Mapping uncertain geographical attributes: incorporating robustness into choropleth classification design

ABSTRACT

Choropleth mapping provides a simple but effective visual presentation of geographical data. Traditional choropleth mapping methods assume that data to be displayed are certain. This may not be true for many real-world problems. For example, attributes generated based on surveys may contain sampling and non-sampling error, and results generated using statistical inferences often come with a certain level of uncertainty. In recent years, several studies have incorporated uncertain geographical attributes into choropleth mapping with a primary focus on identifying the most homogeneous classes. However, no studies have yet accounted for the possibility that an areal unit might be placed in a wrong class due to data uncertainty. This paper addresses this issue by proposing a robustness measure and incorporating it into the optimal design of choropleth maps. In particular, this study proposes a discretization method to solve the new optimization problem along with a novel theoretical bound to evaluate solution quality. The new approach is applied to map the American Community Survey data. Test results suggest a tradeoff between within-class homogeneity and robustness. The study provides an important perspective on addressing data uncertainty in choropleth map design and offers a new approach for spatial analysts and decision-makers to incorporate robustness into the mapmaking process.     

并行空间分析算法研究进展及评述

作为GIS的核心功能之一,空间分析逐步向处理数据海量化及分析过程复杂化方向发展,以往的串行算法渐渐不能满足人们对空间分析在计算效率、性能等方面的需求,并行空间分析算法作为解决目前问题的有效途径受到越来越多的关注。该文在简要介绍空间分析方法和并行计算技术的基础上,着重从矢量算法与栅格算法两方面阐述了目前并行空间分析算法的研究进展,评述了在空间数据自身特殊性的影响下并行空间分析算法的发展方向及存在的问题,探讨了在计算机软硬件技术高速发展的新背景下并行空间分析算法设计面临的机遇与挑战。     

Enhanced multi-objective optimization algorithm for renewable energy sources: optimal spatial development of wind farms

A new approach for treating multi-objective spatial optimization problems is introduced in this study, aiming at deriving the optimal spatial allocation of Wind Farms on a Greek Island (Lesvos). This work builds on the knowledge gained from numerous applications of multi-objective genetic algorithms, either for spatial planning purposes or for other engineering-related topics, by incorporating modified genetic operators and sophisticated planning criteria. Hence, a stand-alone genetic optimizer was developed that incorporates the controlled non-dominated sorting genetic algorithm-II (CNSGA-II), in which the user can model all planning criteria and constraints for every spatial entity to be allocated, and handle the genetic solver via a built-in computational framework that permits the analysis of large terrains. The presented paradigm provides interesting findings for the optimal development of renewable energy sources projects whose spatial allocation is governed by conflicting criteria and strict constraints.     

Local entropy map: a nonparametric approach to detecting spatially varying multivariate relationships

The relationship between two or more variables may change over the geographic space. The change can be in parameter values (e.g., regression coefficients) or even in relation forms (e.g., linear, quadratic, or exponential). Existing local spatial analysis methods often assume a relationship form (e.g., a linear regression model) for all regions and focus only on the change in parameter values. Therefore, they may not be able to discover local relationships of different forms simultaneously. This research proposes a nonparametric approach, a local entropy map, which does not assume a prior relationship form and can detect the existence of multivariate relationships regardless of their forms. The local entropy map calculates an approximation of the Rényi entropy for the multivariate data in each local region (in the geographic space). Each local entropy value is then converted to a p-value by comparing to a distribution of permutation entropy values for the same region. All p-values (one for each local region) are processed by several statistical tests to control the multiple-testing problem. Finally, the testing results are mapped and allow analysts to locate and interactively examine significant local relationships. The method is evaluated with a series of synthetic data sets and a real data set.     

全月球撞击坑识别、分类及空间分布

撞击坑是月球表面分布广泛的地貌单元,是研究月球的最直接窗口。本文以嫦娥一号卫星获取的遥感影像和DEM,以及国际天文学联合会(IAU)公布的撞击坑名录为基础数据源,以全月球表面撞击坑为研究对象,采用遥感图像处理与专家知识融合的目视解译法确定撞击坑的边界,识别出全月球表面直径大于500 m的撞击坑共计106030个,采用累积频率和与IAU公布撞击坑对比两种方法对目视解译的撞击坑进行精度评价,其识别的总体误差率为10.97%;按照形态特征指标,将全月球撞击坑分为六大类,对比分析了不同类的撞击坑影像及形貌差异性;对全月球撞击坑分类进行统计分析,得出了不同类型撞击坑在月球表面的数量与密度特征及空间分布情况。     

论人类活动的空间趋利行为

人类的经济与社会活动存在于空间中,并按照“趋利”的本质特性游离在空间中,形成一系列物质空间景观形态和作用关系表征的空间关联模式。如何看待行为与景观、行为与结构、行为与空间功能间的关系既具有理论意义,也具有重要的实践指导价值。我们所感知的客观世界是在空间逐利行为作用下形成的复杂综合体。为了保持人类社会可持续发展的空间福利,是放任空间行为任其对空间结构的塑造,还是通过建构功效空间来约束空间行为？哪个更有利于人类生存空间所体现的安全、健康和发展福利的保持？人类文明走到现在,恐怕向后者的转向是必然选择。本文基于政治经济学和空间经济学的思考,从分析人类的空间创利、逐利和寻租等空间行为切入,阐释空间趋利的基本特征与形式,及其体现的空间福利效应;剖析了生态文明转向趋势下功效空间组织和空间行为约束的必要性和机制;探索了可持续发展的空间行为模式、范式,进而导出功效空间建构与组织的基本准则。     

The use of digital map data in the segmentation and classification of remotely-sensed images

Abstract

Remotely-sensed data constitute a major potential source of input to geographical information systems (GIS)However, these data often have a relatively poor classification accuracy compared with that of the cartographic data from maps with which they may be combined in the course of GIS analysis. The possibility exists of using data sets (in the form of digital maps) resident within a GIS in order to improve this accuracy, before the classified image is incorporated into the GIS. Results are discussed from a British Alvey Information Technology project to develop a system for the knowledge-based segmentation and classification of remotely-sensed terrain images, in which the knowledge contained in digital map     

基于R树的分布式并行空间索引机制研究

为提高分布式并行计算环境下海量空间数据管理与并行化处理的效率,基于并行空间索引机制的研究,设计一种多层并行R树空间索引结构。该索引结构以高效率的并行空间数据划分策略为基础,以经典的并行计算方法论为依据,使其结构设计在保证能够获得较好的负载平衡性能的前提下,更适合于海量空间数据的并行化处理。以空间范围查询并行处理的系统响应时间为性能评估指标,通过实验证明并行空间索引结构具有设计合理、性能高效的特点。     

Place matters in sports: effects of the length of championship series on winning probabilities for the team with home field advantage

In this paper, I address the question of how the length of championship series between two teams can affect the probability that a team wins the series. The geographical element of the question enters through consideration of ‘home-field advantage’. This refers to the fact that in championship series, one of the teams has the benefit of one additional game that is scheduled to be played at home. This, coupled with the fact that teams typically have a higher likelihood of winning at home, leads to an interesting and surprisingly complex relationship between the length of a series and the probability of winning that series. Conclusions include the facts that (1) when the team with home-field advantage has a relatively small probability of winning away from home, it will fare relatively better in shorter series, and (2) the probability of winning a series can first become lower, but then become higher, as one progresses from 1-game series to 3-, 5- and 7-game series.     

Revisiting John Snow's map: network-based spatial demarcation of cholera area

Dr. John Snow's cholera map is known as one of the pioneering examples of an epidemiology map, illustrating the spatial distribution of the victims from the cholera outbreak. This article revisits his map and expands on his attempt at visualizing the distribution of the victims by focusing on spatial demarcation using the sphere of influence along the street network by applying two analytical methods that are designed for analysis of network space. First, the article generates a network-based Voronoi diagram of the water pumps in the map that encompasses Snow's original version of the equidistance line that was drawn around a single pump. The article then presents a new, revised equidistance line that better reflects the circumstances around the time of the outbreak. This is followed by the construction of another set of boundaries derived by the application of a network-based clumping method. Comparing the demarcation lines produced with the two methods shows a sphere of influence which was unclear when using the network Voronoi diagram alone. Results from the analysis using the clumping method also confirm some of Snow's observations on the spatial distribution of the victims.     

Digital map conflation: a review of the process and a proposal for classification

This article is centred on analysing the state of the art of the conflation processes applied to geospatial databases (GDBs) from heterogeneous sources. The term conflation is used to describe the procedure for the integration of these different data, and conflation methods play an important role in systems for updating GDBs, derivation of new cartographic products, densification of digital elevation models, automatic features extraction and so on. In this article we define extensively each conflation process, its evaluation measures and its main application problems and present a classification of all conflation processes. Finally, we introduce a bibliography which the reader may find useful to further explore the field. It tries to serve as a starting point and direct the reader to characteristic research in this area.     

空间分析研究进展

空间分析从地理空间的视角描述和分析问题,是地理学日益受关注的研究手段与方法,已引起其他相关学科的重视。该文阐述了空间分析的概念、内容、分类与定义,沿着1960s以来空间分析的发展脉络,分为3个阶段:1960s对空间数据的分析和空间自相关的测度,1970s-1980s空间统计学的迅速发展时期,1990s到本世纪初,空间分析与GIS和智能计算相互结合产生巨大的应用潜力,计算密集型的特点明显。结合各阶段典型的、具有代表性的文献资料,阐述不同时期的主要特点与成就,最后总结了空间分析的发展趋势和相关问题。     

2008年以来地图学眼动与视觉认知研究新进展

地图是人类日常生活中不可或缺的工具。地图认知作为研究人对地图的感知、学习、记忆、推理和决策的科学,一直以来是地图学基础理论的重要内容。作为地图认知研究的核心,近年来地图视觉认知在相关学科（如心理学、认知科学和计算机视觉）和新的研究手段（如眼动跟踪、脑电和核磁）的促进下取得了一系列新的研究成果。尤其是眼动跟踪方法作为地图视觉认知研究的重要手段之一,越来越受到研究者的关注,为地图视觉认知研究的定量化、实用化提供了有力支撑。本文系统地梳理了2008年以来眼动跟踪方法在地图视觉认知研究中取得的新进展,并将其归纳为6个发展趋势,分别包括：① 刺激材料：从静态地图到动态交互地图;② 研究范围：从地图认知到地图空间认知;③ 实验环境：从实验室环境到真实环境;④ 地图维度：从二维地图到三维地图;⑤ 个体差异：从单一维度到多维度;⑥ 研究目的：从规律探究到实践应用。本文最后总结了未来研究面临的挑战、难点和可能的解决方法,期望能在地图视觉认知研究中起到抛砖引玉的作用。     

基于数据分治与双层索引的并行点面叠加分析方法研究

地图叠加分析是一种计算密集型算法,并行化计算是加快算法执行速度的一种有效方法。该文研究分布式环境下的点面图层并行化叠加分析方法与实现。首先根据点面叠加的特点设置并行数据分解的方式,基于分治法分解空间数据,在并行系统下将地理要素分而治之。然后引入双层索引的并行叠加机制,一是对面图层根据Hilbert空间索引的排序方式分发数据,二是对点图层建立四叉树索引,对每一个进行相交运算的多边形进行快速过滤和求交。最后在Linux集群系统下实现该并行算法,其一利用MPI分布式计算环境实现在整体计算框架下的消息通讯模式的并行,其二在每个子节点中实现基于多核OpenMP工具的本地并行化。结果表明,利用双层空间索引分治的方法可实现并行数据分块,各子节点实现独立计算,减少并行系统中的I/O冲突,并行加速比明显。该方法对矢量地图运算的并行化进行了有益的尝试,为大数据时代的空间数据分析提供一种有效的途径。     

Detecting arbitrarily shaped clusters using ant colony optimization

In the map of geo-referenced population and cases, the detection of the most likely cluster (MLC), which is made up of many connected polygons (e.g., the boundaries of census tracts), may face two difficulties. One is the irregularity of the shape of the cluster and the other is the heterogeneity of the cluster. A heterogeneous cluster is referred to as the cluster containing depression links (a polygon is a depression link if it satisfies two conditions: (1) the ratio between the case number and the population in the polygon is below the average ratio of the whole map; (2) the removal of the polygon will disconnect the cluster). Previous studies have successfully solved the problem of detecting arbitrarily shaped clusters not containing depression links. However, for a heterogeneous cluster, existing methods may generate mistakes, for example, missing some parts of the cluster. In this article, a spatial scanning method based on the ant colony optimization (AntScan) is proposed to improve the detection power. If a polygon can be simplified as a node, the research area consisting of many polygons then can be seen as a graph. So the detection of the MLC can be seen as the search of the best subgraph (with the largest likelihood value) in the graph. The comparison between AntScan, GAScan (the spatial scan method based on the genetic optimization), and SAScan (the spatial scan method based on the simulated annealing optimization) indicates that (1) the performance of GAScan and SAScan is significantly influenced by the parameter of the fraction value (the maximum allowed size of the detected cluster), which can only be estimated by multiple trials, while no such parameter is needed in AntScan; (2) AntScan shows superior power over GAScan and SAScan in detecting heterogeneous clusters. The case study on esophageal cancer in North China demonstrates that the cluster identified by AntScan has the larger likelihood value than that detected by SAScan and covers all high-risk regions of esophageal cancer whereas SAScan misses some high-risk regions (the region in the southwest of Shandong province, eastern China) due to the existence of a depression link.     

An agent-based model for optimal land allocation (AgentLA) with a contiguity constraint

Spatial optimization is complex because it usually involves numerous spatial factors and constraints. The optimization becomes more challenging if a large set of spatial data with fine resolutions are used. This article presents an agent-based model for optimal land allocation (AgentLA) by maximizing the total amount of land-use suitability and the compactness of patterns. The essence of the optimization is based on the collective efforts of agents for formulating the optimal patterns. A local and global search strategy is proposed to inform the agents to select the sites properly. Three sets of hypothetical data were first used to verify the optimization effects. AgentLA was then applied to the solution of the actual land allocation optimization problems in Panyu city in the Pearl River Delta. The study has demonstrated that the proposed method has better performance than the simulated annealing method for solving complex spatial optimization problems. Experiments also indicate that the proposed model can produce patterns that are very close to the global optimums.     

国土空间规划：基础设施与公共服务设施单幅总图的研制

基础设施的建设与布局是在遵循自然系统格局的基础上,由人类活动所引致的物质环境再建构和空间秩序再安排,是构建和引领区域空间结构的重要支撑体系,因此一直是区域发展类规划的重要组成部分。结合省级空间规划试点工作,提出符合空间规划目标的基础设施与公共服务设施编制方案与技术流程,强调专项规划与“三区三线”、空间布局总图的关系,并以福建省为例,设计了基础设施与公共服务设施单幅总图的编制技术流程,以期为其他地区空间规划的编制提供借鉴意义。     

国土空间规划:产业空间配置类单幅总图的研制

省级空间规划中的产业空间配置是在“三区三线”划分基础上进一步明确地域功能、引导地域功能格局优化的必要步骤。在综合考虑方法的创新性和成熟度基础上,对在“三区三线”格局内进行产业空间配置的逻辑架构、技术方法、数据体系等内容进行定量和定性相结合的探索性分析,形成了主导产业筛选、产业园区适宜规模识别、重点产业空间识别等流程体系,共同合成了一套用以研制空间规划中的产业空间配置类单幅总图的技术方法。其中,在主导产业筛选体系中综合考虑了产业关联、产业发展基础、发展潜力和政策支持等方面,在产业园区适宜规模识别体系中综合考虑了产业园区级别、园区产业是否切合区域产业发展导向、园区产业发展程度、与各类红线及城镇的空间关系等指标,并从微观企业入手向上总结重点产业空间范围,结合“三区三线”的国土空间适宜性、城镇空间划分结果进行空间叠加,做到了对省级重点产业空间的有效识别和落地。同时,以福建省为案例进行了实践分析。     

基于最优供需分配的公共设施空间可达性分析

空间可达性是衡量公共服务设施公平性的重要指标,在医疗、教育、休闲等公共服务的布局规划中得到广泛应用。然而已有设施服务可达性模型难以充分反映服务供需关系,计算指标也缺乏物理意义。本文提出新的最优供需分配的公共设施空间可达性计算方法（OSD）取代现有方法。该方法基于最优供需分配模型,将设施服务分配给需求者,根据分配结果计算空间可达性指标。给定服务设施与需求的空间分布,以最小化旅行成本为目标,顾及设施服务能力,采用经典的运输问题模型确定最优的服务供需分配方案,进而度量服务的空间可达性。以郑州市金水区社区卫生服务为例,求解25个中心与1333个居住小区的最优服务配置。使用最优配置结果确定每个设施的服务范围、每个居住小区使用服务的旅行时间,以及特定时间阈值的服务覆盖比率。与流行的两步移动搜索法相比,新方法的计算指标具有明确的物理意义。本文提出的可达性评价方法无需参数,计算高效,结果易于解释,在公共服务评价及设施布局规划方面具有应用潜力。     

基于UCMap的城市环境气候空间格局分析——以广州市为例

城市化的不断深入使城市下垫面发生改变,自然景观的大幅减少与人工建筑的大规模增加,给城市气候与环境带来了巨大影响。城市环境气候图作为分析与调控城市环境气候、评估城市环境气候状况的工具与平台,拓展了城市气候信息在城市规划与发展中的应用。针对目前中国华南地区城市环境气候研究缺乏多要素图层、多技术方法综合分析的现状,充分考虑到不同要素对环境气候影响程度的差异,论文结合已有的城市环境气候图的编制方法,选择典型亚热带季风气候特征的广州市为研究区域,构建了多环境要素、多评估时段、多技术方法的复杂下垫面城市环境气候图系统,利用专业气象插值、遥感反演、GIS空间分析等多种技术手段,对广州市空气质量、热负荷与通风潜力进行分析评估。结果表明：广州空气质量和热负荷具有明显的季节和空间差异性,通风潜力的空间差异性明显而季节变化微弱。通过进一步叠加分析各环境要素,将广州环境气候划分为7种类型,其中最适宜类型主要分布于北部山区林地与城间耕地,最不适宜类型位于天河、越秀、荔湾的城市核心区以及白云、增城的工业密集区,形成“北优南劣”的环境气候空间格局。最后,以环境气候分析结果为基础,提出各气候类型所在区域的简要规划措施,为广州市的可持续发展提供科学建议与建设方向。