无人机影像匹配点云的露天矿台阶高度计算方法

计算露天矿台阶高度是矿山测量验收工作的重要部分,对加强矿山生产监控和成本管理具有重要意义。针对传统台阶高度量测方法工作量大、效率差,难以保障测绘人员安全等问题,本文基于无人机倾斜摄影获取的露天矿点云提出了一种顾及边坡分层结构的台阶高度计算方法。该方法通过面元划分剔除平坦区域,再利用密度聚类处理坡面点云,最后通过随机抽样一致性获取台阶坡顶线和坡底线,计算台阶高度。试验结果表明,该方法可以高效、精确地量测露天矿台阶高度,对于矿区的开采作业和安全防范具有重要的应用价值。     

一种基于距离变换与标记图的边缘匹配方法

介绍了基于3-4Chamfer距离变换的边缘匹配方法，针对距离变换易受干扰等问题，提出了使用距离变换的标记图方法建立目标图像边缘点与其距离图的对应关系。利用Model—Based方法，使用参数搜索遗传算法，将结合标记图的3-4Chamfer距离作为评价依据。实验结果显示，使用3-4Chamfer距离图结合路径图的方法对轮廓的匹配比直接使用距离图的方法有较明显的改进。     

一种基于高度差异的点云数据分类方法

LiDAR点云数据存在数据量大、不易识别、不易处理的问题,为了解决上述问题,需要对点云数据进行分类处理。针对点云分类方法存在精度不高、处理过程复杂等难题,本文提出了一种基于高度差值的二次导数的建筑物、植被的点云分类方法,能够高效、准确地将各类点云分离。利用该方法分离点云数据,首先通过Terra Solid软件对原始LiDAR点云数据进行初步处理,去除噪点并提取出地表点云,然后利用规则建筑和不规则植被高度差异上的二次导数不同,提取出可能是建筑物或植被的点,并利用高斯偏差估计模型为建筑物、植被点的分类提供阈值,最后利用断点统计模型将建筑物、植被点云补充完整。为证明这种方法的可行性和有效性,使用Autzen_Stadium地区的LiDAR点云数据进行点云分类试验,结果表明,该方法具有可行性好、分类效果好、处理自动化等优势。     

三维激光点云数据在城市建筑物高度监测中的应用

三维激光扫描技术是一种新型的测绘技术,为高时空分辨率全球空间数据信息获取提供了一种跨时代的技术手段。本文探讨了利用三维激光技术获取的点云数据,在地理国情监测中城市建成区城市建筑物高度监测中的应用,阐述了其技术流程和分析方法。与传统的测量方法相比,该方法具有工作效率高、测量精度高的优点,对于相同的测绘类项目具有较好的借鉴意义。     

一种基于室内点云数据的建筑墙线提取

针对室内点云数据无结构化属性、数据间无连接、不承载语义信息且数据点密度高的特点,结合建筑物点云几何特征和室内导航需求,通过数据降维简化建筑几何特征提取的复杂性,提出一种基于室内点云数据提取建筑物墙线的方法.该方法首先通过向特定方向投影,利用点云密度直方图完成天花板面、地板面和房间墙面的初步分割;然后将房间墙面点云数据向...     

一种无人机热红外与可见光影像匹配方法

针对异源无人机影像视角、分辨率、灰度值差异大的特点,提出一种基于语义深度局部特征的无人机热红外与可见光影像匹配方法。该方法首先利用全卷积神经网络和注意力机制提取具有语义信息的深度局部特征;其次以多通道特征图作为描述符进行kd-tree匹配;最后将向量场一致性VFC(Vector Field Consensus)和随机采样一致性RANSAC(Random Sample Consensus)相结合(VFC-RANSAC)进行误匹配剔除,从而实现无人机热红外与可见光影像的稳健匹配。匹配试验表明,与SIFT、KAZE等提取的人工特征相比,深度特征可以抵抗更大的影像几何和辐射差异;与RANSAC相比,VFC-RANSAC能够更有效地剔除外点,获得更高的正确匹配率和匹配精度。     

基于机载激光点云的建筑物高度提取方法研究

以宁波市第一次地理国情普查中的建筑高度普查专项工作为例,提出了一条基于激光点云分类成果、大比例尺地形图和DEM,快速提取建筑物高度的技术路线。实验结果表明,该方法可快速准确提取建筑高度和顶部纹理信息,从而为城市建设和规划提供了可靠的测绘地理信息服务和保障。     

影像边缘特征与LS-SVM的点云边缘残缺区域修补方法

针对点云修补过程中点云边缘的残缺区域边界信息的不确定性问题,本文提出了一种基于影像边缘特征与LS-SVM的点云边缘残缺区域修补方法:首先将影像与点云进行配准,并利用亚像素边缘检测算法提取目标边缘特征;然后构造一特征平面,同时将训练样本集与目标边缘特征投影至该平面,以确定重采样范围与点位;通过利用最小二乘支持向量机回归方法,获得残缺区域的曲面方程并进行重采样,最终完成修补。实验证明,该方法得到的修补点云与原始数据融合平滑,修补效果符合实际目标的特征。     

热红外图像与可见光图像的配准与融合

红外热成像是一种有效的无损检测技术.红外与可见光传感器是目标识别系统中常用的两种传感器,对这两种传感器图像进行有效地融合能大大提高探测识别的准确性和可靠性.图像配准是图像融合的前提,在仿射变换的模型基础上,用最小二乘法达到用多个配准点拟合出最优参数解的目的.在图像融合中引入了小波变换,实现了图像的彩色融合.     

欧氏聚类算法支持下的点云数据分割

欧氏聚类算法是多元统计中的一种重要分类方法,可以将其应用于测绘领域中点云数据的分割。本文首先计算点云数据中两点之间的欧氏距离,将距离小于指定阈值作为分为一类的判定准则;然后迭代计算,直至所有的类间距大于指定阈值,完成欧氏聚类分割。具体步骤为：①利用Octree法建立点云数据拓扑组织结构;②对每个点进行k近邻搜索,计算该点与k个邻近点之间的欧氏距离,最小归为一类;③设置一定的阈值,对步骤②迭代计算,直至所有类与类之间的距离大于指定阈值。试验证明,欧氏聚类算法对不同测量技术手段获取的点云数据均具有适用性,可以成功对点云数据进行分割,分割效果良好。     

基于双阈值SSDA模板匹配的遥感图像道路边缘检测研究

利用遥感图像提取道路边缘信息可以简化常规城市道路的测绘工作。根据一般道路在图像上的影像特征对图像进行模型化处理,提出了基于双阈值的序贯相似性检测算法(sequential similarity detection algorithm,SSDA)的模板匹配算法,并在该算法的基础上,提出了一个基于减小增长误差的算子,用以减少由于样本数过多而产生的增长误差。与其他算法相比,该算法能够更有效地获取道路边缘信息,在准确提取路面边缘信息的同时,能对预处理中难以完全提取的路面部分进行修复,减少处理过程,从而提高处理效率。     

Retrieval of leaf water content spanning the visible to thermal infrared spectra

The objective of this study was to investigate the entire spectra (from visible to the thermal infrared; 0.390–14.0 μm) to retrieve leaf water content in a consistent manner. Narrow-band spectral indices (calculated from all possible two band combinations) and a partial least square regression (PLSR) were used to assess the strength of each spectral region. The coefficient of determination (R²) and root mean square error (RMSE) were used to report the prediction accuracy of spectral indices and PLSR models. In the visible-near infrared and shortwave infrared (VNIR–SWIR), the most accurate spectral index yielded R² of 0.89 and RMSE of 7.60%, whereas in the mid infrared (MIR) the highest R² was 0.93 and RMSE of 5.97%. Leaf water content was poorly predicted using two-band indices developed from the thermal infrared (R² = 0.33). The most accurate PLSR model resulted from MIR reflectance spectra (R² = 0.96, RMSE = 4.74% and RMSE cross validation RMSE_CV = 6.17%) followed by VNIR–SWIR reflectance spectra (R² = 0.91, RMSE = 6.90% and RMSE_CV = 7.32%). Using thermal infrared (TIR) spectra, the PLSR model yielded a moderate retrieval accuracy (R² = 0.67, RMSE = 13.27% and RMSE_CV = 16.39%). This study demonstrated that the mid infrared (MIR) and shortwave infrared (SWIR) domains were the most sensitive spectral region for the retrieval of leaf water content.     

A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data

Surface soil moisture (SSM) is a critical variable for understanding the energy and water exchange between the land and atmosphere. A multi-linear model was recently developed to determine SSM using ellipse variables, namely, the center horizontal coordinate (x₀), center vertical coordinate (y₀), semi-major axis (a) and rotation angle (θ), derived from the elliptical relationship between diurnal cycles of land surface temperature (LST) and net surface shortwave radiation (NSSR). However, the multi-linear model has a major disadvantage. The model coefficients are calculated based on simulated data produced by a land surface model simulation that requires sufficient meteorological measurements. This study aims to determine the model coefficients directly using limited meteorological parameters rather than via the complicated simulation process, decreasing the dependence of the model coefficients on meteorological measurements. With the simulated data, a practical algorithm was developed to estimate SSM based on combined optical and thermal infrared data. The results suggest that the proposed approach can be used to determine the coefficients associated with all ellipse variables based on historical meteorological records, whereas the constant term varies daily and can only be determined using the daily maximum solar radiation in a prediction model. Simulated results from three FLUXNET sites over 30 cloud-free days revealed an average root mean square error (RMSE) of 0.042 m³/m³ when historical meteorological records were used to synchronously determine the model coefficients. In addition, estimated SSM values exhibited generally moderate accuracies (coefficient of determination R² = 0.395, RMSE = 0.061 m³/m³) compared to SSM measurements at the Yucheng Comprehensive Experimental Station.     

Transforming ellipsoidal heights and geoid undulations between different geodetic reference frames

Transforming height information that refers to an ellipsoidal Earth reference model, such as the geometric heights determined from GPS measurements or the geoid undulations obtained by a gravimetric geoid solution, from one geodetic reference frame (GRF) to another is an important task whose proper implementation is crucial for many geodetic, surveying and mapping applications. This paper presents the required methodology to deal with the above problem when we are given the Helmert transformation parameters that link the underlying Cartesian coordinate systems to which an Earth reference ellipsoid is attached. The main emphasis is on the effect of GRF spatial scale differences in coordinate transformations involving reference ellipsoids, for the particular case of heights. Since every three-dimensional Cartesian coordinate system ‘gauges’ an attached ellipsoid according to its own accessible scale, there will exist a supplementary contribution from the scale variation between the involved GRFs on the relative size of their attached reference ellipsoids. Neglecting such a scale-induced indirect effect corrupts the values for the curvilinear geodetic coordinates obtained from a similarity transformation model, and meter-level apparent offsets can be introduced in the transformed heights. The paper explains the above issues in detail and presents the necessary mathematical framework for their treatment. An erratum to this article can be found at     

机载LIDAR点云数据的处理及检校

利用机载LiDAR技术获取较大范围地面三维信息比传统测量方法具有高精度、高密度、速度快、成本低的优点,已成为国土资源管理领域一个重要支撑技术。在实际应用中,激光点云数据处理及其检校是生产的关键环节,直接影响成果质量和作业效率。该论述结合测制我国西部某测区带状4D成果的应用实例,综合分析了原始激光点云数据的获取、标准激光点云数据的制作及其分层分类处理等关键过程和需要注意的问题,详细论述了标准激光点云数据的检校及其检校精度检测的方法步骤,分析评估了检校精度对激光点云平面和高程精度的影响,可为同类工程提供借鉴。     

基于车载激光扫描数据的电线杆自动识别与定位

本文对车载激光扫描数据进行了研究,将投影点密度(DoPP)与电线杆的几何特点相结合,提出了一种基于激光扫描数据的电线杆自动识别和定位的方法。首先,将车载测量系统获取的激光点云投影到水平面,建立水平格网,设置投影点密度阈值分类出杆状地物所在的格网区域;然后将分类得到的杆状数据拟合成为一条空间直线,以电线杆的几何特性作为期望值和方差,自动识别电线杆;最后,该空间直线与地面网格相交确定电线杆的定位位置。本文算法与T3D Analyst商用软件提取的电线杆进行比较,实验结果表明本文方法行之有效。     

IMU/DGPS辅助车载CCD及激光扫描仪三维数据采集与建模

三维信息快速采集是真实场景建模与三维虚拟现实技术的关键。本文提出了一种基于激光扫描仪、线/面阵CCD相机及GPS与IMU等多种传感器融合的车载移动式数据快速采集系统。各传感器安置在车内稳定平台上并随车保持一致的运动姿态。通过对GPS和IMU数据进行卡尔曼(Kalman)滤波,可推测出整个系统及各传感器的位置和最佳姿态估计;从扫描仪点云数据可提取出街道场景中事物的三维几何信息;线阵CCD相机用于获取路面带状地物等线性特征;面阵CCD采集街道两侧面状纹理信息,从而快速获得城市目标的地理坐标和三维建模信息,由此可重建城市路面街道的三维真实场景。     

Modelling,encoding and transforming of open geographic data to examine interoperability between GIS applications

The interoperability of geographic data sets is required between geo-information system applications to use geographic data sets effectively. Thus, international standardisation organisation/technical committee 211 standards supporting model-driven architecture were examined to test the ability of producing interoperable geographic data sets. With Turkey case, unified modelling language application schemas were designed for base geographic data themes and encoded to data interchange model based on geography markup language. To test the applicability of the open data models, extract-transform-load (ETL) tools were developed and applied for case applications such as topographic map and web urban atlas. This study gives a methodology and indicates that ETL tools should be created to enable multiple uses of geo-data sets without spending time and labour. However, data model design should be refined and kept as simple as possible because data transformation is laborious to use the models in the applications.