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1.
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   
2.
本文提出了一种基于纹理特征的围填海SAR图像分水岭分割方法,首先对机载MiniSAR图像进行灰度共生矩阵纹理滤波,获得纹理特征图像,再对纹理特征图像进行分水岭算法分割,将获得的形态学重建图像进行门限阈值分割,得到最后的二值化分割结果。该方法一方面通过调整灰度共生矩阵纹理滤波的窗口大小,抑制了斑点噪声的影响;另一方面,利用分水岭算法对边缘模糊杂乱图像的优势,提高了围填海信息提取的准确性。实验结果表明,本方法对高分辨率SAR图像围填海监测图像的分割效果良好。  相似文献   
3.
hairy作为成对控制基因参与果蝇等体节动物的体节形成;体节极性基因hedgehog是节肢动物和环节动物体节边界维持的关键基因。本研究分析了单环刺螠hairy的序列特征以及hairy和hedgehog在其幼虫体节发生过程中的时空表达特征,结果显示:单环刺螠Hairy序列中含有保守的HLH结构域、Hairy_orange结构域和四肽WRPW;其mRNA在早期体节幼虫中的表达量显著高于晚期担轮幼虫,并且定位于每个体节的边界处。单环刺螠hedgehog mRNA在体节幼虫中的表达水平显著高于早期体节幼虫,并且呈现保守的体节边界表达特征。研究结果表明,hairy和hedgehog在单环刺螠幼虫体节中的表达图式与小头虫等典型体节动物中的表达图式基本一致。  相似文献   
4.
Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.  相似文献   
5.
多源地理空间矢量数据关联分析   总被引:1,自引:1,他引:0  
针对多源地理空间矢量数据多来源、难以集成综合利用这一现状,本文提出了多源地理空间矢量数据关联方法,并以此为基础构建了多源地理空间矢量数据关联的可视与计算查询系统。首先,对多源地理空间矢量数据关联的概念及分类进行了定义。然后,以此为基础,提出了关联关系构建技术:自适应四叉树编码技术、扫描线技术、几何匹配及语义匹配技术。最后,为实现关联关系的直观展示,设计了原型系统。关联技术的提出可建立起多源地理空间矢量数据之间的关联关系,原型系统的构建也为用户综合利用多源地理空间矢量数据提供了平台,提高了数据的利用率及数据查询的效能。  相似文献   
6.
本文选取成都市某一区域建筑物A、B为研究对象,采用分辨率为0.61 m的Quick bird影像,运用图像分割法和LVQ神经网络算法,提取建筑物侧面信息,根据假设法原理,构建高度计算物理模型,求取建筑物高度。对比实测数据,结合可能影响实验结果的实地因素、遥感影像因素进行精度分析与评价,探讨基于高分遥感影像的建筑物侧面信息提取和高度计算的方法。结果表明,LVQ神经网络算法在建筑物侧面提取和高度计算中有更好的应用价值,精度高达94%。  相似文献   
7.
A most fundamental and far-reaching trait of geographic information is the distinction between extensive and intensive properties. In common understanding, originating in Physics and Chemistry, extensive properties increase with the size of their supporting objects, while intensive properties are independent of this size. It has long been recognized that the decision whether analytical and cartographic measures can be meaningfully applied depends on whether an attribute is considered intensive or extensive. For example, the choice of a map type as well as the application of basic geocomputational operations, such as spatial intersections, aggregations or algebraic operations such as sums and weighted averages, strongly depend on this semantic distinction. So far, however, the distinction can only be drawn in the head of an analyst. We still lack practical ways of automation for composing GIS workflows and to scale up mapping and geocomputation over many data sources, e.g. in statistical portals. In this article, we test a machine-learning model that is capable of labeling extensive/intensive region attributes with high accuracy based on simple characteristics extractable from geodata files. Furthermore, we propose an ontology pattern that captures central applicability constraints for automating data conversion and mapping using Semantic Web technology.  相似文献   
8.
针对智能优化图像分割算法易陷入局部最优、分割精度不高等问题,本文融合改进的分数阶达尔文粒子群算法和二维Renyi熵多阈值,提出了一种新的多阈值遥感图像分割算法。算法利用粒子自身进化信息来定义进化因子,结合进化因子并利用高斯图函数调整分数阶次α系数以实现精确计算和快速收敛;根据局部最优概率因子对局部最优位置进行Levy飞行随机扰动以提高算法跳出局部最优的能力;同时将二维Renyi熵单阈值扩展到多阈值分割上,并结合改进的分数阶达尔文粒子群算法,将二维Renyi熵多阈值应用于遥感图像分割中。仿真结果表明,与其他2种智能优化分割算法相比,本文分割算法在细节处理和分割精度上均有明显优势,在PRI上至少提升7.27%、VOI至少降低6.5%、GCE至少降低10.4%。  相似文献   
9.
Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.  相似文献   
10.
刘亢  李岩峰  郭辉文  张迎峰 《地质学报》2021,95(8):2346-2360
1948年川西理塘M7. 3地震是川滇菱形块体内部近一个世纪以来发生的震级最大的走滑型地震。在对此次同震地表破裂进行详细调查基础上,利用差分GPS对同震地表破裂带进行了精确测量与统计分析。结果揭示该地表破裂的现存长度为36 km,北端始于无量河以北,往东南沿藏坝盆地北东缘、德巫盆地东南缘,延伸至德巫乡北,分为南、北两段,而在交德附近存在约3 km长的地表破裂空区。对同震地表破裂的线密度和同震水平位错量进行分段统计后揭示,此次地震的宏观震中应位于德巫盆地中部交德东南约4~5 km处。对理塘同震地表破裂的Riedel剪切分析结果指示,该破裂带主要由R剪切组成,以发育雁列状排列的挤压鼓包(Push- up)为主要特征,伴有少量R′剪切与T裂缝,缺少P型与X型剪切。其中R剪切占95%以上,其在藏坝段(北段)的优势方向为318°,德巫段(南段)为315°,整条地表破裂带的R剪切平均方向为316°。同时发现,此次地震形成的雁列状挤压鼓包主要以平缓的“弧形”为主,这与1981年道孚MS 6. 9地震和2010年玉树MS 7. 1地震地表破裂带中出现大量反“S”形挤压鼓包有所不同,推断与走滑断裂滑动速率密切相关。沿强滑动速率走滑断层地震破裂带的Riedel剪切发育会更为完善,挤压鼓包也更发育,易形成反“S”形,反之则以平缓的“弧形”为特征。综合分析认为,1948年理塘同震地表破裂带的展布主要受藏坝盆地与德巫盆地控制,而且藏坝段(北段)与德巫段(南段)的R剪切方向存在偏差,这可能与两个拉分盆地的发育程度有关。  相似文献   
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