Abstract: Population density varies sharply from place to place on the whole territory of Poland. The largest number of people per 1 km2 is 21,531, while uninhabited areas account for about 48% of the country. Such uneven, non-Gaussian distribution of the data causes some difficulty in choosing the classification method in geometric choropleth maps. A thorough evaluation of a geometric choropleth map of population data is not possible using only traditional indicators such as the Tabular Accuracy Index (TAI). That is why the aim of the article is to develop an innovative index based on distance analysis and neighbour analysis of grid cells. Two indexes have been suggested in this paper: the Spatial Distance Index (SDI) and the Spatial Contiguity Index (SCI). The paper discusses the use of five classification methods to evaluate choropleth maps of population data, like head-tail breaks, natural breaks, equal intervals, quantile, and geometrical intervals. A comprehensive assessment of such geometric choropleth maps is also done. The research was conducted for the whole territory of Poland, using data from the 2011 National Census of Population and Housing. Population data are presented in the 1km grid. The results of the analysis are shown on thematic maps. A compatibility of the choropleth maps with urban-rural typology of the OECD (Organisation for Economic Co-operation and Development) was also checked.

Abstract: Choropleth map animation is widely used to show the development of spatial processes over time. Although animation congruently depicts change, the rapid succession of complex map scenes easily exce...

Abstract: Geovisualization of attribute uncertainty helps users to recognize underlying processes of spatial data. However, it still lacks an availability of uncertainty visualization tools in a standard GIS environment. This paper proposes a framework for attribute uncertainty visualization by extending bivariate mapping techniques. Specifically, this framework utilizes two cartographic techniques, choropleth mapping and proportional symbol mapping based on the types of attributes. This framework is implemented as an extension of ArcGIS in which three types of visualization tools are available: overlaid symbols on a choropleth map, coloring properties to a proportional symbol map, and composite symbols.

Abstract: Because of the disability in visualizing statistical data with spatiotemporal information of choropleth map, we propose a novel method banded choropleth map (BCM). This technique makes use of space filling, splits sub-regions with equal width or area, and then fills partitions with different colors. It can utilize limited screen space more sufficiently than small multiples. It can also preserve context more clearly than animation. Based on the technique, we made a formal evaluation to find the efficiency of BCM in doing global task and local task under different factors.

Abstract: Choropleths are a common and useful way of depicting area-coupled data on a geo-spatial map. One advantage they provide is combining area-based data accurately with geo-space. However perceptual problems arise when areas are too small, i.e when they only cover a few pixels or less. This is a very common occurrence when zooming or in densely populated areas like capital cities. We present a novel algorithm that ensures the user is able to observe area-based data coupled to geo-space based on their interactive level of zoom without distorting the original geo-spatial map. This is resolved by building a hierarchical data structure in which each area and its data is merged with one of its smallest neighbor recursively until only one polygon covers each contiguous region. The benefits are that the viewer can always view area-based data contained in the map regardless of how small any individual area becomes during interactive zooming. We break down each step of the algorithm and provide pseudo-code to enable reproducibility. We also discuss unique test cases that challenge the robustness of the algorithm with 30,000 polygons and 4,652,800 vertices as well as the performance.

Abstract: Although many 3D thematic cartography methods exist, the effectiveness of their use is not known. The described experiment comprised two parts focusing on the evaluation of two 3D thematic cartography methods (Prism Map and Illuminated Choropleth Map) compared to a simple choropleth map. The task in both parts of the experiment was to determine which of the marked areas showed a higher value of the displayed phenomenon. The correctness of answers, response time and selected eye-tracking metrics were analysed. In the first part of the experiment, a higher number of correct answers was found for Prism Maps than for simple choropleth maps, but it required more time to solve the task. The Illuminated Choropleth Map showed a higher proportion of correct answers than a simple choropleth map. During evaluation of the eye-tracking metrics, a statistically significant difference was not found in most cases.

Abstract: Choropleth maps are widely used for the display of relative values associated with areas such as population density of counties. The visual impact of these maps is influenced by the actual value distribution of the input data and in the case of a classified representation by the data classification method in use. However, conventional methods like equidistant, quantiles or Jenks work simply data-driven and do not explicitly consider any given spatial context within the data set. Consequently, important spatial characteristics like extreme values, hot spots or dusters might get lost due to an unfavorably setting of class breaks. With that, the visual impact and follow-up decisions can be largely affected (Schiewe 2016).

Abstract: The article presents the results of a study on the spatial distribution of acts of vandalism and alcohol consumption in prohibited areas. The study made use of data on offences committed in Krakow, reported by citizens of the city and illustrated on an interactive map - the National Safety Risk Map. The gathered data was calibrated and generalised. Then, a map was prepared illustrating the spatial distribution of both categories of offences in different sub-districts in Krakow, as well as a choropleth map of both types of offence. Two methods were used for examining the interrelationship between these offences - regression analysis using the Poisson regression model with a linear correction of the dispersion and dual kernel density estimation with a "hot spot" analysis. The study constitutes the first systematic attempt to analyse NSRM data with regard to the spatial distribution and spatial co-occurrence of two common offences in Krakow.

Abstract: . The article provides an overview of the features of the Magrit web application: a free online thematic mapping tool, presenting a strong pedagogical dimension and making possible to mobilize all the elements necessary for the realization of a thematic map. In this tool, several simple modes of representation are proposed such as proportional maps or choropleth maps. Other, more complex modes are also available such as smoothed maps and cartograms. Each map can be finalized thanks to layout and customization features (projection, scale, orientation, toponyms, etc.) and exported in vector format. Magrit is therefore a complete, light and versatile tool particularly adapted to cartography teaching at the university.

Abstract: Map-based regional analysis is interested to detect areas with a large concentration of certain populations. Here kernel density estimates (KDE) offer advantages over classical choropleth maps. However, kernel density estimation needs exact geo-coordinates. In a recent paper Gros et al. (2017) have proposed a measurement error model which uses local aggregates for kernel density estimation. Their algorithm simulates "exact" geo-coordinates which reflect the information on the aggregates. In this article we suggest two extensions of this approach. First, we consider boundary constraints, which are usually ignored in the KDE framework. This concerns not only the outer limits of a municipality but also unsettled regions within a city like parks, lakes and industrial areas. Without a boundary correction standard KDEs underestimate the density in the vicinity of boundaries. Here we propose a modification of the original algorithm which uses rescaled kernel functions. Regional maps often display local percentages, for example, voters for a special party among all voters in each voting district. Here we derive a smooth representation of percentages which is based on the ratio of two densities. Again, the original algorithm is modified to cope with the estimation of a ratio of two densities. Our empirical examples refer to voting results from Berlin. It is shown that the proposed methodology reveals a lot of regional insight which is not produced by standard choropleth maps.

Abstract: The Ministry of Regional Development and Public Administration (MRDPA) in Romania launched a large debate in regard to updating the National Territory Plan (PATN). According to Barca (2009) and McCann and Pose (2012) the success of public policies is conditioned by their simultaneous reliance on locations and people. The scope of this paper is to formulate a functional city definition on the background of place-based policy based on the New Geography Economy theory, supported by GIS (Anselin, 2002b, p.5). Our causality chain analysis concluded that the root cause of the public policies is space. We found and show spatial patterns of population, the density of population and population growth rates using ESDA tools choropleth maps (Jenks Classification, equal interval data, Statistical map), maps overlay and spatial correlation analysis at NUTS 5 and 3 level. The tendency is to shrinking wining agglomeration and to expanding the marginalised ones.

Abstract: The classification of data is an important step towards the elaboration of choropleth maps because the use of colors will be attributed to the basic spatial units in accordance with the classes defined. Another representation for quantitative data analysis is made through the usage of proportional symbols, which are appropriate to the data related to the dimension of the Basic Spatial Unit in relation to the phenomenon under consideration. At a given moment the responsible for the cartographic representation, which will be led to organize the presented data, and for that to happen, it is necessary to define the number of classes to be adopted, which colors or symbols scheme is the most appropriate and, among several classification criteria, which is the best appropriate for the phenomenon under study. In this work, contributions for better understanding and use with methodological basis of the criteria more commonly adopted in the classification and visual representation of geographic data to produce graphs, choropleth maps, maps of proportional symbols or, in addition, to explore the existing relationship between them.

Abstract: A purpose-built mobile data collection application is used to plan and implement community-oriented primary care (COPC) in a pilot project in the City of Tshwane (South Africa). Web reports present the data in the form of tables, graphs and point maps, but other types of thematic maps have not yet been implemented. We describe a proof-of-concept web map application that presents the COPC data in different cartographic representations. To reveal spatio-temporal patterns and correlations in the daily growing dataset, the user can choose between choropleth maps, segmented proportional circle maps, or a combination of these. The data is shown aggregated by administrative unit or by regular grid cell. As the user zooms in, the aggregation level automatically changes to smaller aggregation units. The setting of a threshold ensures data privacy protection. Spider diagrams link households visited by community health workers during a user-specified period to the sending clinic. The web maps can empower those involved in COPC to dynamically tailor health care provision to the complexity of people’s health needs. It is a valuable addition to the mobile application and web reports, and could contribute to more effective and efficient service delivery to meet the specificity of localized needs.

Abstract: The process of creating printed statistical maps in the predigital era was expensive and time consuming. These and other interacting factors constrained the number of design alternatives, such as color choices, that a cartographer might reasonably have been able to consider. In this article, we develop an approach to map deconstruction that enables researchers to investigate the statistical choices made by cartographers by placing each printed map into the universe of all possible choices available to them. We place a particular focus on the specification of choropleth map class intervals for maps produced in the early twentieth century. Three published choropleth maps are used as case studies to illustrate the approach, using four evaluation criteria to evaluate the accuracy of the data classifications. The results indicate that the class interval selection choices made for the examined maps are inferior when compared with available alternatives and that, in one case, classification errors are not only e...