改进G2SFCA的深圳市室内应急避难场所空间可达性研究

以深圳市为研究区,在考虑距离衰减效应的重力型两步移动搜索法（gravity two-step floating catchment area method,G2SFCA）基础上,引入Huff模型,并考虑需求点位置要素及地形要素,分别从供给点竞争、需求点定位、路网距离优化三方面对G2SFCA进行改进,并采用改进的G2SFCA对深圳市室内应急避难场所空间可达性进行研究。实验结果表明,改进的G2SFCA不仅能很好地揭示深圳市各社区室内应急避难场所的空间可达性,而且也能有效反映避难场所可达性与人口密度分布的空间匹配规律,较其他模型更符合现实情况;已建成室内应急避难场所数量、容纳人口及空间可达性的统计与分析结果真实、可靠,相关结论可为深圳市未来的防灾工作以及室内应急避难场所的空间规划与建设提供参考。     

Mapping the spatial disparities in urban health care services using taxi trajectories data

The understanding of spatial inequality in health care services is critical for reasonable policy‐making and management. In this study, we present a novel approach to analyze the demand–supply of health care services using taxi data. Taxi data provide observations of individual travel activities, and hence can be used to characterize the actual demand–supply of health care services. We apply the proposed approach in Guangzhou, China to carry out a case study. The results show the spatial disparities in health care service access. About 21.05% of the total population has high hospital accessibility, while the remaining 78.95% has relatively low hospital accessibility (i.e., roughly an “80/20” distribution). It is found that 6.29% of the population lives in high‐density suburban communities but has relatively low hospital accessibility. Most of the hospitals serve a population that is compatible with their capacity. One hospital is found to have a small capacity but to serve a large population, while two hospitals have relatively high capacities but serve small populations. These findings can help improve our understanding of spatial inequalities in public service provision, and may also provide useful information to address the health care problems of an aging population in contemporary, rapidly urbanizing China.     

基于GIS的两步移动搜寻法在北京市就医空间可达性评价中的应用

传统上用行政区内每千人病床数等指标来评价就医的空间可达性,并未考虑医院(供给)与人口(需求)的空间分布差异性及两者可跨越行政区界的潜在相互作用。基于GIS的移动搜寻法使用较小普查单元的人口数据,解决了内在的人口空间分布问题;移动搜寻域可以跨越行政区界,更合理地考虑病人与医院潜在的相互作用。本文通过北京市就医空间可达性的实证研究,展现了基于GIS的两步移动搜寻法在公共服务空间可达性评价方面的重要作用。     

A Computational Method for Estimating the Demand of Retail Stores on a Street Network and its Implementation in GIS

This paper describes a computational method for estimating the demand of retail stores on a street network using GIS. First, the 'network Huff model' is formulated on a network with the shortest-path distance as an extension of the ordinary Huff model (which assumes a continuous plane with Euclidean distance). Second, using this model, a formula for estimating the demand is derived. This estimation formula is similar to that with the ordinary Huff model, but it has an advantage in that the formula exactly computes the demand on a network. Third, a practical method for computing the formula is developed. Finally, a method of implementing this computational method in a GIS environment is shown.     

MapGISK9服务引擎：一种基于云的影像分析功能部署

为了突破桌面软件对地理空间信息应用的限制,本文应用MapGISK9服务引擎,提出了一种新的服务引擎功能,它能够将MapGISK9REST风格的Web服务处理功能作为在线式和按需式影像科学程序提供给地理空间组织机构。针对目前地理空间用户在影像处理方面具有在线式和按需式访问需求的情况,本文借鉴ENVI并利用MapGISK9服务引擎的工程化应用实例,提出了一套客户端一服务器企业架构或云架构的解决方案,以增强态势感知能力。     

基于网络爬虫的导航深度服务信息自动采集

根据近来对地理信息Web服务搜索引擎的研究,设计一种基于网络爬虫自动采集POI(Point Of Interest)深度服务信息的方法。使用网络爬虫与DOM(Document Object Model)技术从发布相关POI深度服务信息的网站抓取实时信息,并通过编辑距离与针对地址匹配的改进最大公共子序列分析页面内容与POI主题相关度,进而将相关度最高的深度服务信息与POI点匹配,生成深度服务信息点特征。实验证明了方法的有效性。     

Positioning Disaster Relief Teams Given Dynamic Service Demand: A Hybrid Agent‐Based and Spatial Optimization Approach

During extreme events, like hurricanes, it is essential to position relief services for non‐evacuees throughout the affected region in optimal locations. While previous research has explored a variety of spatial optimization models to accomplish such a task, most work assumes that the population with demand is relatively static. However, this assumption neglects to account for potential feedbacks in the relief distribution system. For example, a population's behavior can both affect and be affected by the placement of relief services, resulting in a dynamic spatial distribution of demand. This article presents a hybrid modeling approach that utilizes GIS data with agent‐based and spatial optimization models to position emergency relief teams in Bay County, Florida during a hurricane event. Non‐evacuating household agents choose to remain at home or seek shelter, while relief team agents are periodically repositioned to account for changes in the spatial distribution of household agents. A total of 220 simulations are run to explore a variety of scenarios. Results show different repositioning timing strategies and the magnitude of the feedback effect drastically changes the level of access households have to relief teams. Ultimately, this work demonstrates the importance of accounting for behavioral and spatial dynamics in disaster relief distribution systems.     

Calibrating the dynamic Huff model for business analysis using location big data

The Huff model has been widely used in location‐based business analysis to delineate a trade area containing a store’s potential customers. Calibrating the Huff model and its extensions requires empirical location visit data. Many studies rely on labor‐intensive surveys. With the increasing availability of mobile devices, users in location‐based platforms share rich multimedia information about their locations at a fine spatio‐temporal resolution, which offers opportunities for business intelligence. In this research, we present a time‐aware dynamic Huff model (T‐Huff) for location‐based market share analysis and calibrate this model using large‐scale store visit patterns based on mobile phone location data across the 10 most populated US cities. By comparing the hourly visit patterns of two types of stores, we demonstrate that the calibrated T‐Huff model is more accurate than the original Huff model in predicting the market share of different types of business (e.g., supermarkets versus department stores) over time. We also identify the regional variability where people in large metropolitan areas with a well‐developed transit system show less sensitivity to long‐distance visits. In addition, several socioeconomic and demographic factors (e.g., median household income) that potentially affect people’s visit decisions are examined and summarized.     

基于OGC规范的遥感影像数据服务研究

以遥感数据共享为研究对象,针对传统遥感数据共享方法存在的问题,提出了基于WebService技术和OGC规范的遥感数据共享方案,设计了基于WMS和WCS的遥感影像数据服务,为用户提供在线遥感影像查询、浏览与获取服务,实现了遥感影像数据共享方法服务化。     

构建面向个性化服务的特大城市云空间数据中心

特大城市测绘地理信息数据具有数据海量、增长快速、多源异构、频繁使用的特点。随着大数据和Web2.0时代的到来,传统的空间数据存储管理与共享服务模式存在成果缺乏整合和挖掘、空间信息服务被动且无差别性等缺点,难以满足用户不断提高的空间数据内容、服务响应速度和服务质量的要求,也难以适应因人而异的个性化空间信息服务的需求。本文对个性化服务和云空间数据中心构建的关键技术进行了研究,提出了个性化空间数据情境应用模式,以及一种基于Web客户端的个人异构空间数据在线集成方法,基于NoSQL实现了个人空间数据与传统空间数据服务集成,并以北京市为例基于私有云构建了安全可靠、高效运行、可扩展、用户参与度高、提供个性化服务的特大城市云空间数据中心。     

Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices

Access to certain types of facilities can promote health and well‐being. When population and facilities are not uniformly distributed across the landscape, inequities in accessibility may occur. Current research into GIS‐based accessibility measures has focused primarily on spatial inequities between different geographic locations but not directly on differences in accessibility between subgroups of the population. The research presented here develops a new method for measuring differential accessibility to facilities between various segments of the population. The method extends concepts and techniques in spatial point pattern analysis that account for the spatial structure of demand and its relationship to supply. In this approach, the traditional Lorenz curve and its associated indices, the Gini coefficient and the dissimilarity index, which are used to measure inequality, are recast in spatial terms for measuring differences in accessibility between population subgroups. An analysis of spatial accessibility to grocery stores in Akron, OH illustrates the value of the spatial Lorenz curve and its associated indices compared to other methods.     

位置地图的空间认知研究

作为信息时代实现位置服务的重要基础,位置地图交互性强、使用方便,并且能实时、应景地向用户提供位置关联信息,因而比传统的电子地图更能满足用户的位置服务需求。文中分析位置地图的特点和服务模式,并基于地图空间认知理论,提出位置地图的空间认知过程,最后探讨位置地图的认知设计原则,为基于位置地图的位置服务中空间信息的认知与表达提供理论依据。     

Knowledge Transfer for Large‐Scale Urban Growth Modeling Based on Formal Concept Analysis

Cellular automata (CA) are useful for studies on urban growth and land‐use changes. Although various methods have been developed to define transition rules, modeling urban growth of large areas remains a tough challenge owing to heterogeneous geographical features. To address the problem, we present a novel method based on the combination of Formal Concept Analysis (FCA) and knowledge transfer techniques. FCA is used to solicit association rules among cities within a large area. This method can provide a theoretical basis for the knowledge transfer process. A cutting‐edge algorithm called TrAdaBoost is then integrated with the commonly‐used Logistic‐CA as the modeling framework. The proposed method is applied to the urban growth modeling of Guangdong Province, a large region with 21 cities in China, from 2005 to 2008. Compared with traditional methods, this method can achieve better results at the provincial and local levels, according to the experiments. The combination of FCA and knowledge transfer is expected to provide a useful tool for calibrating large‐scale urban CA models.     

顾及空间访问密度的地理信息服务请求负载均衡算法

有效的负载均衡是提升当前海量地理信息网络服务请求响应效率最常用的方法,但现有算法存在空间服务调用方面难以兼顾空间性和服务请求量的不足。为此,本文通过引入空间访问密度,同时考虑地理信息服务请求本身的频繁程度与数据在空间分布上的关系,提出一种顾及空间访问密度的地理信息服务请求负载均衡算法。首先,统计地理信息服务访问调用日志信息,提取数据的外包框数据集,并生成四叉树索引,通过四叉树索引建立空间访问密度均衡模型;然后,在地理信息服务请求时,利用空间访问密度均衡模型进行轮询分配;最后,对比经同等试验环境下的效率和性能,本文算法可有效提高地理信息服务请求响应效率。     

核密度估计法支持下的网络空间POI点可视化与分析

城市空间POI点的分布模式、分布密度在基础设施规划、城市空间分析中具有重要意义,表达该特征的核密度法(kernel density estimation)由于顾及了地理学第一定律的区位影响,比其他密度表达方法(如样方密度、基于Voronoi图密度)占优。然而,传统的核密度计算方法往往基于二维延展的欧氏空间,忽略了城市网络空间中设施点的服务功能及相互联系发生于网络路径距离而非欧氏距离的事实。本研究针对该缺陷,给出了网络空间核密度计算模型,分析了核密度方法在置入网络结构中受多种约束条件的扩展模式,讨论了衰减阈值及高度极值对核密度特征表达的影响。通过实际多种POI点分布模式(随机型、稀疏型、区域密集型、线状密集型)下的核密度分析试验,讨论了POI基础设施在城市区域中的分布特征、影响因素、服务功能。     

Integrating Spatial Data Linkage and Analysis Services in a Geoportal for China Urban Research

Many geoportals are now evolving into online analytical environments, where large amounts of data and various analysis methods are integrated. These spatiotemporal data are often distributed in different databases and exist in heterogeneous forms, even when they refer to the same geospatial entities. Besides, existing open standards lack sufficient expression of the attribute semantics. Client applications or other services thus have to deal with unrelated preprocessing tasks, such as data transformation and attribute annotation, leading to potential inconsistencies. Furthermore, to build informative interfaces that guide users to quickly understand the analysis methods, an analysis service needs to explicitly model the method parameters, which are often interrelated and have rich auxiliary information. This work presents the design of the spatial data linkage and analysis services in a geoportal for China urban research. The spatial data linkage service aggregates multisource heterogeneous data into linked layers with flexible attribute mapping, providing client applications and services with a unified access as if querying a big table. The spatial analysis service incorporates parameter hierarchy and grouping by extending the standard WPS service, and data‐dependent validation in computation components. This platform can help researchers efficiently explore and analyze spatiotemporal data online.     

Multi‐scale approach to mining significant spatial co‐location patterns

Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features, which are frequently located in close geographic proximity to each other. Existing methods for identifying spatial co‐location patterns usually require users to specify two thresholds, i.e. the prevalence threshold for measuring the prevalence of candidate co‐location patterns and distance threshold to search the spatial co‐location patterns. However, these two thresholds are difficult to determine in practice, and improper thresholds may lead to the misidentification of useful patterns and the incorrect reporting of meaningless patterns. The multi‐scale approach proposed in this study overcomes this limitation. Initially, the prevalence of candidate co‐location patterns is measured statistically by using a significance test, and a non‐parametric model is developed to construct the null distribution of features with the consideration of spatial auto‐correlation. Next, the spatial co‐location patterns are explored at multi‐scales instead of single scale (or distance threshold) discovery. The validity of the co‐location patterns is evaluated based on the concept of lifetime. Experiments on both synthetic and ecological datasets show that spatial co‐location patterns are discovered correctly and completely by using the proposed method; on the other hand, the subjectivity in discovery of spatial co‐location patterns is reduced significantly.     

利用ANNS的空间信息处理服务智能集成算法

针对常用的空间信息处理服务,分析了相关领域服务组合方法的优缺点,结合服务资源本身及神经网络的智能性特点,提出了基于神经网络概念的服务智能组合方法,以尽可能准确高效地实现服务组合的自动化该方法采用面向特殊服务扩展本体表达模型,结合语义描述,利用神经网络的突触原理完成核心服务的查找,最后通过集成索引函数实现服务的串接实验结果表明,在保证满足应用需求的情况下,此方法缓解了非专业用户的服务再组合障碍,提高了计算效率。     

乡村地理信息服务模式探讨与实现技术

地理信息服务聚合是将服务按照业务流程需求集成为更加复杂的服务,从而提高空间信息服务的复用能力,节约地理信息服务集成的成本。本文基于地理信息服务及乡村数据的特点,提出了一种基于补偿服务机制的地理信息服务无缝聚合的方法,聚合不同来源的服务,实现了分布式数据的无缝聚合显示及共享。