基于点云数据的不规则文物三维重建——以经幢为例     

喜文飞  李灵索  杨勇  李国柱  李春梅  李金平 《测绘通报》2020,(12):87-89

海量点云数据可以较好地构建文物的三维建模，针对文物复杂的表面结构，传统的算法很难达到精细建模，为了解决复杂模型表面的空间三角网构网问题，本文结合空间三角形的法向量构建三角网，以空间三角网表面的曲率为约束条件，构建物体表面的空间三角网，然后对构建的空间三角网进行精细建模。以昆明市文物——经幢为例进行三维重建试验，结果表明，新方法适合室内文物的三维建模，可以达到较好的效果。  相似文献   

融合多源数据的三维建模方法及精度分析     

祖立辉 《北京测绘》2020,(3):347-351

以地面相机影像、低空无人机影像和地面三维激光点云数据为融合对象,研究空地影像融合、低空影像融合地面三维激光点云和低空影像融合三维白模进行三维建模的方法,并对其三维建模精度和建模效果进行综合分析。这3种融合方法进行三维建模丰富了三维模型的色彩纹理信息,提高了三维模型的几何结构精度,能满足较大场景的三维实景模型的建模要求,为数字化古建筑(古文物)保护提供具有较高价值的参考数据。  相似文献   

Fast genetic mapping in barley: case studies of cuticle mutants using RNA-sequencing     

XiaoFeng Li  Chao Li  Qin Zhou  GuoXiong Chen  PengShan Zhao 《寒旱区科学》2020,12(3):180-188

Barley(Hordeum vulgare L.) is one of the earliest domesticated crop species and ranked as the fourth largest cereal production worldwide. Forward genetic studies in barley have greatly advanced plant genetics during the last century; however, most genes are identified by the conventional mapping method. Array genotyping and exome-capture sequencing have also been successfully used to target the causal mutation in barley populations, but these techniques are not widely adopted because of associated costs and partly due to the huge genome size of barley. This review summarizes three mapping cases of barley cuticle mutants in our laboratory with the help of RNA-sequencing. The causal mutations have been successfully identified for two of them and the target genes are located in the pericentromeric regions. Detailed information on the mapping-by-sequencing, mapping-and-sequencing, and RNA-sequencing assisted linkage mapping are presented and some limitations and challenges on the mapping assisted by RNA sequencing are also discussed. The alternative and elegant methods presented in this review may greatly accelerate forward genetics of barley mapping, especially for laboratories without large funding.  相似文献   

利用GLAS激光测高数据评估DSM产品质量及精度优化   总被引：2，自引：0，他引：2  

胡柳茹  唐新明  李国元  付冬暇  窦显辉  赵世湖 《测绘通报》2019,(11):39-43

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。  相似文献   

厚层切叠砂体自然层描述方法:以北一区断东葡一组1-4小层为例     

吴迪  马世忠  景丽娟  周志国 《世界地质》2020,39(1):106-112

将多期切叠河道砂体归类合并,建立一个“垂向连续,横向联通的表外砂岩空间体”(其中砂岩间夹层厚度≤0.4 m)的自然层概念来控制多期河道复合切叠厚砂体。以北一匹断东萄一组1-4小层为例,利用自然层间砂体厚度、切叠程度、测井曲线形态、相叠加类型及砂体叠加期次将自然层分为5类;再依据砂体间切叠位置、切叠程度和切叠形态的差异建立自然层剖面表征方法;依据砂体叠加期次,建立自然层在平面上表征模式。  相似文献   

碎冰条件下单点系泊船舶动态响应特性研究     

杨佳东  吕海宁  王晋 《海洋工程》2019,37(2):29-39

为了研究不同单点系泊位置对极地系泊船舶在来冰角度改变时动态响应的影响,运用离散元方法(DEM),计算了船舶在60%密集度下,冰速为1.0 m/s、冰厚为1 m时不同角度的船冰阻力,结合系泊分析软件二次开发功能,计算分析系泊船舶在不同来冰角度和不同系泊位置下受上述冰情影响下的响应。通过对模拟结果与试验结果的对比,认为离散元方法(DEM)的数值模拟结果与试验结果吻合较好;单点系泊位置为距船头L/4时,系泊船舶能以最快速、最稳定的方式对来冰方向的变化做出响应。  相似文献   

基于深度残差网络的机载LiDAR点云分类     

赵传  郭海涛  卢俊  余东行  张保明 《测绘学报》2020,49(2):202-213

机载LiDAR点云的分类是利用其进行城市场景三维重建的关键步骤之一。为充分利用现有的图像领域性能较好的深度学习网络模型,提高点云分类精度,并降低训练时间和对训练样本数量的要求,本文提出一种基于深度残差网络的机载LiDAR点云分类方法。首先提取归一化高程、表面变化率、强度和归一化植被指数4种具有较高区分度的点云低层次特征;然后通过设置不同的邻域大小和视角,利用所提出的点云特征图生成策略,得到多尺度和多视角点云特征图;再将点云特征图输入到预训练的深度残差网络,提取多尺度和多视角深层次特征;最后构建并训练神经网络分类器,利用训练的模型对待分类点云进行预测,经后处理得到分类结果。利用ISPRS三维语义标记竞赛的公开标准数据集进行试验,结果表明,本文方法可有效区分建筑物、地面、车辆等8类地物,分类结果的总体精度为87.1%,可为城市场景三维重建提供可靠的信息。  相似文献   

空地技术结合地形图测图方法研究     

方秋生  王宵雷  刘如飞  马新江 《测绘与空间地理信息》2020,(3):37-40

车载移动测量系统可以快速、高精度地对测区进行三维激光扫描,但是因地物遮挡、视角限制,使得点云数据存在缺失;无人机航测具有高效率、高灵活性和低成本等优势,但是稳定性差,受天气影像严重,易导致影像不清晰或精度低。无人机航测技术可以弥补车载移动测量技术的采集盲区,后者可以发挥高精度的优点,二者技术联合应用,将极大提高测绘精度及生产效率。本文以某小区为例,进行了相关方法实验,对建筑物顶部或植被茂密处等扫描盲区,采用无人机航测补测,通过高精度激光点云对航摄影像进行纠正匹配,综合利用激光点云与航摄影像进行大比例尺测图。  相似文献   

Monitoring soil surface roughness under growing winter wheat with low-altitude UAV sensing: Potential and limitations     

Nils Onnen  Anette Eltner  Goswin Heckrath  Kristof Van Oost 《地球表面变化过程与地形》2020,45(14):3747-3759

Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.  相似文献   

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

《International Journal of Applied Earth Observation and Geoinformation》2020

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.  相似文献