xii, 80 p. : ill., maps (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Choropleth maps are a popular way of depicting spatial data. The map communication model, which theorizes that geographic information is transmitted from the cartographer to the map user via a map, suggests that cartographers are responsible for clearly conveying spatial data in a way all map users can understand. Map users, however, come from different places and may harbor certain regional biases. This thesis investigates whether map users tend to focus on data patterns within their home regions during the visual-search and decision-making processes when reading classed choropleth maps, thereby exhibiting an egocentric map behavior. Seventy-one subjects took a computer-based test asking them to identify various phenomena on a series of choropleth maps of the lower 48 states. The results show a weak positive effect of egocentric map behavior; subjects who lived in a particular state longer were slightly more likely to choose states nearby their home region. / Committee in Charge: Dr. Amy Lobben, Chair; Dr. Dan Gavin

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliography.

The p-Median problem (PMP) is one of the most widely applied location problems in urban and regional planning to support spatial decision-making. As an NP-hard problem, the PMP remains challenging to solve optimally, especially for large-sized problems. This research focuses on developing geocomputational approaches to improve the effectiveness and efficiency of solving the PMP. This research also examines existing PMP methods applied to choropleth mapping and proposes a new approach to address issues associated with uncertainty. Chapter 2 introduces a new algorithm that solves the PMP more effectively. In this chapter, a method called the spatial-knowledge enhanced Teitz and Bart heuristic (STB) is proposed to improve the classic Teitz and Bart (TB) heuristic.. The STB heuristic prioritizes candidate facility sites to be examined in the solution set based on the spatial distribution of demand and candidate facility sites. Tests based on a range of PMPs demonstrate the effectiveness of the STB heuristic. Chapter 3 provides a high performance computing (HPC) based heuristic, Random Sampling and Spatial Voting (RSSV), to solve large PMPs. Instead of solving a large-sized PMP directly, RSSV solves multiple sub-PMPs with each sub-PMP containing a subset of facility and demand sites. Combining all the sub-PMP solutions, a spatial voting strategy is introduced to select candidate facility sites to construct a PMP for obtaining the final problem solution. The RSSV algorithm is well-suited to the parallel structure of the HPC platform. Tests with the BIRCH dataset show that RSSV provides high-quality solutions and reduces computing time significantly. Tests also demonstrate the dynamic scalability of the algorithm; it can start with a small amount of computing resources and scale up or down when the availability of computing resources changes. Chapter 4 provides a new classification scheme to draw choropleth maps when data contain uncertainty. Considering that units in the same class on a choropleth map are assigned the same color or pattern, the new approach assumes the existence of a representative value for each class. A maximum likelihood estimation (MLE) based approach is developed to determine class breaks so that the overall within-class deviation is minimized while considering uncertainty. Different methods, including mixed integer programming, dynamic programming, and an interchange heuristic, are developed to solve the new classification problem. The proposed mapping approach is then applied to map two American Community Survey datasets. The effectiveness of the new approach is demonstrated, and the linkage of the approach with the PMP method and the Jenks Natural Breaks is discussed.

This thesis uses the United Nations Human Development Index as a model for comparing a selected set of socioeconomic indicators across Florida’s sixty-seven counties. Whether for urban planning, hazards mitigation, transportation forecasting, or other county-level and state-level functions, information and understanding of socioeconomic conditions are keys to efficient planning and policy making, both in the early development stages as well as during implementation. A summary overview of socioeconomic well-being and its distribution across a given area offers a distinct advantage in terms of deciding where planning or policy changes are most needed and where they will prove most beneficial. This thesis takes a well-established and well documented index used for examining and comparing human development in nations across the globe, and modifies it for comparing county-level socioeconomic conditions across Florida. The results from this modified index are then displayed using choropleth maps as an aid to location interpretation of the ranked socioeconomic values, thereby providing a spatial context for the indexing. In the end, this thesis seeks to answer whether or not the modified index model is a suitable one for normalizing, aggregating, and ranking county-level socioeconomic data for Florida, and whether the use of choropleth mapping to display the rankings is a viable choice.

abstract: Choropleth maps are a common form of online cartographic visualization. They reveal patterns in spatial distributions of a variable by associating colors with data values measured at areal units. Although this capability of pattern revelation has popularized the use of choropleth maps, existing methods for their online delivery are limited in supporting dynamic map generation from large areal data. This limitation has become increasingly problematic in online choropleth mapping as access to small area statistics, such as high-resolution census data and real-time aggregates of geospatial data streams, has never been easier due to advances in geospatial web technologies. The current literature shows that the challenge of large areal data can be mitigated through tiled maps where pre-processed map data are hierarchically partitioned into tiny rectangular images or map chunks for efficient data transmission. Various approaches have emerged lately to enable this tile-based choropleth mapping, yet little empirical evidence exists on their ability to handle spatial data with large numbers of areal units, thus complicating technical decision making in the development of online choropleth mapping applications. To fill this knowledge gap, this dissertation study conducts a scalability evaluation of three tile-based methods discussed in the literature: raster, scalable vector graphics (SVG), and HTML5 Canvas. For the evaluation, the study develops two test applications, generates map tiles from five different boundaries of the United States, and measures the response times of the applications under multiple test operations. While specific to the experimental setups of the study, the evaluation results show that the raster method scales better across various types of user interaction than the other methods. Empirical evidence also points to the superior scalability of Canvas to SVG in dynamic rendering of vector tiles, but not necessarily for partial updates of the tiles. These findings indicate that the raster method is better suited for dynamic choropleth rendering from large areal data, while Canvas would be more suitable than SVG when such rendering frequently involves complete updates of vector shapes. / Dissertation/Thesis / Ph.D. Geography 2013

Presenting large amount of Multivariate Data is not a simple problem. When there are multiple correlated variables involved, it becomes difficult to comprehend data using traditional ways. Information Visualization techniques provide an interactive way to present and analyze such data. This thesis has been carried out at ABB Corporate Research, Västerås, Sweden. Use of Parallel Coordinates and Multiple Coordinated Views was has been suggested to realize interactive reporting and trending of Multivariate Data for ABB’s Network Manager SCADA system. A prototype was developed and an empirical study was conducted to evaluate the suggested design and test it for usability from an actual industry perspective. With the help of this prototype and the evaluations carried out, we are able to achieve stronger results regarding the effectiveness and efficiency of the visualization techniques used. The results confirm that such interfaces are more effective, efficient and intuitive for filtering and analyzing Multivariate Data.

The diploma thesis deals with the identification and analysis of misconceptions that are formed when the ninth grade pupils work with thematic maps of quantitative mapping methods, specifically with the choropleth map and proportional symbol map. The theoretical introduction defines the tested mapping methods, reviews previous foreign and Czech studies of map skills, and describes misconceptions that are formed both in cartography in general and specifically when working with thematic maps of quantitative mapping methods. The theoretical part is followed by the practical part - the research methodology and the design of an open conceptual test itself. The test is compiled according to the concept map, which was based on the literature review of previous empirical studies and theoretical publications. From the conceptual map eight propositions (statements) that are key to understanding the concept of choropleth map and proportional symbol map were determined based on an expert evaluation. The conceptual test was used to reveal misconceptions that are formed when working with these mapping methods. A total of 257 pupils from eight primary schools across Czechia took part in the testing and a total of 59 misconceptions of varying severity and frequency were revealed. These misconceptions were then...

<p>The population of Sweden is ageing as in almost every European country. Improved medical progresses and treatment options lead to a decreasing mortality at older ages, increasing life expectance and an advanced health of the elderly. Due to these improvements and the so called ‘baby- boomers’, a great number of persons born in the 1940s that will reach retirement age the coming years, their total number will increase strongly in the near future all over Sweden. To enable these elderly to live a normal, active and independent life as long as possible activities, services and special housing with improved accessibility and meeting places for elderly has to be provided. Thus, for local authorities it is essential to know the actual and favoured living conditions as well as environments of elderly. This study aims therefore to investigate the characteristic of preferred residential neighbourhoods of the elderly in the city of Norrköping. The demographic, social and crime situation was examined for the districts of the city using several methods from both Statistics and GIS. Statistical methods included classifications, indexes or indicators and bivariate correlations. A model was developed to combine demographic and social data to characterise districts. GIS was to a major extent used as a visualisation tool. Choropleth mapping and Kernel density estimations were used to illustrate distribution of elderly and crime. Preliminary global statistical tests were used to verify clustering in the crime data set. An accessibility analysis was conducted with the help of the network analyst tool. Results indicate that districts experiencing the highest total numbers and proportion of elderly are very distributed throughout the city of Norrköping. They are, with some exceptions, characterised by lower social status. Four districts of the city show considerable evidences of demographic ageing, experiencing a population pyramid formed like an urn. Beside districts where elderly constitute a bigger proportion of the population, they tend to live in districts characterised by a relatively high proportion of young adults aged between 20 and 29. Crime analyses have shown crime clusters in different parts of the city. A high proportion of elderly faces a high crime level in the districts Gamla staden, Nordantill and Hageby. However, it has been proved that only some hot spots of crime within these areas contribute to the high crime level. Districts such as Skarphagen, Såpkullen, Smedby and Linö, all (except Såpkullen) situated on the outskirts of the city, hold high or middle elderly and a low crime level. Accessibility analyses have shown that elderly aged over 80 do not live significant closer to health centres and the public transport stops compared to the age groups 20 – 65 and inhabitants aged between 65 and 79.</p>

The population of Sweden is ageing as in almost every European country. Improved medical progresses and treatment options lead to a decreasing mortality at older ages, increasing life expectance and an advanced health of the elderly. Due to these improvements and the so called ‘baby- boomers’, a great number of persons born in the 1940s that will reach retirement age the coming years, their total number will increase strongly in the near future all over Sweden. To enable these elderly to live a normal, active and independent life as long as possible activities, services and special housing with improved accessibility and meeting places for elderly has to be provided. Thus, for local authorities it is essential to know the actual and favoured living conditions as well as environments of elderly. This study aims therefore to investigate the characteristic of preferred residential neighbourhoods of the elderly in the city of Norrköping. The demographic, social and crime situation was examined for the districts of the city using several methods from both Statistics and GIS. Statistical methods included classifications, indexes or indicators and bivariate correlations. A model was developed to combine demographic and social data to characterise districts. GIS was to a major extent used as a visualisation tool. Choropleth mapping and Kernel density estimations were used to illustrate distribution of elderly and crime. Preliminary global statistical tests were used to verify clustering in the crime data set. An accessibility analysis was conducted with the help of the network analyst tool. Results indicate that districts experiencing the highest total numbers and proportion of elderly are very distributed throughout the city of Norrköping. They are, with some exceptions, characterised by lower social status. Four districts of the city show considerable evidences of demographic ageing, experiencing a population pyramid formed like an urn. Beside districts where elderly constitute a bigger proportion of the population, they tend to live in districts characterised by a relatively high proportion of young adults aged between 20 and 29. Crime analyses have shown crime clusters in different parts of the city. A high proportion of elderly faces a high crime level in the districts Gamla staden, Nordantill and Hageby. However, it has been proved that only some hot spots of crime within these areas contribute to the high crime level. Districts such as Skarphagen, Såpkullen, Smedby and Linö, all (except Såpkullen) situated on the outskirts of the city, hold high or middle elderly and a low crime level. Accessibility analyses have shown that elderly aged over 80 do not live significant closer to health centres and the public transport stops compared to the age groups 20 – 65 and inhabitants aged between 65 and 79.

Olika typer av data genereras kontinuerligt varje sekund och för att kunna analysera denna data måste den transformeras till någon typ av visuell representation. En vanlig typ av data är spatio-temporal data, vilket är data som existerar i både rymd och tid. Hur denna typ av data kan visualiseras har undersökts under en lång period och området är fortfarande relevant idag. Ett antal metoder har undersökts i detta arbete och en genomgående litteraturstudie har genomförts. En applikation som implementerar ett antal av dessa undersökta metoder för att visualisera klimatdata har även skapats. / Different kinds of data is generated continuously every second and in order to be ableto analyze this data it has to be transformed into some kind of visual representation. Onecommon type of data is spatio-temporal data, which is data that exists in both space andtime. How to visualize this kind of data have been researched for a long time and is still avery relevant subject to expand on today. A number of approaches have been explored inthis work. An extensive literature study has also been performed and can be read in thisreport. The study has been divided into different classifications of spatio-temporal dataand the visual representations are structured by these classes.Another contribution of this thesis is a climate data application to visualize spatiotemporaldata sets of temperatures collected for several countries in the world. This applicationimplements several of the visual representations presented in the survey includedin this thesis. This resulted in a four display application, each showing a different aspect ofthe chosen data sets that consisted of climate data. The result shows how effective multiplelinked views are in order to understand different characteristics of the data.