统计数据地图可视化扩展研究

本文作者在对统计数据、相关统计软件以及统计地图可视化流程进行研究的过程中,发现了目前统计地图制图方面存在着统计数据分类研究不完善、统计地图可视化流程不尽科学等问题。基于以上的研究,作者对统计数据进行了归类,提出了对传统的统计地图可视化流程的改进思路,并根据统计数据的归类总结出各个分类最适宜的统计图类型,这对统计GIS软件设计软件可视化流程的人机交互和制图者利用软件制作统计地图都有一定的指导作用。最后,基于改进的统计制图流程和分类统计图,作者开发了一个小型的统计制图系统,基本达到了所期望的效果。     

网络环境下分区统计地图制图子系统的设计与实现

分析了网络环境下分区统计地图表达信息的特点,根据其可视化地理统计信息的需要,运用Java Ap-plet技术,设计和开发了网络环境下交互式分区统计地图制图子系统。     

分级统计地图的模型评价与应用

首先,从点纹、线纹、混合纹、底色4个方面归纳了分级统计地图的面状符号类型;然后,以统计数据的利用程度为视角对分级模型进行了分类,同时,给出了动态聚类初始聚类中心的计算方法,并提出了一种用级内数据集中度和级间均值离散度来评价分级精度的方法;最后,在CorelDRAW环境下进行了二次开发,实现了分级统计地图从模型分级、评价、选择到制图单元的点纹、线纹、底色填充等一系列过程的自动化,对提高统计地图制图水平和效率具有现实意义。     

网络上分级统计地图制图软件的设计与开发

分析了网络环境中分级统计图表达信息的特点,阐述了交互式分级统计图的设计方法和思路,运用JavaApplet设计并实现了网络上分级统计地图制图子系统。     

期刊博览

太湖藻类的遥感监测研究;数字图像融合技术在摄影测量中的应用;网络环境下分级统计地图可视化;数字油藏空间数据挖掘与知识发现框架设计;国内外三维导航的发展现状。     

以符号为中心的统计地图制图模板技术研究

地图制图自动化与智能化是当前制图领域研究的热点问题,模板制图是实现制图自动化,提高制图效率的一种手段。在探讨模板制图原理的基础上,分析了现有制图模板的特点及其应用模式上存在的不足,设计了以符号为中心的统计地图制图模板的应用模式,提出了以符号为中心的统计地图制图模板技术,凸显了统计地图制作过程中符号的重要地位。以此为基础,深入剖析了统计制图模板、统计专题图层、图面表达结果三者之间的区别与联系,研究了以符号为中心的统计地图制图模板构建技术、存储技术以及匹配技术,并进行了系统应用,验证了这一技术的可行性和有效性。     

分级界线引起的读图误差及改进

一、前言分级统计制图法是定量专题制图中经常采用的一种方法,适用于数据为离散分布且以一个明确的计数单元统计的地理主题,在科研、教学以及有关部门的宏观规划中得到了广泛的运用。分级统计地图图例的制作过程一般包括:数据的预处理、确定分级间距、符号设计与量表、图例设计等工作。目前一些分级统计制图的地图作品,分级     

基于视觉元素的统计地图符号自适应生成

从电子地图自适应可视化角度出发,本文结合J.Bertin的视觉变量理论,研究了统计地图符号构成的内在规律,分解出统计地图符号构成的基本元素(视觉元素);基于视觉元素建立了统计地图符号自适应生成模型,并在某GIS平台上实现了统计地图符号的自适应生成系统,取得了良好的效果。     

顾及空间自相关的统计数据分级质量评价

详细分析了统计地图数据分级质量的评价指标，研究了数据分级中应当考虑的数据空间分布规律，并用实例证明了分级数与空间自相关系数之间的变化规律。     

GIS中统计地图与统计数据的一致性研究

本文考察了统计数据与统计地图的一般形式，用维数的概念对现有统计地图进行了重新分类，探讨了统计地图与统计数据的维数一致性，对ＧＩＳ中统计制图的标准化作了有益探索。     

Frequency Histogram Legend in the Choropleth Map: A Substitute to Traditional Legends

This article presents the use of the frequency histogram legend (FHL) as a substitute to traditional legends in both classed and unclassed choropleth maps. Great variation in the size of mapping units can hinder readers' ability to comprehend statistical distributions from a choropleth map. Replacing conventional legends with FHL can aid readers in their understanding of spatial as well as statistical distributions of the mapped data simultaneously. A customized mapping application was designed in ArcInfo 9.0 to test the use of FHL in both classed and unclassed choropleth maps. Frequency histogram legends were tested on different types of statistical distributions. Although the comparison of the results shows that the FHL works best for a Gaussian or close to a Gaussian distribution for eight or fewer classes, the customized application permits users to generate choropleth maps with frequency histogram legends for any type of statistical distribution with any number of classes. The analysis reveals that readers' background in statistics helped them to effectively utilize and interpret frequency histogram legends in the choropleth maps.     

Computer-produced Unclassed Bivariate Choropleth Maps

Many cartographers subscribe to the view that unclassed choropleth maps and multivariate choropleth maps exceed map readers' abilities to process visual information. This paper examines recent evidence which controverts both of these beliefs and discusses applications of a computer program, BICHOR, designed to produce unclassed bivariate choropleth maps interactively on a line plotter or CRT. The maps utilize crossed-line symbolism and putatively overcome both the quantization error inherent in conventionally classed choroplethic displays and the perceptual difficulties associated with color-encoding schemes used for earlier bivariate maps.     

Singly- and Doubly-Constrained Methods of Areal Interpolation for Vector-based GIS

Traditionally, areal interpolation has referred to techniques for transferring attribute values from one partitioning of space to a different partition of space but this is only one of several situations that create the need for estimating unknown data values for areal units. This paper presents a categorization of four areal interpolation problems that includes the "missing" data problem, the traditional "alternative geography" problem, the overlay of a choropelth and an area-class data layer, and the overlay of two choropleth data layers and demonstrates the relationship between the last three problems and general spatial interaction modelling. The "alternative geography" and overlay of choropleth and area-class data layers mirrors a singly constrained spatial interaction model while the overlay of two choropleth layers is analogous to a doubly constrained interaction model. Iterative proportional fitting techniques with and without ancillary data are developed to solve these three classes of problems.     

Unclassed Animated Choropleth Maps

Abstract

The potential of unclassed animated choropleth maps as a solution to false patterns of geographic change arising from data classification is investigated. Old concerns about unclassed choropleth maps may be mitigated through map interactivity that offers four advantages over traditional data legends, and previous insights from testing static choropleth maps do not necessarily translate to animated cartography. Data from user testing revealed unclassed animated choropleth maps neither help nor hurt the ability of map readers to understand patterns of geographic change. However, the unclassed map (1) appeared 'less jumpy' to participants and was perceived to run at a slower pace (despite running at the same number of frames per second), and (2) subtle geographic shifts (e.g., seasonal unemployment cycles) were more readily noticed on the unclassed maps. Preliminary results also suggest classed data emphasise stability over time – while their unclassed counterparts improve our ability to see changes. This paper also outlines animated simultaneous contrast as a new perceptual issue in the creation of animated choropleth maps.     

An Evaluation of the Use of Grid Squares in Computerised Choropleth Maps

Abstract

There are numerous computer programs to produce choropleth maps and some work has also been published on the use of a grid matrix as a way of dividing an area into discrete units. The purpose of this paper is to combine the two approaches and evaluate the suitability of using a network of grid cells, each containing a representative value of the variable being mapped, as a way of producing choropleth maps on a computer.     

Change Blindness in Animated Choropleth Maps: An Empirical Study

Animated choropleth maps enable cartographers to visualize time-series data in a way that congruently depicts change over time. However, users have difficulty apprehending information encoded within these displays, and often fail to detect important changes between adjacent scenes. Failures of visual experience, such as change blindness, threaten the effectiveness of dynamic geovisual displays, in which several important changes can occur simultaneously throughout the display. Animated choropleth maps require viewers not only to notice changes but also understand symbolic meanings encoded in rapid transitions between scenes. Graphic interpolation between key frames, also known as “in-betweening” or “tweening”, smoothes transitions and lengthens the duration of the transition between scenes in a dynamic sequence. Previous cartographic literature suggests tweening could be a potential solution for change blindness in the cartographic context. This article examines this issue of change blindness in the cartographic context and reports on a human subjects investigation designed to evaluate the influence of cartographic design variables on map readers' change detection abilities. Our results indicate that 1) map readers have difficulty detecting changes in animated choropleth maps, 2) map readers over-estimate their own change detection abilities, and 3) tweening influences the legibility of change in animated choropleth maps.     

Mapping the Results of Geographically Weighted Regression

Abstract

Geographically weighted regression (GWR) is a local spatial statistical technique for exploring spatial nonstationarity. Previous approaches to mapping the results of GWR have primarily employed an equal step classification and sequential no-hue colour scheme for choropleth mapping of parameter estimates. This cartographic approach may hinder the exploration of spatial nonstationarity by inadequately illustrating the spatial distribution of the sign, magnitude, and significance of the influence of each explanatory variable on the dependent variable. Approaches for improving mapping of the results of GWR are illustrated using a case study analysis of population density–median home value relationships in Philadelphia, Pennsylvania, USA. These approaches employ data classification schemes informed by the (nonspatial) data distribution, diverging colour schemes, and bivariate choropleth mapping.     

A heuristic multi-criteria classification approach incorporating data quality information for choropleth mapping

ABSTRACT

Despite conceptual and technology advancements in cartography over the decades, choropleth map design and classification fail to address a fundamental issue: estimates that are statistically indifferent may be assigned to different classes on maps or vice versa. Recently, the class separability concept was introduced as a map classification criterion to evaluate the likelihood that estimates in two classes are statistical different. Unfortunately, choropleth maps created according to the separability criterion usually have highly unbalanced classes. To produce reasonably separable but more balanced classes, we propose a heuristic classification approach to consider not just the class separability criterion but also other classification criteria such as evenness and intra-class variability. A geovisual-analytic package was developed to support the heuristic mapping process to evaluate the trade-off between relevant criteria and to select the most preferable classification. Class break values can be adjusted to improve the performance of a classification.     

Choosing Geographic Units for Choropleth Rate Maps,with an Emphasis on Public Health Applications

Choropleth maps are the most widely used map type for mapping rates, such as those involving disease, crime, and socioeconomic indicators. The essential step of choosing a geographic unit to map is often made in an ad hoc manner. Among the desirable characteristics of choropleth mapping units are high degree of resolution, homogeneity of population size, homogeneity of land area, observation of minimum population thresholds and land area thresholds, temporal stability and currency, compactness of shape, audience familiarity, data availability, and the functional relevance of the unit to the phenomena mapped. Because of the uneven distribution of human populations, no single geographic unit can meet all of these characteristics in practice, and a well designed choropleth map necessarily involves some compromise. We present guidelines for choosing geographic units that take into account the above criteria, considering 12 geographic units ranging from census blocks to states. Even allowing for differences in scale and purpose, some units confer clear advantages over others.