Building geospatial infrastructure

ABSTRACT

Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today’s focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.     

Extracting spatial patterns in bicycle routes from crowdsourced data

Much is done nowadays to provide cyclists with safe and sustainable road infrastructure. Its development requires the investigation of road usage and interactions between traffic commuters. This article is focused on exploiting crowdsourced user‐generated data, namely GPS trajectories collected by cyclists and road network infrastructure generated by citizens, to extract and analyze spatial patterns and road‐type use of cyclists in urban environments. Since user‐generated data shows data‐deficiencies, we introduce tailored spatial data‐handling processes for which several algorithms are developed and implemented. These include data filtering and segmentation, map‐matching and spatial arrangement of GPS trajectories with the road network. A spatial analysis and a characterization of road‐type use are then carried out to investigate and identify specific spatial patterns of cycle routes. The proposed analysis was applied to the cities of Amsterdam (The Netherlands) and Osnabrück (Germany), proving its feasibility and reliability in mining road‐type use and extracting pattern information and preferences. This information can help users who wish to explore friendlier and more interesting cycle patterns, based on collective usage, as well as city planners and transportation experts wishing to pinpoint areas most in need of further development and planning.     

基于高分辨率影像的道路交通可达性分析

基于完善的交通规划理论和模型,以某市为例,借助RS技术的空间数据获取能力和GIS技术的空间分析能力,综合考虑最短出行距离、最短出行时间以及网络节点人口密度3个因素,研究分析某市的道路交通可达性,并对现有的道路交通网络进行评价,为未来城市道路交通规划以及城市建设提供科学可靠的参考依据。     

基于自适应图像分割自动提取道路中心线

道路是城区地理空间信息中最重要的基础设施之一,从高分辨影像中自动、快速的提取道路特征,是快速更新城市道路网信息的重要途径。文中在分析道路基本特征的基础上,选择基于自适应结构元素的形态分析算法提取初始道路区域;引入面积和长宽比等形状指数,得到较精确的道路信息;最后,采用Hilditch细化算法,并进行优化处理。实验证明,该道路提取过程中无需人工设置参数,且能够得到具有较高完整性和正确性的道路中心线。     

Accessibility Futures

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility‐based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side‐by‐side. For roadway modeling, zone‐to‐zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person‐weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.     

Relaxation‐Based Point Feature Matching for Vector Map Conflation

With the rapid advance of geospatial technologies, the availability of geospatial data from a wide variety of sources has increased dramatically. It is beneficial to integrate / conflate these multi‐source geospatial datasets, since the integration of multi‐source geospatial data can provide insights and capabilities not possible with individual datasets. However, multi‐source datasets over the same geographical area are often disparate. Accurately integrating geospatial data from different sources is a challenging task. Among the subtasks of integration/conflation, the most crucial one is feature matching, which identifies the features from different datasets as presentations of the same real‐world geographic entity. In this article we present a new relaxation‐based point feature matching approach to match the road intersections from two GIS vector road datasets. The relaxation labeling algorithm utilizes iterated local context updates to achieve a globally consistent result. The contextual constraints (relative distances between points) are incorporated into the compatibility function employed in each iteration's updates. The point‐to‐point matching confidence matrix is initialized using the road connectivity information at each point. Both the traditional proximity‐based approach and our relaxation‐based point matching approach are implemented and experiments are conducted over 18 test sites in rural and suburban areas of Columbia, MO. The test results show that our relaxation labeling approach has much better performance than the proximity matching approach in both simple and complex situations.     

GeoCube： 面向大规模分析的多源对地观测时空立方体

随着对地立体观测体系的建立,遥感大数据不断累积。传统基于文件、景/幅式的影像组织方式,时空基准不够统一,集中式存储不利于大规模并行分析。对地观测大数据分析仍缺乏一套统一的数据模型与基础设施理论。近年来,数据立方体的研究为对地观测领域大数据分析基础设施提供了前景。基于统一的分析就绪型多维数据模型和集成对地观测数据分析功能,可构建一个基于数据立方的对地观测大数据分析基础设施。因此,本文提出了一个面向大规模分析的多源对地观测时空立方体,相较于现有的数据立方体方法,强调多源数据的统一组织、基于云计算的立方体处理模式以及基于人工智能优化的立方体计算。研究有助于构建时空大数据分析的新框架,同时建立与商业智能领域的数据立方体关联,为时空大数据建立统一的时空组织模型,支持大范围、长时序的快速大规模对地观测数据分析。本文在性能上与开源数据立方做了对比,结果证明提出的多源对地观测时空立方体在处理性能上具有明显优势。     

关于山区道路工程控制网布设方案研究

对于贵州山区而言,多数道路工程测区中通常是山峦起伏、荆棘丛生,致使通视、通行条件差,因此,建立满足工程施工需要和符合控制精度要求并能尽量减少工作量的测量控制网是很有研究价值的。从通视性分析和网形优化的角度提出控制网的布设方案,希望对今后的此类项目实施起到一定的借鉴作用。     

基于栅格GIS的公交站点覆盖率算法研究

本文利用栅格分析技术对公交站点覆盖率的计算进行了改进,从高分辨率遥感影像与公交站点信息数据叠加得到的栅格数据中提取三个栅格矩阵:记录公交站点ID号及其位置信息的栅格矩阵、道路网络上各点的出行阻抗矩阵、不在道路网络上各点的出行阻抗矩阵,对这三个阻抗矩阵进行栅格运算,计算公交站点的覆盖率,并通过南京城区部分公交站点的分布说明本文算法的具体应用情况。     

GeoPW: Laying Blocks for the Geospatial Processing Web

Recent advances in Web‐related technologies have significantly promoted the wide sharing and integrated analysis of distributed geospatial data. Geospatial applications often involve diverse sources of data and complex geoprocessing functions. Existing Web‐based GIS focuses more on access to distributed geospatial data. In scientific problem solving, the ability to carry out geospatial analysis is essential to geoscientific discovery. This article presents the design and implementation of GeoPW, a set of services providing geoprocessing functions over the Web. The concept of the Geospatial Processing Web is discussed to address the geoprocessing demands in the emerging information infrastructure, and the role of GeoPW in establishing the Geospatial Processing Web is identified. The services in GeoPW are implemented by developing middleware that wraps legacy GIS analysis components to provide a large number of geoprocessing utilities over the Web. These services are open and accessible to the public, and they support integrated geoprocessing on the Web.     

大数据环境下道路场景高时空分辨率众包感知方法EI北大核心CSCD

道路场景作为人类发展演变中最重要、最复杂、最典型的载体之一,是道路基础设施与活动行为共同构成的综合体,链接和构建“人地关系”。道路场景感知从二维抽象简略到三维精细丰富、从静态过去式向动态现在时发展,成为智慧城市、智能交通、无人驾驶的关键技术支撑,是我国新型城镇化战略、交通强国战略的核心技术保障。本文立足于时空交通大数据,提出基于道路场景静态基础设施“形”和动态活动行为“流”的高时空分辨率道路场景感知方法。该方法从静态路网“形”角度,以“点-线-面-体”等要素为研究脉络,构建高精度道路地图众包感知的理论体系;在活动行为“流”感知上,突破传统的点模式分析局限,发展了道路网络空间活动流的时空建模与多尺度分析方法。本文揭示了静态基础设施“形”结构与动态活动行为“流”模式交互作用下的道路场景演化规律,形成以“形”控“流”、借“流”定“形”、“形”“流”叠置的高时空精度道路场景众包感知理论体系,为智慧城市、智能交通的发展提供核心技术与数据支撑。     

城市POI的空间数据分析与可视化表达

随着科技的迅速发展,地理空间数据已经成为人们日常生活中的一部分,城市POI数据则是涵盖城市公共基础设施属性信息与位置信息的大型地理空间数据。针对现阶段对城市POI数据利用程度不充分的问题,本文运用密度分析、热点分析以及服务范围分析等方法研究大连金普新区城市POI数据的空间分布特征。结果表明:大连金普新区城市POI数据呈现"二区八带多点"的分布格局,金石滩街道、中长街道、先进街道以及大李家街道医疗、教育、娱乐设施较为完善,且远离工厂,比较宜居。本研究可为市民生活、工作、学习、娱乐提供参考,也可为城市发展、管理维护提供服务。     

我国地球空间数据框架的设计思想与技术路线

根据当前我国基础地理信息系统的发展态势,较为详尽地讨论了１∶１万至１∶５万基础地理信息系统的设计思路,提出了地球空间数据框架（ＤＧＤＦ）的概念,即基于数字正射影像和ＤＥＭ及与若干层矢量框架数据（如大地控制、交通图、水系、境界、行政边界、注记等）的整体集成的栅格－矢量一体化空间数据库,目的在于尽快建立起有活力的和可更新的国家和省级基础地理信息系统。还详尽讨论了建立基础地理信息系统的主要技术路线和数据采集与数据处理的工艺流程。     

廊坊公路交通空间数据库设计与生成

在交通系统的开发和应用中,电子地图占有举足轻重的地位;而交通地理数据库的设计与创建则是研究开发智能数字交通的决定性因素,是GIS应用开发的基础。本文以廊坊道路及交通设施的管理为背景,详细介绍了基于Geodatabase及统一建模语言UML进行交通地理数据库的设计思路,并且生成了廊坊公路交通空间数据库。     

A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data

Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi‐structured datasets, and often use distinct data models, are encoded using ad‐hoc vocabularies, and sometimes are being published in non‐standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non‐expert users. Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain.     

Multi‐temporal transport network models for accessibility studies

Vehicle tracking is a spatio‐temporal source of high‐granularity travel time information that can be used for transportation planning. However, it is still a challenge to combine data from heterogeneous sources into a dynamic transport network, while allowing for network modifications over time. This article uses conceptual modeling to develop multi‐temporal transport networks in geographic information systems (GIS) for accessibility studies. The proposed multi‐temporal network enables accessibility studies with different temporal granularities and from any location inside the city, resulting in a flexible tool for transport and urban planning. The implemented network is tested in two case studies that focus on socially excluded people in a large global city, São Paulo, Brazil, including accessibility analyses from slum areas. It explores variations within a day and differences between transport modes across time. Case study results indicate how the accessibility is heterogeneous in low‐income regions.     

Exploring the spatiotemporal relationships between search flows and travel flows

Numerous studies attempted to associate search engine data with travel behaviors. However, most existing studies focus on the destinations of search and travel, while ignoring the origins, which embed critical information of where the search requests were initiated and where the travelers came from. In this study, we explore the relationships between two types of intercity origin–destination flow data, namely travel flows and search flows, which, respectively, record the number of travelers and search requests from one city towards another. By comparing the two flows during holiday and non-holiday, we examine their complex spatiotemporal relationships from multiple perspectives, including time-lag effect, distance decay effect, spatial autocorrelation, network community, cities' rankings, and important factors of search and travel activities. The findings can deepen our understanding of search and travel behaviors, hence they can help decision makers to develop targeted strategies to enhance city's attractiveness, improve transportation infrastructure, and promote tourism.     

武汉市地理空间信息共享服务平台的建设与应用

武汉市地理空间信息共享服务平台建设是"数字武汉空间数据基础设施"建设的核心内容.该平台按照"数字城市"的理念和框架,集成了武汉市多源、多尺度、多时态的空间数据,实现了跨部门、跨平台的空间信息共享共用,为政府部门和相关行业提供在线的地理信息网络服务,在武汉市经济社会发展和和谐社会建设中得到了广泛应用.