An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering     

Xiaojing Wu  Raul Zurita-Milla  Changqing Song 《International journal of geographical information science》2020,34(9):1822-1848

  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   

MARC: a robust method for multiple-aspect trajectory classification via space,time, and semantic embeddings     

Lucas May Petry  Camila Leite Da Silva  Andrea Esuli  Chiara Renso  Vania Bogorny 《International journal of geographical information science》2020,34(7):1428-1450

ABSTRACT

The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score.  相似文献   

基于车载激光点云的街景立面自动提取     

耿雨馨  钟若飞  彭宝江 《地球信息科学学报》2018,20(4):480-488

街道景观图是城市规划设计和城市管理的重要参考依据,车载点云数据能够提供沿街建筑的三维点信息,精度高,覆盖范围广泛,为街景立面整治提供了新的解决方案。为此,本文提出一种适用于车载点云的街景立面的自动提取方法,提取立面点云的具体步骤为：对原始数据去噪滤波;选取非地面点构建规则格网并二值化,依据语义特征筛选出建筑物点云;用POS数据拟合直线段帮助选取参考向量与参考平面;计算点云到参考面的距离,按距离分类点云数据,并对前述步骤中未分类点另行提取,合并面点集得到以沿街建筑物立面为主的街景立面点云。为了验证这一方法的可行性和有效性,采用点云数据进行实验,实验结果表明本方法在一定程度上提高了数据处理效率,能得到较理想的结果。  相似文献   

基于间接平差的ICP点云配准算法研究     

于明旭 《测绘与空间地理信息》2020,(2):38-40

点云配准精度是决定三维重建模型的质量因素之一,目前,最常用是ICP点云配准算法,经典的ICP算法易局部收敛,影响点云配准精度。本文提出基于间接平差的ICP点云配准算法,设定目标点集中目标点坐标与转入目标点集中的点坐标之间的距离阈值实现点云精确配准。通过与经典ICP算法对比可知,本算法在一定程度上提高了点云配准精度和速度。  相似文献   

一种由粗到精的地面激光点云多层级配准方法     

王英  张云生 《测绘与空间地理信息》2020,(2):156-159

提出了一种综合利用快速点特征直方图(FPFH)描述符和同名点引导ICP优化的地面激光扫描(TLS)点云配准方法。该方法包括3个步骤:1)点云金字塔构建;2)基于FPFH的粗配准;3)同名点引导的ICP精配准。首先使用体素网格滤波器构造点云的金字塔结构,在粗配准时,FPFH描述符用于金字塔顶层上点云的鲁棒匹配,在此基础上,再进行两层级同名点引导的ICP精配准优化,使用3组典型TLS点云对进行实验,结果表明本文方法可以高效地完成TLS点云的配准。  相似文献   

BDS-3多频点伪距单点定位性能研究     

张乾坤  刘小生  何琦敏 《测绘通报》2020,(1):71-75

针对目前有关北斗三号系统伪距单点定位研究较少，未对三号系统多个频点的定位性能进行对比分析的现状，本文利用实测数据对三号系统多个频点的定位性能进行了研究，并联合BDS-2、Galileo进行了同频伪距单点定位试验，统计分析了组合定位多个频点的同频定位结果。试验结果表明：目前三号系统单独定位能力有限，不适合单独定位；BDS-3/Galileo同频组合定位可以弥补BDS-3新频点单频定位时卫星个数不足、数据不完整导致的定位精度过差的情况，同时能够提高Galileo的定位精度；BDS-2/3的B3I频点与BDS/Galileo组合的B2b频点的定位精度均与GPS的L1频点的定位精度相当。  相似文献   

基于深度学习理论的无人机影像分类     

阳成 《北京测绘》2020,(4):481-484

针对无人机影像深度学习分类方法缺乏现状,本文利用深度学习理论卷积神经网络方法对无人机影像进行了分类。该法首先抽取无人机影像作为训练集和检验集,然后建立一个2个卷积层-池化层的卷积神经网络模型进行深度学习,通过设定参数并运行模型实现无人机影像分类。实验表明,本文提出的方法可完成较复杂地区无人机影像分类,其分类精度与支持向量机方法相当,为无人机遥感影像分类提供了一个崭新的技术视点。  相似文献   

BDS-2/BDS-3伪距单点定位精度分析          下载免费PDF全文

方欣颀  范磊 《全球定位系统》2020,45(1):19-25

北斗三号(BDS-3)基本系统于2018年底开始提供全球服务．通过处理37个全球GNSS服务组织(IGS)多模实验跟踪网(MGEX)观测站90天北斗数据,评估了北斗二号(BDS-2)和BDS-3在全球范围内的可见卫星数、几何精度衰减因子(GDOP)和单频伪距单点定位精度,分析了BDS-2／BDS-3组合对BDS-2、BDS-3单系统空间几何构型、伪距单点定位(SPP)精度的改善程度．结果表明,BDS-3的空间几何构型较BDS-2有明显的提升,定位精度在东方向、北方向和高程方向分别为1.490、2.610、5.238 m(RMS),相较于BDS-2分别提高了58％、1％、24％．BDS-2／BDS-3组合在东方向、北方向和高程方向分别为1.45、2.36、4.90 m(RMS),较BDS-2与BDS-3单系统分别提高了59％、11％、29％,以及3％、10％、6％．并且BDS-2／BDS-3组合明显削弱了BDS-2定位精度与地理经度相关的边缘效应.   相似文献   

In-season crop classification using elements of the Kennaugh matrix derived from polarimetric RADARSAT-2 SAR data     

《International Journal of Applied Earth Observation and Geoinformation》2020

Accurate spatio-temporal classification of crops is of prime importance for in-season crop monitoring. Synthetic Aperture Radar (SAR) data provides diverse physical information about crop morphology. In the present work, we propose a day-wise and a time-series approach for crop classification using full-polarimetric SAR data. In this context, the 4 × 4 real Kennaugh matrix representation of a full-polarimetric SAR data is utilized, which can provide valuable information about various morphological and dielectric attributes of a scatterer. The elements of the Kennaugh matrix are used as the parameters for the classification of crop types using the random forest and the extreme gradient boosting classifiers.The time-series approach uses data patterns throughout the whole growth period, while the day-wise approach analyzes the PolSAR data from each acquisition into a single data stack for training and validation. The main advantage of this approach is the possibility of generating an intermediate crop map, whenever a SAR acquisition is available for any particular day. Besides, the day-wise approach has the least climatic influence as compared to the time series approach. However, as time-series data retains the crop growth signature in the entire growth cycle, the classification accuracy is usually higher than the day-wise data.Within the Joint Experiment for Crop Assessment and Monitoring (JECAM) initiative, in situ measurements collected over the Canadian and Indian test sites and C-band full-polarimetric RADARSAT-2 data are used for the training and validation of the classifiers. Besides, the sensitivity of the Kennaugh matrix elements to crop morphology is apparent in this study. The overall classification accuracies of 87.75% and 80.41% are achieved for the time-series data over the Indian and Canadian test sites, respectively. However, for the day-wise data, a ∼6% decrease in the overall accuracy is observed for both the classifiers.  相似文献