一种基于GDF4扩展模型的通用导航数据转换平台设计

GDF3.0中所有要素必须由平面拓扑结构组成[1],国内各导航数据生产商的数据目前基本上很难达到这种结构要求,这限制了其采用GDF标准的进度.这种复杂的拓扑关系在导航应用中并不是最重要的信息,因此各厂商的数据虽然不满足这种底层的拓扑关系,但并不影响实际导航应用.     

基于共享单车轨迹的精细路网更新方法

城市道路数据的完整性和实时性是保障位置服务和规划导航路径的关键支撑。该文提出一种基于共享单车轨迹数据的新增自行车骑行道路自动检测和更新方法:首先,结合缓冲区方法和轨迹—路网几何特征检测增量轨迹;其次,基于分段—聚类—聚合策略提取更新路段,利用多特征融合密度聚类算法与最小外包矩形骨架线法提取增量道路中心线;最后,基于拓扑规则完成道路更新。以广州市共享单车轨迹为例,将该方法与传统栅格细化法进行实验对比,结果表明:该方法能有效更新道路网络,且在2 m和5 m精细尺度范围内提取的新增道路覆盖精度提升14%左右;在7 m尺度下精度达90%以上,在10 m尺度下精度达96%以上。     

浅谈ARCGIS数据模型GeoDatabase

Geodatabase是一种采用标准关系数据库技术来表现地理信息的数据模型。是ESRI公司建立的面向对象的空间数据模型,它真实的反映了现实世界的物理实体,在继承传统的Coverage数据格式拓扑关系管理优势的同时,提出了基于规则的拓扑关系管理机制,并给出了配套的应用工具对其进行交互处理     

基于高空间分辨率遥感影像的湿地信息提取技术研究

如何利用遥感技术获取高精度的湿地信息是湿地遥感研究中的重要内容之一.基于高空间分辨率的遥感影像数据,研究利用面向对象的分类方法,综合利用遥感数据的光谱信息、纹理特征、拓扑关系等信息进行多尺度分割,通过对对象的目视解译建立隶属度函数,并结合最邻近分类法,获取湿地信息.并以福建省闽江口湿地为例,采用高分辨率的SPOT5影像数据,研究表明：利用面向对象的方法对SPOT5遥感影像进行湿地信息的提取精度达到90.40%,为湿地信息的提取又提供了一个有效的方法.     

基于超像素的高分辨率影像建筑物提取

建筑物提取对于基础地理数据获取与更新具有重要意义。针对传统的基于像元方法难以利用影像空间、上下文信息以及面向对象方法最优分割尺度难以确定等问题,该文提出一种基于超像素的高分辨率影像建筑物提取方法。首先利用LiDAR点云数据生成归一化高程模型以获取地物的高度特征,并通过Layerstacking方式与高分辨率影像融合;随后基于Simple Linear Iterative Clustering(SLIC)算法分割高分辨率影像的RGB彩色图像生成超像素;继而基于分割所得的超像素中的每个像元对超像素进行特征计算;最后使用基于RBF核的支持向量机方法进行超像素级别分类,得到建筑物提取结果。实验结果表明,该方法能够有效识别出简单场景和复杂场景下的建筑物,显著消除了传统基于像元方法出现的"椒盐效应",同时避免了面向对象方法中最佳分割尺度选择的难题,取得了较好的建筑物提取效果。     

古陆上丝绸之路复原及沿线基本地理特征分析

古陆上丝绸之路的路线复原是丝绸之路研究的重要组成部分,但目前该方面的研究还缺乏全局性、整体性的视角。该文首先基于30m分辨率SRTM数据提取了对古代道路形成产生重要影响的关键地形因子和水文因子,并按照一定成本比率生成路线成本数据;然后,结合该区域的河流湖泊分布数据以及相关文献记载的古陆上丝绸之路沿线关键驿站数据,应用最优路径分析方法逐段复原古陆上丝绸之路;最后,应用迭代分析法对分段路线进行合并,模拟得到完整的从长安到君士坦丁堡、横跨亚欧大陆的古陆上丝绸之路。在此基础上,结合MODIS遥感影像数据以及沿线相关国家的人口、经济统计数据,分析了古陆上丝绸之路沿线主要地理要素特征,以期能较为全面地了解古陆上丝绸之路沿线基本人文、自然地理特征。     

融合遥感影像光谱和纹理特征的矿区林地信息变化监测

以某超贫钒钛磁铁矿为例,基于Landsat TM/OLI数据,首先利用相关性分析和单因素方差分析法(one-way ANOVA),结合林地与其他地物的光谱、纹理特征差异,筛选了提取林地信息的最佳光谱和纹理波段;其次,融合光谱纹理特征,利用支持向量机法获取了林地的空间分布信息。结果表明,基于OLI数据光谱和纹理特征的林地提取精度达85.51%,较基于单一光谱特征的提取精度提高5.0%,且基于OLI数据的提取精度整体优于TM数据。统计显示,2015年矿区林地覆盖面积为103.26km2,较2001年减少14.21km2,超贫钒钛磁铁矿采区和尾矿库的迅速扩展是造成林地覆盖减少的主要原因。该文为获取矿区林地空间分布信息提供了一种新的方法与思路,为矿区林业资源监测提供了技术支持。     

基于TM光谱特征的沼泽地定量提取模式研究

要从TM影像上定量提取沼泽地信息就必须首先获取TM数据中的沼泽地波谱信息这个最基本参数。以2000年7月TM数据为数据源,在ERDAS和PCI等遥感软件支持下,运用灰度分析方法分析沼泽地及背景地物光谱特征,并以一条光谱采样剖面线分析沼泽地内部光谱结构。最终,建立了基于前述光谱特征的三个关于沼泽地信息的定量提取模式,定量提取了沼泽地的植被、积水信息以及与水田区别的参数,具有计算机上运算的可行性。     

数据融合方法在道路提取中的应用研究

以SAR与SPOT多光谱影像为数据源,通过几何校正、辐射定标、降噪等数据预处理,选取PCA(Principal Component Analysis)、BT( Brovey Transform)、WT( Wavelet Transform)和HPF( High-Pass Filtering)4种方法进行融合实验,并对融合后数据以及原SPOT多光谱数据进行道路提取研究.结果表明:基于PCA和HPF方法所提取的道路特征明显,纹理清晰,错分和漏分现象不明显,道路信息效果较好;WT方法提取效果次之;BT道路提取效果相对较差;4种方法经融合后数据提取道路精度均高于原始SPOT多光谱数据,最优方法提取道路精度错分率较SPOT多光谱高达29.4％,道路提取精度相对较差的BT方法较SPOT多光谱错分率高出18％.     

一种基于拓扑信息的多边形数据自动生成算法

在GIS的众多应用中,多边形数据的自动生成和多边形数据拓扑关系的构建与维护都是一种高频率的操作。该文在分析和总结已有多边形数据自动生成算法和拓扑关系生成算法基础上,提出了一种基于拓扑信息的多边形数据自动生成算法(PG-TI)。介绍了该算法的数据结构以及弧段邻接关系确定、多边形搜索和拓扑关系确定3个核心过程,重点探讨了使用多边形搜索过程中建立的拓扑信息来提升拓扑关系确定过程性能,在此基础上与传统算法和ArcGIS中对应算法的时间复杂度进行了对比分析和验证。     

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.     

乡村旅游的乡村性测评模型——以江西婺源为例

乡村性是乡村旅游的本质特性,对乡村性进行测评是乡村旅游可持续发展研究的基础,是指导乡村旅游开发、经营和管理的重要依据。本文采用定性与定量相结合的方法,通过理论分析选取了5个潜在因素和17个观测因子构建了乡村性测评的指标体系,运用结构方程原理,建立了乡村性CFA测评模型,并以江西婺源为例进行了实证研究。通过对婺源乡村旅游典型地区的抽样调查,获取了相关数据,建立了多元回归方程,运用SPSS软件进行回归分析,获得模型的路径系数和随机误差,并对每个回归方程进行了F检验和拟合度检验,结果显示回归方程具有较高的可靠性。对模型中的路径系数进行了t检验,t值在2.319~86.895之间,其显著性概率P小于0.01或0.05,模型中的因果关系显著,与研究的假设条件相符合,模型可以接受。     

Map-matching algorithm for large-scale low-frequency floating car data

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.     

Pedestrian network map generation approaches and recommendation

With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database, which represents a network (e.g., road networks for car navigation) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activity studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there is a void in literatures discussing the challenges, methods, and best practices for pedestrian network map generation. This coupled with the increased demand for pedestrian networks is the prime motivation for development of new approaches and algorithms to automatically generating pedestrian networks. Three approaches, network buffering, using existing road networks, collaborative mapping, using Global Positioning System (GPS) traces collected by volunteers, and image processing, using high-resolution satellite and laser imageries, were implemented and evaluated with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatic pedestrian network map generation. The recommendation of a suitable approach for generating pedestrian networks for a given set of sources and requirements is provided.     

月面形貌仿真设计及在嫦娥三号任务中的应用

月面形貌仿真可以为嫦娥三号着陆前地形建立及视觉导航仿真测试提供逼真的三维月面环境。利用分形随机算法并结合月面撞击坑与石块的数学分布模型,在实现月面数字地形的基础上利用纹理映射和纹理融合的方法为月面地形添加纹理,完成了月面逼真三维环境的构建。结合导航相机的外方位元素和光照条件,实现了对该仿真月面环境的模拟环拍,支撑了嫦娥三号发射前月球车导航相机数据获取、地形建立、通行代价图计算、月球车路径规划等遥操作任务过程仿真测试。测试结果表明,仿真月面三维地形具有良好的视觉效果,满足了巡视器导航相机测试验证对精细月面地形和纹理的需求,为导航相机测试验证提供了有效的月面形貌仿真数据。     

Inferring user tasks in pedestrian navigation from eye movement data in real-world environments

Eye movement data convey a wealth of information that can be used to probe human behaviour and cognitive processes. To date, eye tracking studies have mainly focused on laboratory-based evaluations of cartographic interfaces; in contrast, little attention has been paid to eye movement data mining for real-world applications. In this study, we propose using machine-learning methods to infer user tasks from eye movement data in real-world pedestrian navigation scenarios. We conducted a real-world pedestrian navigation experiment in which we recorded eye movement data from 38 participants. We trained and cross-validated a random forest classifier for classifying five common navigation tasks using five types of eye movement features. The results show that the classifier can achieve an overall accuracy of 67%. We found that statistical eye movement features and saccade encoding features are more useful than the other investigated types of features for distinguishing user tasks. We also identified that the choice of classifier, the time window size and the eye movement features considered are all important factors that influence task inference performance. Results of the research open doors to some potential real-world innovative applications, such as navigation systems that can provide task-related information depending on the task a user is performing.     

Cognitive Abilities in the Service of Wayfinding: A Functional Approach

A functionally oriented framework for examining the cognitive abilities that are involved in human wayfinding is suggested. The framework includes a categorical distinction among types of wayfinding tasks (commutes, explores, and quests) and means used most frequently to accomplish these tasks (piloting, repetition of locomotor pattern, path integration, and navigation by cognitive map). The cognitive abilities contributing to these wayfinding means have been demonstrated by research on spatial cognition and behavior or can be inferred from relevant research and theory.     

基于定位视频的车辆导航原型系统设计与关键技术研究

基于电子地图的导航系统相对抽象且缺乏沉浸感,不方便用户判别。为使导航效果更加直观和生动,该文提出基于定位视频的车辆导航思路,对车辆导航原型系统进行总体设计与实现,并探讨其关键技术。核心思想是建立道路定位视频(Geo-video)数据库,利用移动终端和固定目标的位置信息对定位视频数据库进行空间检索,将相应位置的视频图像传输给移动终端并实现路线和目标指引。试验证明该方法在技术上具有可行性。     

A prefetching model based on access popularity for geospatial data in a cluster-based caching system

Geospatial tile popularity reflects the general characteristics of user preferences in tile access. However, tile access has both long-term popularity features (characterized as stable) and short-term popularity features (characterized as explosive). Specific features of tile popularity are an important theoretical basis for improving the accuracy of caching and prefetching. This article considers both long-term and short-term popularity features for tile access and presents a Markov prefetching model in a cluster-based caching system based on a Zipf distribution. First, it describes the navigation path and the transition probability path for tile access based on the global features of tile access to find a way to estimate the transition tile access probabilities based on the access pattern, which satisfies Zipf's law. Then, based on temporal and spatial local changes in tile access patterns, the basic Markov model is used to prefetch tiles with the highest probability in the follow-up state for current hot tiles and these tiles are labeled as the set of prefetched objects. Finally, based on the access probability for prefetched tiles, they are evenly distributed in a cluster-based caching system. This method takes into account both global and local space–time changes in tile access patterns. This method not only makes the set of cached objects relatively stable but also adapts to changes in access distribution. Experimental results reveal that this method has a higher prefetch hit rate and a shorter average response time for tile requests and thus can improve the efficiency and stability of cluster-based caching systems.