Integration of linear and areal hierarchies for continuous multi-scale representation of road networks

Spatial data can be represented at different scales, and this leads to the issue of multi-scale spatial representation. Multi-scale spatial representation has been widely applied to online mapping products (e.g., Google Maps and Yahoo Maps). However, in most current products, multi-scale representation can only be achieved through a series of maps at fixed scales, resulting in a discontinuity (i.e., with jumps) in the transformation between scales and a mismatch between the available scales and users' desired scales. Therefore, it is very desirable to achieve smoothly continuous multi-scale spatial representations. This article describes an integrated approach to build a hierarchical structure of a road network for continuous multi-scale representation purposes, especially continuous selective omission of roads in a network. In this hierarchical structure, the linear and areal hierarchies are constructed, respectively, using two existing approaches for the linear and areal patterns in a road network. Continuous multi-scale representation of a road network can be achieved by searching in these hierarchies. This approach is validated by applying it to two study areas, and the results are evaluated by both quantitative analysis with two measures (i.e., similarity and average connectivity) and visual inspection. Experimental results show that this integrated approach performs better than existing approaches, especially in terms of preservation of connectivity and patterns of a road network. With this approach, efficient and continuous multi-scale selective omission of road networks becomes feasible.     

Selective omission of road features based on mesh density for automatic map generalization

Selection of roads is an intractable generalization operation due to the difficulty in retaining the density difference and connectivity of a road network. This paper proposes a novel approach of selective omission for roads based on mesh density. The density of a road network and its local variations are calculated using meshes as units. Since maps at different scales usually reveal different densities, different density thresholds for road networks are determined on the basis of theoretical analysis and empirical study of mesh densities on maps at different scales. The selection process starts with the identification of the meshes that have a density beyond the threshold. The mesh with the largest density is first treated. Its bounding road segments are ordered according to their relative importance. The least important segment is eliminated. The remaining segments are then merged with the adjacent mesh, thus forming a new mesh. The selection procedure is repeated until none of the meshes has a density beyond the threshold. Such a process of eliminating road segments and merging meshes can ensure the road network connectivity. In this study, the meshes are classified depending on the types of road segment. For the different mesh types, their density thresholds are set to be different, which can be used as an indicator for the preservation of the density difference. This proposed approach considers topological, geometric and semantic properties of the road network. It was applied to two sets of road networks, and the results of selection are convincing. This methodology has now been adopted for the updating of 1:50,000 maps of China.     

Image‐based quality assessment of road databasesX

In this paper an approach to the automatic quality assessment of existing geo‐spatial data is presented. The necessary reference information is derived automatically from up‐to‐date digital remotely sensed images using image analysis methods. The focus is on the quality assessment of roads as these are among the most frequently changing objects in the landscape. In contrast to existing approaches for quality control of road data, the data to be assessed and the objects extracted from the images are modelled and processed together. A geometric‐topologic relationship model for the roads and their surroundings is defined. Context objects such as rows of trees support the quality assessment of road vector data as they may explain gaps in road extraction. The extraction and explicit incorporation of these objects in the assessment of a given road database give stronger support for or against its correctness.

During the assessment existing relations between road objects from the database and extracted objects are compared to the modelled relations. The certainty measures of the objects are integrated into this comparison. Normally, more than one extracted object gives evidence for a road database object; therefore, a reasoning algorithm which combines evidence given by the extracted objects is used. If the majority of the total evidence argues for the database object and if a certain amount of this database object is covered by extracted objects, the database object is assumed to be correct, i.e. it is accepted, otherwise it is rejected. The procedure is embedded into a two‐stage graph‐based approach which exploits the connectivity of roads and results in a reduction of false alarms. The algorithms may be incorporated into a semi‐automatic environment, where a human operator only checks those objects that have been rejected.

The experimental results confirm the importance of the employed advanced statistical modelling. The overall approach can reliably assess the roads from the given database, using road and context objects which have been automatically extracted from remotely sensed imagery. Sensitivity analysis shows that in most cases the chosen two‐stage graph‐approach reduces the number of false decisions. Approximately 66% of the road objects have been accepted by the developed approach in an extended test area, 1% has been accepted though incorrect. Those false decisions are mainly related to the lack of modelling road junction areas.     

Robust inferences of travel paths from GPS trajectories

Monitoring and predicting traffic conditions are of utmost importance in reacting to emergency events in time and for computing the real-time shortest travel-time path. Mobile sensors, such as GPS devices and smartphones, are useful for monitoring urban traffic due to their large coverage area and ease of deployment. Many researchers have employed such sensed data to model and predict traffic conditions. To do so, we first have to address the problem of associating GPS trajectories with the road network in a robust manner. Existing methods rely on point-by-point matching to map individual GPS points to a road segment. However, GPS data is imprecise due to noise in GPS signals. GPS coordinates can have errors of several meters and, therefore, direct mapping of individual points is error prone. Acknowledging that every GPS point is potentially noisy, we propose a radically different approach to overcome inaccuracy in GPS data. Instead of focusing on a point-by-point approach, our proposed method considers the set of relevant GPS points in a trajectory that can be mapped together to a road segment. This clustering approach gives us a macroscopic view of the GPS trajectories even under very noisy conditions. Our method clusters points based on the direction of movement as a spatial-linear cluster, ranks the possible route segments in the graph for each group, and searches for the best combination of segments as the overall path for the given set of GPS points. Through extensive experiments on both synthetic and real datasets, we demonstrate that, even with highly noisy GPS measurements, our proposed algorithm outperforms state-of-the-art methods in terms of both accuracy and computational cost.     

Computing a hierarchy favored optimal route in a Voronoi-based road network with multiple levels of detail

This paper introduces a robust method for computing the optimal route with hierarchy. We convert a planar road network into its Voronoi-based counterpart with multiple levels of detail (LoDs), which is subsequently assigned travel times that are estimated for different times of day using taxicab trajectory data. On the basis of this network structure, we model the path-finding process in travel, as the optimal route with hierarchy is computed in a ‘coarse-to-fine’ manner. In other words, the route is iteratively constructed from roads in a low LoD network to roads in a high LoD network. To confirm the efficiency and effectiveness of our method, comparative experiments were conducted using randomly selected pairs of origins/destinations in Wuhan, China. The results indicate that our travel lengths are on average 12% longer than those computed by the Dijkstra algorithm and 15% shorter than those computed by the hierarchical algorithm (in ArcGIS). Our travel times are on average 29% longer than those computed by the Dijkstra algorithm and 31% shorter than those computed by the hierarchical algorithm (in ArcGIS). Hence, we argue that our method is situated in terms of performance between the Dijkstra algorithm and the hierarchical algorithm (in ArcGIS). Moreover, road usage patterns confirm that our algorithm is cognitively equivalent to the hierarchical algorithm (in ArcGIS) by favoring high-class roads and outperforms the Dijkstra algorithm by avoiding choosing low-class roads. Computationally, our method outperforms the Dijkstra algorithm but is on the same level as the hierarchical algorithm (in ArcGIS) in terms of efficiency. Therefore, it has the potential to be used in real-time routing applications or services.     

从Google Maps看我国全球化地理信息服务面临的挑战和对策

以Google Maps为代表的地图服务的推出预示着全球化地理信息服务的开始。IT领域竞争市场的形成、高分辨率卫星影像的应用及Web地理信息服务开发平台的实现是全球化地理信息服务的主要趋势。面对全球化地理信息服务发展机遇,我国面临地理数据库建设、地理信息市场社会化与地理信息区域均衡发展的严峻挑战。在分析我国地理信息服务面临挑战的基础上,从数字化建设、地理信息服务市场培育、卫星遥感技术商业化发展3方面提出我国地理信息服务发展的对策与建议。     

Geometric-based approach for integrating VGI POIs and road networks

Integrating heterogeneous spatial data is a crucial problem for geographical information systems (GIS) applications. Previous studies mainly focus on the matching of heterogeneous road networks or heterogeneous polygonal data sets. Few literatures attempt to approach the problem of integrating the point of interest (POI) from volunteered geographic information (VGI) and professional road networks from official mapping agencies. Hence, the article proposes an approach for integrating VGI POIs and professional road networks. The proposed method first generates a POI connectivity graph by mining the linear cluster patterns from POIs. Secondly, the matching nodes between the POI connectivity graph and the associated road network are fulfilled by probabilistic relaxation and refined by a vector median filtering (VMF). Finally, POIs are aligned to the road network by an affine transformation according to the matching nodes. Experiments demonstrate that the proposed method integrates both the POIs from VGI and the POIs from official mapping agencies with the associated road networks effectively and validly, providing a promising solution for enriching professional road networks by integrating VGI POIs.     

Computing least air pollution exposure routes

Personalized routing counts on traveler’s preferences which are usually based on different criteria, such as shortest, fastest, least traffic, or less expensive (e.g., less fuel cost, toll free). However, people are increasingly becoming concerned about the adverse health effects of exposure to air pollution in chosen routes. Exposures to elevated air pollution concentrations particularly endanger children, pregnant women, elderly people, and people with asthma and other respiratory conditions. Choosing routes with least air pollution exposure (APE) is seen as one approach to minimize the level of pollution exposed, which is a major public health issue. Routing algorithms use weights on segments of road networks to find optimum routes. While existing weights are commonly distance and time, among a few others, there is currently no weight based on APE to compute least APE routes. In this paper, we present a weight function that computes weight based on APE. Two different approaches, geostatistical and non-geostatistical, were used to compute APE weight. Each approach was evaluated, and the results indicate that the APE weight is suitable for computing least APE routes.     

南大洋海冰影像地图投影变换与瓦片切割应用研究

南大洋海冰分布是南极考察过程中影响破冰船航行的重要因素,也是南极研究的重要内容之一。目前国际上不同机构发布的南大洋海冰分布图,大多是球面投影,不能直接用于主流的瓦片地图发布。将极方位立体投影海冰图转换为目前主流的网络墨卡托投影地图,并利用合适的图像重采样方法,按照不同级别比例尺进行瓦片切割和编号存储,最终实现海冰影像地图的发布共享是本文的主要研究内容。笔者对不同的图像重采样方法进行了比较,分析了最邻近点采样方法、双线性内插和双三次卷积重采样方法的优劣,针对本文的研究优选双线性内插方法进行影像地图瓦片的切割,并最终叠加融合在Google地图上,实现了Google底图、准实时海冰影像图与破冰船走航位置的集成显示,为雪龙船的冰区航行提供了重要的数据支撑。     

基于人眼视域图像识别的风景道视觉景观质量评价

风景道是国家旅游与交通产业融合发展的举措,而视觉景观质量（VLQ）则是风景道建设的依托。当代计算机视觉技术的发展为风景道VLQ的研究带来机遇,使其在方法上能够突破主观与客观之间的二元分割。以云南思小高速为研究对象,通过多镜头组合的等距拍摄方式获取道路景观的双眼视域图像,利用图像识别技术获取图像的像素信息;建构“非量表式语义差异法”,从“自然—人工”“多样—统一”“开阔—幽深”3个维度对视域图像进行像素级别的计算。结果显示,案例地VLQ的特征较为突出,具有高度自然、相对统一和开阔的总体特征;不同行驶方向上的VLQ存在差异,但该差异会随观测尺度的扩大而减小。基于研究结果,本文提出设置支线道路配合突出风景道形象、强化双向道路景观的差异化建设措施。实证研究在风景道VLQ测评方面表现出了直观、精确的特征,反映了本文“主体性与客观性兼顾”的方法论优势。该方法的运用将助力管理机构制定更具科学性的风景道规划、建设与管理决策,推动中国风景道的高质量发展。     

Turn calculations for the indoor application of the fewest turns path algorithm

ABSTRACT

Present-day indoor navigation systems are often not well adapted to the specific needs and requirements of its users. This research aims at improving those indoor navigation systems by providing navigation support that cognitively closer to user preferences and behaviour. More specifically, the focus is on the implementation of an accurate turn calculation method in a turn minimization algorithm, aiming to lower the complexity of routes and route instructions. This new-introduced perception-based turn calculation procedure is based on a direct door-to-door walking pattern, and, in contrast to previous algorithms, independent of the underlying indoor network type. It takes into account the effects of geometry of indoor space on human movement. To evaluate its functioning, both the traditional algorithm and the proposed perception-based algorithm are applied in the fewest turns path algorithm. It is demonstrated that the proposed algorithm accurately calculates turns in alignment with people’s perception. The implementation of the calculation algorithm in the fewest turns path algorithm also allows future applications in indoor simplest path algorithms, and overall contributes to cognitively richer indoor navigation systems.     

基于交通状态分析的南昌市区区际联系通达性研究

综合考虑交通状态日变化规律、区际联系出入口等级及高速公路、过江大桥和隧道等对通达性的影响,引入路网饱和度模型分析南昌市区区际联系通达性的时空分布特征,研究表明：① 南昌市区区际通达性主干路指向性强,整体呈由中心向外围不规则辐射状;② 全区通达性格局受交通状态影响,不同时段通达性格局差异明显,尤其是南昌市核心区变化更为显著;③ 过江大桥、隧道的交通状态对区域通达性影响较大,高峰期过江大桥及隧道的拥堵凸显出河流、铁路线等因素对交通的阻隔,河流及铁路线两侧通达性差距拉大。在此基础上,为提升区际联系通达性提出了南昌市区际公路及市内道路空间组织的优化建议。     

跨界道路交通对同城化地区时空联系影响研究：广佛案例

同城化是区域内城市发展到一定阶段的产物,而交通是同城化时空联系产生的重要基础。利用空间句法以及时间地图方法,分析广佛时空结构特征,多方面探讨跨界道路建设对广州与佛山时空联系的影响。结果表明：① 广佛时空结构特征方面,5 km、10 km句法整合度模型呈现以广州内环高速范围内地区为中心的极化格局特征,佛山中心城区位于节点位置;20 km、100 km整合度模型中广佛中心集聚特征明显;广佛时间地图呈东西方向收缩。② 跨界道路影响方面,通行后越接近交界区域,时间距离偏移越大,广州南部地区与南海、顺德时间成本改善明显。③ 跨界道路通行有利于不同尺度下路网可达性整体水平的提高,能为广佛路、陈村大桥、禺山西等道路分流部分交通流。空间句法与时间地图方法的使用识别了不同尺度上广佛等级差异与交通潜力,且对地理空间进行了时空转换,结论能为今后城市功能整合提供参照,并为相关研究提供新的分析维度和视角。     

基于手机基站数据的城市交通流量模拟

基于移动定位数据的城市内社会经济活动特征分析是人类移动性的重要研究内容,而交通流量更是这些特征的基本反映。为还原城市道路网络的使用情况并分析其分布特征,本文从产生交通流量的个体出发,对包含基站位置的手机话单数据进行系统抽样,利用蒙特卡洛方法产生个体的出行起止点,并结合当地道路交通网络求得最短路径,最后估算出一天内道路交通网络上的流量分布。通过分析发现：城市内大部分道路的流量小,使用率低,大部分交通流量集中在小部分主干道路;进一步统计分析可知,当地道路交通流量符合20/80规律,即大约20%的道路承担着80%的交通流量;而对不同类型的道路,流量分布也反映出其在城市道路网络中的地位和作用。此研究对于历史交通流量分布的重现、城市道路交通模式的研究以及基于此的道路网络规划情景模拟都有着重要意义。     

Rockfall in the Port Hills of Christchurch: Seismic and non‐seismic fatality risk on roads

Numerous rockfalls released during the 2010–2011 Canterbury earthquake sequence affected vital road sections for local commuters. We quantified rockfall fatality risk on two main routes by adapting a risk approach for roads originally developed for snow avalanche risk. We present results of the collective and individual fatality risks for traffic flow and waiting traffic. Waiting traffic scenarios particularly address the critical spatial‐temporal dynamics of risk, which should be acknowledged in operational risk management. Comparing our results with other risks commonly experienced in New Zealand indicates that local rockfall risk is close to tolerability thresholds and likely exceeds acceptable risk.     

Ajax在WebGIS中的应用

Google Maps的Ajax客户端为WebGIS开发提供了新思路。该文从3方面讨论了Ajax在WebGIS中的应用。在原理方面,通过分析Ajax模型和Google Maps,阐述了Ajax方法与OGC规范相结合的客户端模式;在实现环节,以MapBuilder为例分析了Ajax客户端的实现模式及功能扩展方法;在应用方面,介绍了基于GeoServer和Map-Builder实现的淮河流域水环境信息网络查询原型系统实例。     

武汉城市圈城乡道路网的空间结构复杂性

以武汉城市圈为研究区,借助ArcGIS9.3、Pajek2.7和SPSS16.0等软件,从节点重要性、可达性、集聚性3个方面定量揭示了复杂城乡道路网的空间异质性:①高度节点重要性呈幂律分布,表现出无标度性,低度节点重要性则基本呈钟型泊松分布,呈现一定的随机性,导致整个圈域节点的重要性分布曲线既不遵循钟型泊松分布也不遵循幂律分布,出现"涌现"性;节点度值空间分布较均匀,呈现点状特征和弱集聚性,具有明显间断性和跳跃性,表现出一定的"中心-边缘"和"等级圈层"的复合结构;②节点的可达性主要由网络平均路径长度、紧密度和介数指标表达,其中道路网平均路径长度较大,节点交通联系呈线状组织,遵循距离衰减律,成等级圈层分异,但受快速干道影响明显,空间收敛减慢,发生"摄动"变形,形成两条以南北京珠高速和东西宜黄高速为轴的城市交通走廊;节点的紧密度系数较随机网络小,但高紧密度节点在空间分布上较为集中,呈现出一定的"中心-边缘"空间格局;节点的介数指标相对较高,呈现指数分布,空间分布较均匀,但仍呈现出一定的"等级圈层"分异;③网络的集聚性空间差异显著,形成多个大型网络社团,网络的聚类系数近似为零,局部呈现耦合性质,高聚类系数节点集聚成"半月形"展布,低聚类系数节点分布较为离散。     

中国空中廊道划设与时空拥堵识别及其航线流量影响

航空运输的迅速发展使空中交通流增加,空中廊道因能容纳高密度交通流而成为支持空域资源充分开发利用的一种新技术,空中廊道拥堵时段和拥堵区段的识别是廊道上车道分配和开合操作的基础。在回顾空中廊道与交通拥堵相关研究后,构建了由空中廊道划设、拥堵状态识别、航线流量影响组成的研究方法。依据高流量航线确定空中廊道位置、依据距离约束条件确定航线参与者,合并划设出全国14条空中廊道;进而通过时空数据计算、时空图编绘、网格频数筛选及划分阈值设定等步骤,遵照重叠次数及热格频数的指示规则,对拥堵时段和拥堵区段进行识别;并通过规模值和汇聚值两个指标分析高流量航线的拥堵影响。研究发现：拥堵时段呈现为全天多峰“波浪型”分散分布及高峰后端集聚的结构特征;拥堵区段整体呈现为不平衡覆盖和交汇节点集中分布的结构特征,其中高拥堵程度的空中廊道呈现为一个斜体“N”字型框架,框架上为小区段集中的不完全贯通;时空交互上,拥堵区段存在单一时段和多时段重叠两种类型,多个廊道的不同拥堵区段存有共同拥堵时段。高流量航线在空中廊道拥堵中起相对决定性作用,且在抵港和离港两个方向上的影响不均衡。空中交通拥堵识别可为中国未来空域资源时空动态评估和空中廊道建设提供依据。