机载LiDAR测深点云滤波与分类方法研究EI北大核心CSCD

机载LiDAR测深(airborne LiDAR bathymetry,ALB)技术在海岸带、海岛礁等复杂浅水海域的水下地形测量中具有效率高、精度高、机动性强等优势,但受复杂海面、水体环境等多种因素的综合影响,ALB点云中存在大量噪点,直接影响ALB数据成果质量及其应用。为此,论文针对海面异常点导致的海底虚假地形、海底点云过度滤波导致的真实地形细节损失以及如何深度挖掘ALB信息进行高效底质分类问题,分别从海面异常点检测、海底点云滤波和海底点云分类3个方面进行了详细研究。     

机载LiDAR点云数据建筑物提取方法适应性研究

为解决机载LiDAR点云数据建筑物提取精度不高的问题,首先分析了现有的基于机载LiDAR点云数据的建筑物提取方法;然后综合地形、树木、建筑物密度等对建筑物提取的影响,以德国斯图加特市法伊英根的LiDAR点云数据为例进行了建筑物提取实验;最后对提取结果进行了定量精度评定。结果表明,基于影像的机载LiDAR点云数据建筑物提取精度为93.1%;而基于数学形态学图像的处理方法和基于Delaunay三角剖分的方法受建筑物形状和地形等限制较多,提取精度分别为87.6%和81.3%,说明基于影像的机载LiDAR点云数据建筑物提取方法的准确性较高,限制性条件较少。     

基于超体素的机载LiDAR点云滤波与建筑物提取方法

为了提高目前机载LiDAR点云数据滤波和建筑物提取精度,本文提出一种基于超体素的点云滤波与建筑物提取方法。对每个超体素进行相似性判断来实现向上一层的区域增长式合并,并通过判断超体素簇与邻接超体素簇的凹凸性实现再向上一层的合并,最终通过计算聚类对象自身几何特征来过滤地面、植被和噪声,从而得到建筑物点云。实验利用ISPRS公布的标准数据集,选择3个地形数据进行实验。实验结果表明本文算法滤波性能更好,建筑物提取结果优于专业点云处理软件的提取结果。     

基于LiDAR点云数据索引的DEM快速提取

DEM应用日趋广泛,从LiDAR点云数据中提取DEM是一种满足应用需求的简单有效方法。由于Li-DAR点云数据的庞大性,直接提取DEM效率不高。为了提高对点云数据处理的效率,本文探索应用索引技术来优化LiDAR点云数据的处理,生成高精度DEM。该方法首先对LiDAR原始数据点建立网格分块索引;然后再利用形态学的方法对LiDAR原始数据进行滤波处理;最后用逐点内插方法生成DEM。实验结果表明应用空间数据索引技术极大地提高了点云数据滤波与DEM生成的效率。     

轻型机载LiDAR在农村宅基地房屋测量中的应用

选择新疆焉耆县北大渠乡北大渠村房屋密集区作为研究区,通过三角翼搭载轻型机载LiDAR进行了低空（170m）交叉航线高密度点云数据采集,对点云数据进行拼接、校正、纹理信息增强,在点云上对房屋进行矢量化,并对结果进行精度检查。点云数据房角点采集率为83.3%,中误差为4.8cm。采用机载LiDAR测量房角点能够大大减少外业房角点测量的工作量。机载LiDAR的应用鲜有纹理信息的提取,本次测试通过对高密度点云数据进行有效的处理,提取了点云数据纹理信息,为机载LiDAR数据纹理信息的应用提供了参考,并对其精度有了明确的认识,可为后期相关工作的开展提供借鉴。     

基于机载LiDAR点云数据的城区道路提取

对于利用机载LiDAR点云数据提取城区道路提出一种新的思路。首先利用机载LiDAR点云数据的高程和强度属性对城区道路进行初始提取,获得初始道路点云;其次采用距离分割法和基于RANSAC算法的分割方法精化初始道路点云,有效剔除停车场等与道路相似的区域;最后采用数学形态学细化方法提取道路中心线。实验结果表明,该方法可以较正确和完整地提取城区道路。     

面向滩涂DEM构建的机载LiDAR点云滤波方法

在基于激光点云构建DEM的过程中,用于区分地面点和非地面点的点云滤波处理至关重要。本文面向基于机载LiDAR点云的沿海滩涂DEM高精度的构建需求,提出了一种机载LiDAR点云的改进坡度滤波算法。首先,采用统计异常值剔除法(SOR)去除原始机载LiDAR点云数据中的噪声;然后,利用规则格网的坡度和高程阈值,设计了适用于滩涂点云数据的地面点坡度滤波方法;最后,选取如东市长沙港的滩涂机载LiDAR点云作为试验数据,构建滩涂DEM,并进行精度检验。试验结果表明,利用本文方法处理后的LiDAR点云构建的DEM精度满足国家与行业标准的要求。     

基于机载LiDAR点云数据的城区道路提取

针对利用机载LiDAR点云数据提取城区道路问题,本文提出一种新的思路。首先利用机载LiDAR点云数据的高程和强度属性对城区道路进行初始提取,获得初始道路点云;然后采用距离分割法和基于RANSAC算法的分割方法精化初始道路点云,有效剔除停车场等与道路相似的区域;最后采用数学形态学细化方法提取道路中心线。实验结果表明,该方法可以较完整地提取城区道路。     

基于NoSQL的机载LiDAR海量点云数据分布式存储

机载LiDAR点云数据是遥感大数据的重要组成部分,其海量化的趋势日益显著。本文设计并实现了基于NoSQL的海量机载LiDAR点云分布式存储模型,解决了海量机载LiDAR点云数据的高效存储问题。通过建立基于虚拟格网与线性八叉树的海量机载LiDAR点云数据组织结构,设计了基于虚拟格网号与Morton码的海量机载LiDAR点云数据标识唯一编码;提出了基于HBase的海量机载LiDAR点云数据存储策略,实现了键值和表结构的优化设计;最终实现了海量机载LiDAR点云数据的高效存储和快速查询。     

基于层次分析和神经网络的机载LiDAR点云分类

在机载LiDAR点云数据处理中,由于机载雷达点云数据的离散性、不确定性等原因,导致点云分类上很难得到准确的结果。针对机载LiDAR点云数据分类问题,提出了基于层次分析和神经网络的机载LiDAR点云分类方法。根据机载LiDAR点云的数据特征以及不同地物的属性,采用层次分析法赋予每个点云一个二进制信号,然后采用后向传播神经网络(BP-ANN)对机载LiDAR点云数据分类。实验表明:这种方法能够从机载LiDAR独立数据源中分类出房屋、高大的树、低矮的树、道路等地物点云。     

一种计算机辅助设计数据与GIS数据转换方法

针对GIS数据与计算机辅助设计(CAD)数据之间的差异性,以及现有转换方法存在的问题,该文提出了一种计算机辅助设计数据处理方法——采用空间数据操作引擎(FME)和Arc Map联合使用的方法。该方法能够较好地解决计算机辅助设计数据向GIS数据转换的难题,实现了对计算机辅助设计数据的批量转换和处理。以某市的地形图为数据源进行实例论证,实验结果显示运用该文所提方法能够更好地处理计算机辅助设计数据,为计算机辅助设计地形图的转换提供了可行的方案;特别是对转换出来的数据进行了拓扑重建、附属性值以及多边形数据分类处理,能够更好地保持数据的精度和完整性,更有利于数据的入库。     

Three dimensional data structure and data model

3D GISs were developed simultaneously in the late 1980s in a number of different disciplines.The development of these 3D GISs can not yet meet all needs for new representations and analytical tools in 3D envir onments.In this paper,the data structures,especially solid-based data representa tions are introduced.Then,a typical object-oriented data model is put forth to show a new data model.And at last,two data access methods are proposed to make the data model clear.     

数传通道遥测数据处理方法研究

天绘卫星在轨运行期间, 星务数据存储模块负责存储整星遥测数据, 并协同相机数据通过数传通道传到地面。本文根据数传通道遥测数据的格式, 提出一种处理遥测数据的方法, 该方法从地面站接收数传通道下传数据, 提取出整颗星遥测数据, 并通过电气地面支持设备对在轨遥测数据进行处理, 便于后期对整星遥测数据的分析。     

Controlling data uncertainty via aggregation in remotely sensed data

Aggregation may be used as a means of enhancing remotely sensed data accuracy, but there is a tradeoff between loss of information and gain in accuracy. Thus, the choice of the proper cell size for aggregation is important. This letter explores the change in data accuracy that accompanies aggregation and finds an increase in image thematic accuracy with increasing cell size, resulting from 1) reduction in the impact of misregistration on thematic error and 2) mutual cancelation of inverse classification errors occurring within the same cell. A model is developed to quantify these phenomena. The model is exemplified using a vegetation map derived from an aerial photo. The model revealed a major reduction in effective location error for cell sizes in the range of 3-10 times the size of mean location error; reduction in effective classification error was minor.     

基于元数据的科学数据汇交研究

科学数据共享过程中如何把国家设立的科学技术研究项目的数据汇交上来,形成数据仓库,是实现科学数据共享的前提。本文根据国内科学数据的调研结果,提出了科学数据汇交系统的总体框架和科学数据汇交平台的设计,详细阐述了数据汇交过程中的工作流程和技术流程,初步设计了汇交网络体系的结构和功能。     

Integration and Sharing of Geo-spatial Data Based on Data Engine

Through analyzing the principle of data sharing in the database system, this paper discusses the principle and method for integrating and sharing GIS data by data engine, introduces a way to achieve the high integration and sharing of GIS data on the basis of VCT in VC , and provides the method for uniting VCT into RDBMS in order to implement a spatial database with object-oriented data model.     

基于NetCDF数据模型的海洋环境数据三维可视化研究

针对海洋环境数据多维、多格式及动态性等特点,本文在全面分析NetCDF数据模型的原理、数据组织及其调度方法的基础上,基于大范围三维虚拟场景,设计了符合NetCDF标准典型海洋环境要素的三维动态渲染模型,实现了海洋环境要素数据的三维动态可视化表达与分析。实验表明,本文方法为复杂海洋现象的表达、变化规律分析以及趋势预测等研究提供强有力的可视化辅助工具。     

Contrast enhancement of landsat data on multispectral data analysis system

Contrast enhancement, one of the image processing techiques, is developed on the Multispectral Data Analysis System (MDAS) for enhancing the LANDSAT data. The purpose of image processing for enhancement is to improve the obscure objects data in the image to stand out more readily for good sensing to the human eye. It is observed on MDAS that some of the LANDSAT scenes when examined on the color display, give inadequate information for the required objective of interpretation. This is due to poor tonal contrast in the scene because of prevailing climatological conditions at the time of satellite pass over that area. Also, the LANDSAT data usually occupy a small subset of the total brightness range 0–127. To provide optimal contrast and variation for color compositing, contrast enhancement may by performed on the data before going to trie information processing (categolization) on the landsat scene. This paper describes the algorithms of parametric linear and non linear contrast enhancement techniques. A typical example to differentiate the degree of salinity in the soils was tested with the suggested algorithms and the results are tabulated in the form of photographs. The test area is selected from Haryana (frame no. 158-040 dated 2nd May, 1977) for testing the algorithms. The enhancement software developed on the MDAS stretches all the four Landsat bands and generates an output tape with the format similar to LANDSAT computer compatible tape (CCT). The stretched results of 5 and 7 bands are displayed in this paper. A false color composite which appears as on the color displya could also be generated from 4, 5 and 7 bands. The enhanced output was found to be useful for easily categorizing the data into various categories on MDAS.     

Calibration of satellite gradiometer data aided by ground gravity data

Parametric least squares collocation was used in order to study the detection of systematic errors of satellite gradiometer data. For this purpose, simulated data sets with a priori known systematic errors were produced using ground gravity data in the very smooth gravity field of the Canadian plains. Experiments carried out at different satellite altitudes showed that the recovery of bias parameters from the gradiometer “measurements” is possible with high accuracy, especially in the case of crossing tracks. The mean value of the differences (original minus estimated bias parameters) was relatively large compared to the standard deviation of the corresponding second-order derivative component at the corresponding height. This mean value almost vanished when gravity data at ground level were combined with the second-order derivative data set at satellite altitude. In the case of simultaneous estimation of bias and tilt parameters from ∂² T/∂z ²“measurements”, the recovery of both parameters agreed very well with the collocation error estimation. Received: 10 October 1996 / Accepted 25 May 1998