Gravitational field routing strategy considering the distribution of traffic flow

Traffic flow transmission is a constantly important aspect of complex networks, geographical information science, and other science and engineering fields. Previous studies have shown that vehicle flow is more strongly correlated with morphological properties of streets than those of axial lines. In addition, street-based topological representations are more suitable for vehicle flow prediction, as well as more memory-oriented and global in nature. In this study, we construct a dual graph to represent the street–street relationship and propose a routing strategy for networks on the basis of gravitational field theory. We aim to diminish traffic congestion and enhance the transmission performance of networks. We borrow from gravitational field theory in establishing a gravitational field stimulated by a node in packet transmission and in defining the corresponding gravitational field equation. On the basis of this study, we present a mathematical model and a routing strategy. Experimental results indicate that compared with the shortest path routing strategy, the proposed method considerably enhances network capacity and effectively balances network traffic flow, especially for congested networks. We achieve critical gravitation that can always maximize network capacity, regardless of the values of other parameters.     

Split-Match-Aggregate (SMA) algorithm: integrating sidewalk data with transportation network data in GIS

Sidewalk geodata are essential to understand walking behavior. However, such geodata are scarce, only available at the local jurisdiction and not at the regional level. If they exist, the data are stored in geometric representational formats without network characteristics such as sidewalk connectivity and completeness. This article presents the Split-Match-Aggregate (SMA) algorithm, which automatically conflates sidewalk information from secondary geometric sidewalk data to existing street network data. The algorithm uses three parameters to determine geometric relationships between sidewalk and street segments: the distance between streets and sidewalk segments; the angle between sidewalk and street segments; and the difference between the lengths of matched sidewalk and street segments. The SMA algorithm was applied in urban King County, WA, to 13 jurisdictions’ secondary sidewalk geodata. Parameter values were determined based on agreement rates between results obtained from 72 pre-specified parameter combinations and those of a trained geographic information systems (GIS) analyst using a randomly selected 5% of the 79,928 street segments as a parameter-development sample. The algorithm performed best when the distances between sidewalk and street segments were 12 m or less, their angles were 25° or less, and the tolerance was set to 18 m, showing an excellent agreement rate of 96.5%. The SMA algorithm was applied to classify sidewalks in the entire study area and it successfully updated sidewalk coverage information on the existing regional-level street network data. The algorithm can be applied for conflating attributes between associated, but geometrically misaligned line data sets in GIS.     

A fine-grained perspective on the robustness of global cargo ship transportation networks

The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System (AIS) data available. First, we subdivide three typical cargo ship transportation networks (i.e., oil tanker, container ship and bulk carrier) from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks (i.e., degree-based attack, betweenness- based attack and flux-based attack) to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1) compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2) different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3) small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation system.     

Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data

Geographically weighted regression (GWR) is an important local technique for exploring spatial heterogeneity in data relationships. In fitting with Tobler’s first law of geography, each local regression of GWR is estimated with data whose influence decays with distance, distances that are commonly defined as straight line or Euclidean. However, the complexity of our real world ensures that the scope of possible distance metrics is far larger than the traditional Euclidean choice. Thus in this article, the GWR model is investigated by applying it with alternative, non-Euclidean distance (non-ED) metrics. Here we use as a case study, a London house price data set coupled with hedonic independent variables, where GWR models are calibrated with Euclidean distance (ED), road network distance and travel time metrics. The results indicate that GWR calibrated with a non-Euclidean metric can not only improve model fit, but also provide additional and useful insights into the nature of varying relationships within the house price data set.     

Performance analysis of radial basis function networks and multi-layer perceptron networks in modeling urban change: a case study

The majority of cities are rapidly growing. This makes the monitoring and modeling of urban change’s spatial patterns critical to urban planners, decision makers, and environment protection activists. Although a wide range of methods exists for modeling and simulating urban growth, machine learning (ML) techniques have received less attention despite their potential for producing highly accurate predictions of future urban extents. The aim of this study is to investigate two ML techniques, namely radial basis function network (RBFN) and multi-layer perceptron (MLP) networks, for modeling urban change. By predicting urban change for 2010, the models’ performance is evaluated by comparing results with a reference map and by using a set of pertinent statistical measures, such as average spatial distance deviation and figure of merit. The application of these techniques employs the case study area of Mumbai, India. The results show that both models, which were tested using the same explanatory variables, produced promising results in terms of predicting the size and extent of future urban areas. Although a close match between RBFN and MLP is observed, RBFN demonstrates higher spatial accuracy of prediction. Accordingly, RBFN was utilized to simulate urban change for 2020 and 2030. Overall, the study provides evidence that RBFN is a robust and efficient ML technique and can therefore be recommended for land use change modeling.     

中国铁路客运流联结的城市时间可达性

基于中国铁路客户服务中心提供的客运流数据,采集全国地级以上行政单元(未含港澳台数据)间铁路客运运行的最短历时,基于GIS网络分析和空间分析等方法,选取时间可达性和一日交流圈2个指标对城市可达性进行测度和分析。研究发现:①城市时间可达性水平划分为7个级别,在空间上呈现中心-外围式圈层结构,中心区域沿铁路干线和高速铁路线轴向扩展,廊道效应明显,东部、中部地区的城市时间可达性优于西部地区。②城市之间的时间可达性小于2.0 h的城市对在空间上构成了由京广、京沪、京哈、京福、杭深、青太、徐兰、沪汉蓉、沪昆、广昆等高速铁路连接的"五纵五横"带状分布格局。时间可达性小于10.0 h的城市对覆盖了"胡焕庸线"东南部的大部分区域,城市带转为城市网络。③直辖市、省会/首府城市一日交流圈以31个城市为中心,按照时间可达性由小到大呈现轴向扩展,廊道效应明显。基于城市一日交流圈划分了19个城市群和拉萨城市圈,为城市群的划分提供方法借鉴。     

不同出游时间视角下游客流动网络结构及其分异特征——以西安市为例

以热门旅游城市西安市为研究区域,采集网络游记数据,综合运用社会网络分析和GIS空间分析方法,探讨不同出游时间下的游客流动网络结构及其分异特征,研究发现：① 不同的出游时间约束下,游客旅游出行行为表现出显著的时间异质性。② 基于游客流动的西安市旅游吸引物的节点结构具有显著的等级规模分异特征,随着出游时间的增加,旅游节点等级结构体系呈现出以高等级景点为枢纽的“强强”关联特征,高等级景点的游客集聚功能提升显著。③ 随着出游时间增加,西安市区旅游节点核心?边缘结构越明显,核心区的节点联系强度越大,区位邻近、知名度接近与交通便利是形成景点组团的关键因子。     

An Indoor Routing Algorithm for the Blind: Development and Comparison to a Routing Algorithm for the Sighted

This paper presents a prototypical implementation of a non‐network‐based indoor routing algorithm for the sighted and the blind. The spatial abilities of the visually impaired are discussed. Former approaches of outdoor navigation systems for the blind are analyzed and deemed inappropriate for the purpose of modeling indoor navigation. The proposed routing algorithm for the blind calculates routes based on physical characteristics of traveling with a long cane. The algorithm distinguishes between clues, landmarks, obstacles, and hazards along the feasible paths and selects the optimal route by trading off distance and the number of landmarks and clues along a route. Subsequently, the routes for the blind are compared to routes calculated by the routing algorithm for the sighted. The paper asserts that the proposed indoor routing algorithm leads to more suitable routes for the blind.     

中国春运人口省际流动的时空与结构特征

本文通过构建人口省际流动的关系矩阵,透视2015年中国春节期间人口省际流动的动态过程、网络特征,并对各省人口流入、流出的规模差异进行测度。研究结论如下：①春节前后中国各省每日人口净流入人次存在显著的规律性特征,2月13-17日和2月25日-3月1日为各省节前返乡流和节后返工流期间人口净流入、流出峰值时段,可作为基于春运研究中国人口省际流动的重要依据;②识别了14个人口净流入省、17个人口净流出省,净流入位序前六省和后八省分别吸纳和提供了全国9成人口的集聚与扩散。人口主要流入省的沿海绵延和主要流出省的中部“人口塌陷”共同构成了双纵格局;③各省流出首位流的指向特征显著,南方人口流出省的流出指向存在共性,京津、长三角、珠三角地区的人口集聚路径存在差异。④移动数据为发掘人口流动过程中蕴含的丰富信息提供了平台,基于节后、节前净流入值差值的方法可以有效识别中国人口流动的规模差异、属性特征。通过与以往研究对比,证实了移动数据与基于人口普查数据研究的诸多结论相似性。     

多元交通视角下异质旅游流分布特征及其空间共轭关系

异质性是旅游流研究亟待拓展的内容。以北京、武汉和西安为案例客源地,基于2017年获取的城市居民出游行为大样本问卷数据,利用数理统计法、地图分析法等方法,从客源地视角对自驾车、火车、飞机3种交通方式旅游流的分布特征进行研究,研究发现：① 随着出游交通时间的增加,自驾旅游流呈指数衰减,火车和飞机旅游流呈正偏态分布。② 3种交通方式旅游流的空间分布格局存在差异。自驾高到访率区域围绕在客源城市周围;火车与飞机高到访率区域远离客源城市。③ 不同交通方式黄金出游空间具有共轭性,距客源城市球面距离0~400 km区域为自驾黄金出游空间,400~1 200 km乘火车（包括动车和高铁）6.00 h可达区域为火车黄金出游空间,1 200~2 600 km区域为飞机黄金出游空间。基于研究结果,提出了异质交通方式黄金出游空间共轭模型,刻画了自驾车、火车、飞机3种主要交通方式黄金出游空间的位置和共轭关系。     

城市旅游流网络结构特征及其影响因素

目前对于旅游流网络形成的影响因素的研究多为区域尺度,因此以上海为例,将国内游客赴上海自由行作为对象,利用网络游记采集2018年上海自由行行程信息,扩充了对旅游节点类型的选取范围,结合社会网络分析法,构建有向旅游流网络,研究国内游客赴上海自由行所形成的旅游流网络结构特征,并通过回归分析研究其影响因素。结果表明,①网络密度较低,网络核心-边缘区结构分层明显,但核心区对边缘区的带动能力有待提高;②目前以核心城区的著名景点以及上海迪士尼乐园为核心旅游节点;③整体而言,网络中旅游节点重要程度的影响因素为核心节点的影响力、旅游节点自身的知名度以及交通便利程度。在此基础上提出了旅游节点应如何提高自身在网络中的重要程度或是融入网络。     

跨界生产网络的组织治理模式——以苏州地区信息电子业台商为例

以最近8年内在苏州地区投资设厂的信息电子业台商为例,分析其本地集聚的供应链的企业间交易关系的本质和组织网络的治理模式,以探讨全球生产网络的地域性集聚的经济地理意义,以及企业组织间的治理结构对地方发展的影响。指出这一轮信息电子业台商的跨界投资基本上强化台湾代工厂商与品牌大厂之间的策略性合作,然而台商生产网络的跨界扩展也交织着企业组织间的权力运作,导致生产网络的治理模式发生改变并形成了空间集聚的动力。研究显示,从全球生产网络的厂商间交易治理结构出发的分析视角有助于理解区域发展的机会与限制,而就发展中国家由全球生产网络之跨界转移所形成的新工业空间而言,经济地理学所强调的厂商间具有地理邻近特征的"互赖性"并不能脱离全球商品链所内含的不对称权力关系。     

考虑东北航线的亚欧LNG运输发展潜力研究

北极海冰的加速消融为北极航线的开发利用带来了机遇,北极地区的经济价值凸显。北极东北航线为亚欧间的LNG运输提供了新的运输通道。为使亚欧间的LNG运输更为经济合理,基于海运里程和单船必要运费率两方面比较通过北极东北航线、苏伊士运河航线、好望角航线进行跨亚欧LNG运输的经济性。在此基础上,采用负指数网络配流方法计算不同路径的配流比例,研究东北航线的亚欧间LNG运输发展潜力。结果表明,整体而言,采用东北航线进行跨亚欧LNG运输的海运里程更短,单船必要运费率更低,配流比例更高,其中,日本袖浦使用东北航线的经济性最为显著。将跨亚欧LNG运输通道的经济性分析和交通分配相结合,为亚洲地区更为经济合理地进行LNG运输提供参考。     

Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

长江三角洲公路网络的可达性空间格局及其演化

以加权平均旅行时间为指标,1986年、1994年、2005年为时间断面,探讨了长江三角洲地区公路网络中主要节点城市可达性空间格局及其演化规律,并结合公路货运特征 (货运量区位商) 分析了各节点可达性水平对其发展的影响。结果显示：研究期内,可达性空间格局总体变动不大,其值以上海、苏州、嘉兴为中心向外围呈不规则环状增高;公路网络的逐步完善极大地提高了区域内主要城市间的可达性,但不同阶段可达性演化特征不同,第二阶段 (1994~2005年) 可达性提升较之第一阶段 (1986~1994年) 更为显著;可达性值变化幅度与初始值有关,可达性值变率在第一阶段由北往南逐渐降低,而在第二阶段呈多极格局;随路网的不断完善,可达性水平由中心向外围呈圈层式优化;多数城市可达性状况优于平均水平,各节点城市相对可达性在第一阶段变化不大,但分布趋向于不均衡,第二阶段改变较大并趋于均衡分布;各节点城市可达性对其发展的影响可分为良好支撑、相对制约和基本适应三种类型。     

中国城市网络等级结构特征及组织模式——基于铁路和航空流的比较

交通流是反映城市间社会经济联系的重要表征,被广泛应用于城市网络研究中。基于2010年中国城际铁路与航空客流OD数据,本文从城市节点、流量、子网络视角对中国城市网络的结构特征与组织模式进行了比较研究,发现：① 铁路与航空流视角下的中国城市网络均呈现出以北上广为顶层节点的空间等级结构体系,但除顶层结构外两种网络结构差异较大。② 城市网络体系中的铁路流联系表现出空间邻近性特征,而航空流联系则主要受到城市节点的规模大小与职能属性的影响。③ 铁路流的首位联系受省级行政区划的制约,航空流的首位联系空间跨度大,形成了若干具有垂直层间联系的地域子系统。④ 铁路网络拥有具有显著地域特征的7个子网络,而航空网络中则不存在明显的子网络。技术经济特征与管理体制是造成铁路与航空两种网络特征差异的主要原因。     

改进型BP神经网络对民勤绿洲地下水位的模拟预测

以具有代表性的民勤绿洲为研究对象,以Matlab7.0为工作平台,对沙漠绿洲地下水埋深预测的三层前馈神经网络（BP神经网络）进行了改进。输入端因子选取民勤绿洲逐月灌溉量、红崖山水库下泄水量、月降水量、月蒸发量（20 cm）、月平均气温、时间序列6项,输出因子为民勤绿洲地下水位。通过在模型的输入层增加时间序列引导因子的方法使BP神经网络对输入端数据具备时间敏感性;通过Levenberg-Marquardt算法使网络误差最小化,并配合Bayesian正则化使网络的误差平方和、网络权重以及阈值平方和实现最优组合,最后使用相关系数、相对误差、效率系数等指标对模型的模拟结果进行检验。结果表明,通过以上一系列改进可以有效提高模型的模拟精度,增强模型的稳定性,并使模型具有良好的“泛化性”。     

Sediment concentration changes in runoff pathways from a forest road network and the resultant spatial pattern of catchment connectivity

Hydrological connectivity is a term often used to describe the internal linkages between runoff and sediment generation in upper parts of catchments and the receiving waters. In this paper, we identify two types of connectivity: direct connectivity via new channels or gullies, and diffuse connectivity as surface runoff reaches the stream network via overland flow pathways. Using a forest road network as an example of a landscape element with a high runoff source strength, we demonstrate the spatial distribution of these two types of linkages in a 57 km² catchment in southeastern Australia. Field surveys and empirical modelling indicate that direct connectivity occurs primarily due to gully development at road culverts, where the average sediment transport distance is 89 m below the road outlet. The majority of road outlets were characterised by dispersive flow pathways where the maximum potential sediment transport distance is measured as the available hillslope length below the road outlet. This length has a mean value of 120 m for this catchment. Reductions in sediment concentration in runoff plumes from both pathways are modelled using an exponential decay function and data derived from large rainfall simulator experiments in the catchment. The concept of the volume to breakthrough is used to model the potential delivery of runoff from dispersive pathways. Of the surveyed road drains (n=218), only 11 are predicted to deliver runoff to a stream and the greatest contributor of runoff occurs at a stream crossing where a road segment discharges directly into the stream. The methodology described here can be used to assess the spatial distribution and likely impact of dispersive and gullied pathways on in-stream water quality.     

Landslide susceptibility evaluation based on BPNN and GIS: a case of Guojiaba in the Three Gorges Reservoir Area

A landslide susceptibility evaluation is vital for disaster management and development planning in the Yangtze River Three Gorges Reservoir Area. In this study, with the support of remote sensing and Geographic Information System, 4 factor groups comprising 10 separate subfactors of landslide-related data layers were selected to establish a susceptibility evaluation model based on the back-propagation neural network including slope, aspect, plan curvature, strata and lithology, distance to faults, land use/land cover, Normalized Difference Vegetation Index, Normalized Difference Water Index, distance from roads, and effect of rivers. During model development, a three-layered interconnected neural network structure of 10 (input layer) × 20 (hidden layer) × 1 (output layer) was used for evaluating the landslide susceptibility in Guojiaba. At the same time, a back-propagation algorithm was applied to calculate the weights between the input layer and the hidden layer and between the hidden layer and the output layer. The results showed that the effect of slope has the highest weight value (0.2051), which is more than two times that of the other factors, followed by strata and lithology (0.1213) and then the effect of rivers (0.1201). At the end of the susceptibility evaluation, the area was divided into four zones such as very high, high, moderate and low susceptibility. For verification, the receiver operating characteristic curve for the back-propagation neural network-derived landslide susceptibility evaluation model was drawn, and the results showed that the area under the receiver operating characteristic curve was 0.8790 and the prediction accuracy was 88%. Furthermore, the results obtained from this article were then verified by comparing with the existing landslide historical data and multiple field-verified results. Lastly, the landslide susceptibility map will help decision makers in risk management, site selection, site planning, and the design of control engineering.     

Vertical structure of the head of a cylindrical mantle plume from a model of two-phase flow with melting

Within the mushroom-shaped head of a cylindrical mantle plume melting occurs, the melt segregates from the matrix, and the matrix deforms and spreads laterally. These processes have been studied with a model of two-phase flow with melting. After characteristics of the solution near the axis of symmetry of the plume were found, a set of asymptotic relations for the variables along the symmetry axis was derived from McKenzie's equations for conservation of mass, momentum and energy of a two-phase system. The distribution of porosity along the plume axis and the vertical and radial segregation velocity of the melt in the vicinity of the axis of symmetry were obtained as functions of depth. Our analytic results show that within the head of a cylindrical mantle plume the contribution of the deformation of the matrix to the total non-hydrostatic pressure gradient cannot be neglected, and melt convergence or divergence is controlled by the radial scale of the upward velocity profile at the depth of the beginning of melting.