珠三角流动人口的代际就业结构分异及影响因素——基于六城市的调查分析     

张晓菲  张国俊  周春山 《热带地理》2020,40(5):821-831

基于珠三角六城市流动人口的问卷调查数据，划分流动人口就业类型，从职业布局和多样化指数的角度比较了新生代、中生代和老一代三代流动人口职业结构差异，利用无序多分类Logistic模型对影响因素进行探究。研究发现：1）珠三角流动人口整体就业水平不高，就业结构在代际间分异明显。新生代在技术型就业和公司文员型就业上表现出优势，中生代在各行业就业相对均衡，老一代多被束缚在以体力劳动为主的基础型部门；就业多样化水平随代际的升高而下降。2）代际就业结构的影响因素及影响方式存在共性和差异，共性因子为受教育程度、月薪水平和性别；外出务工时间正向影响新生代服务型和管理型就业，工作环境稳定的职业对已婚新生代更具吸引力，中生代对户籍和工作保障因子更为敏感。政府可从代际就业特征出发，为流动人口制定有针对性的就业政策；针对就业市场中女性和农村户籍人口的弱势地位，为其提供就业引导，创造健康的就业环境，提高流动人口整体就业水平。  相似文献   

Detecting regional dominant movement patterns in trajectory data with a convolutional neural network     

Can Yang  Győző Gidófalvi 《International journal of geographical information science》2020,34(5):996-1021

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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   

基于深度域地震成像的中沙海槽盆地东北部结构构造研究     

赵斌  高红芳  张衡  李丽青 《热带海洋学报》2019,38(2):95-102

文章基于叠前深度偏移地震成像分析, 结合前人重磁反演等地球物理资料成果, 对中沙海槽盆地东北部结构构造进行探索研究。研究表明: 中沙海槽盆地东北部发育新生代地层, 厚度在1500~2500m之间, 地层层速度为1500~ 3500m·s^-1, 不存在中生界沉积层, 盆地基底为海山或前寒武系基岩及岩浆岩隆起。中沙海槽盆地新生代陆源海相烃源岩丰富, 盆地新生界地层厚度大, 盆地凹陷、断裂发育, 具有一定的油气勘探潜力。  相似文献   

可可西里岩石圈向北俯冲到柴达木地幔的地震学证据          下载免费PDF全文

赵荣涛  赵文津  史大年  刘志伟  杨艳 《地球物理学报》2020,63(8):2940-2953

利用中美德INDEPTH IV合作项目2007—2009年间布置于青藏高原中、北部140个宽频地震台站记录到的天然地震数据,经过接收函数成像处理,获得了3条穿过昆仑—阿尼玛卿缝合带清晰的壳幔结构图像.结果显示柴达木南缘莫霍面位于约50 km深度,羌塘地块、可可西里地块、东昆仑造山带莫霍面位于约65 km深度,昆仑—阿尼玛卿缝合带以北约50 km存在莫霍面深度突变.在可可西里和柴达木岩石圈地幔之间观测到北倾界面,这可能是可可西里岩石圈向北俯冲到柴达木地幔之下的证据.可可西里地块地壳内宽缓的负转换震相带是低速带的反映,其向北挤入到东昆仑山下发生挤压增厚,可能是东昆仑山隆升的原因;由于刚性柴达木岩石圈的阻挡,物质向东改向,则可能是该地区向东旋转的构造应力场产生的原因.本文研究结果不支持亚洲岩石圈地幔在东昆仑—柴达木交界处向南俯冲,据此,我们提出了新的东昆仑造山模式.  相似文献   

基于表层岩土渗透对三峡井网井水位降雨影响的精准分析          下载免费PDF全文

周洋  吴艳霞  罗棋  李查玮 《地震工程学报》2020,42(2):460-467,528

为研究三峡井网表层岩土渗透对井水位降雨的影响,采取井区表层岩土垂向渗透性测试方法试验,测得表层岩土垂向渗透性,并建立数学模型,用于降雨渗入补给分析。在此模型基础上,通过三峡井网8口井水位、气象三要素的对比观测资料对井水位日动态、月动态、年动态的影响进行精准分析与验证。结果表明:这种影响的特征是相当复杂的,同一个降雨过程在不同井上产生的影响特征不同,这一方面可能与各井的水文地质条件不同有关,另一方面可能还与各井点的降雨过程的差异也有关。  相似文献   

Moving from plot-based to hillslope-scale assessments of savanna vegetation structure with long-range terrestrial laser scanning (LR-TLS)     

《International Journal of Applied Earth Observation and Geoinformation》2020

Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide.  相似文献   

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification,visual interpretation and machine learning approaches     

《International Journal of Applied Earth Observation and Geoinformation》2020

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected.  相似文献   

路网约束条件下热力规则设计与试验     

杜晓  周玉秀  周琦  郑义  张俊辉  林尚纬  陈利军 《测绘通报》2020,(7):18-21

热力图是一种能直观准确展示空间观测值的有效工具，在多个领域具有广泛应用。本文在分析设定不同道路层权重、道路技术等级分类的基础上，以反距离权重、直方图均衡化、密度补偿、参数多次迭代等方法，研究构建了以热力方式展示道路网分布及发达程度的相关规则体系。热力规则通过道路赋权、路线曲面化、密度协调、图面综合等多套规则的有机结合，实现了道路网总体发达水平信息的提取与展示，并以全球地理信息资源建设项目路网成果中的亚洲和非洲部分国家数据为例，进行了信息提取与热力分布试验。  相似文献   

沿107.6°E南北向剖面鄂尔多斯地块及周缘地区地壳结构          下载免费PDF全文

陈洁  陈永顺  郭震  杨挺 《地球物理学报》2020,63(7):2592-2604

鄂尔多斯地块紧邻青藏高原东北缘,位于华北克拉通的西部,在我国中生代、新生代以来东部地区的构造活动中起到了重要作用.对鄂尔多斯及其周缘地区的研究可以提供有关华北克拉通的形成、演化和破坏过程的重要信息.本文选取了纵贯鄂尔多斯的107.6°E附近南北剖面上的44个流动地震台站进行分析,采用接收函数方法,进行Kirchhoff偏移成像,并且结合在该区域内前人的地震面波频散进行联合反演,获得剖面下方的地壳内部精细结构.研究结果显示:(1)莫霍面在鄂尔多斯北部较平缓,约45km深;在鄂尔多斯南部有所加深,达到50km;其北边的河套盆地的地壳厚度约为50km;南边的渭河盆地到秦岭地区及四川盆地的地壳厚度从约为40km增厚到47～50km.(2)河套盆地下方存在大规模的低速异常,最深可达25km,反映了其显著的拉张构造和沉积历史.(3)秦岭造山带下方的低速异常对应于其主要为长英质的地壳组分,可能是由于中生代的拆沉作用导致的地壳下部基性岩石层的缺失.(4)以38°N为界的鄂尔多斯地块,南北部地壳速度结构存在差异,可能表明了这两部分经历的构造历史不同.  相似文献