volume, and basal area were 0.88–0.89, 0.89, 0.83–0.97, and 0.88–0.92, respectively, depending on the applied filtration. The magnitude of the required filtration was found to increase according to an increasing basal area, which indicated a possibility to predict this magnitude by means of ALS-based height and density metrics. A simple prediction model provided CCVs which had R2 of 0.77–0.90 with the aforementioned forest attributes. The derived CCVs always produced complementary information and were mainly able to improve the predictions of forest biomass relative to models based on the height and density metrics, yet only by 0–1.9 percentage points in terms of relative root mean squared error. Possibilities to improve the CCVs by a further analysis of topological persistence are discussed. 相似文献
86.
Canada is dominated by forested ecosystems which are subject to various inventory and management practices, with more northern boreal forests subject to neither. Our objectives were to measure the capacity of temporal trajectory metrics for estimating selected forest attributes in a northern Canadian boreal forest context using Landsat imagery and investigate the importance of different types of temporal trajectory metrics. Results indicated that Wetness was the best Tasseled Cap (TC) component for aboveground biomass estimation (R2 = 50%, RMSE% = 56%), and the combination of simple and complex metrics from all TC components produced the highest R2 (62%) and lowest RMSE% (49%). Using a similar combination of variables, other forest attributes were estimated equally reliably with lower RMSE% values. The most important temporal trajectory metrics were simple and described TC component values at each point of change in the temporal trajectory, however the most important variables overall were environmental variables. 相似文献
87.
The development of robust and accurate methods for automatic registration of optical imagery and 3D LiDAR data continues to be a challenge for a variety of applications in photogrammetry, computer vision and remote sensing. This paper proposes a new approach for the registration of optical imagery with LiDAR data based on the theory of Mutual Information (MI), which exploits the statistical dependency between same- and multi-modal datasets to achieve accurate registration. The MI-based similarity measures quantify dependencies between aerial imagery, and both LiDAR intensity data and 3D point cloud data. The needs for specific physical feature correspondences, which are not always attainable in the registration of imagery with 3D point clouds, are avoided. Current methods for registering 2D imagery to 3D point clouds are first reviewed, after which the mutual MI approach is presented. Particular attention is given to adoption of the Normalised Combined Mutual Information (NCMI) approach as a means to produce a similarity measure that exploits the inherently registered LiDAR intensity and point cloud data so as to improve the robustness of registration between optical imagery and LiDAR data. The effectiveness of local versus global similarity measures is also investigated, as are the transformation models involved in the registration process. An experimental program conducted to evaluate MI-based methods for registering aerial imagery to LiDAR data is reported and the results obtained in two areas with differing terrain and land cover, and with aerial imagery of different resolution and LiDAR data with different point density are discussed. These results demonstrate the potential of the MI and especially the CMI methods for registration of imagery and 3D point clouds, and they highlight the feasibility and robustness of the presented MI-based approach to automated registration of multi-sensor, multi-temporal and multi-resolution remote sensing data for a wide range of applications. 相似文献
88.
利用LiDAR数据进行电力设施提取与建模可以克服传统工程测量电力巡线工作量大,危险性高,效率低下等缺点,但现有的电力线提取研究主要集中在电力线的分离与提取,并且拟合的精度不高。针对此问题本文提出了一种精度较高的电力线拟合方法。首先,根据电力线两端悬挂、中间自然下垂的特点,求解电力线拟合的最佳几何模型;然后,通过电力线的走向和端点,建立电力线拟合的最佳平面坐标系;最后,采用基于二次多项式限制的最小二乘法拟合电力线,解算出最优参数,生成最终电力线模型。对真实数据的处理和精度评价表明,本文方法不仅能够实现电力线的快速3维重建,而且能够达到较高的拟合精度。 相似文献
89.
为了能更好地理解激光雷达技术工作原理与三维信息采集全过程,规避现有激光雷达技术,尤其是机载激光雷达,在实践教学中受场地限制的不利条件,本文依托于中国矿业大学(北京)沙河校区的航空模拟平台,自主研发了一套基于单线激光雷达与行程测距仪集成的三维激光扫描装备,阐述了该装备集成的数学原理,设计了三维数据采集实践教学方法,并进行了三维数据采集的实践体验与数据质量评价。结果表明,该装备采集三维点云的精度优于99%,可为激光雷达技术的实践教学、创新训练及本科毕业设计等环节提供有效的硬件支撑,并可在仓储方量核算等工程应用方面进行推广。 相似文献
90.
分形维数法是分析空间结构分布的一种典型方法,但它对于区分不同的分布形式还存在缺陷。针对这一问题,该文介绍了空隙度指数的定义和树冠空隙度的计算方法;以模拟的树冠点云数据为对象,提出了一种基于三维凸包和三维滑动盒算法的激光雷达(Li DAR)点云数据空隙度分析方法,详尽分析了不同冠型产生的空隙度指数差异;并利用4棵实测的树冠点云数据做检验;最后阐述了空隙度指数在树冠空间异质性分析研究中的作用,并对其应用范围和前景作了展望。结果表明:划分尺度相同时,在一定的尺度范围内,锥型树冠、半球型和半椭球型树冠的差别可以通过空隙度指数曲线有效地区分,实测树冠的结果也体现了空隙度指数对于判断树冠空间结构的有效性。 相似文献