Abstract: Spatial patterns of murder and physical injury in Metro Manila, Philippines were visualised through conditional choropleth maps. Relationship of both crime rates with some demographic variables wer...

Abstract: In this paper, we present a community-focused drug abuse monitoring and supporting system, called DrugTracker, that utilizes social media and geospatial data in near real-time. Through the system, users can: (1) Detect drug abuse risk behaviors from social media platforms, e.g., Twitter; (2) Analyze drug abuse risk behaviors by querying consolidated and live datasets with keywords, spatial entities, and time constraints; and (3) Explore the query results and associated data through a web-based user interface in thematic choropleth, heatmap, and statistical charts. To protect the privacy of the Twitter users, whose data is collected, the system automatically hides the re-identification elements in tweets and aggregates the geo-tags into areas such as census tracts. For the demonstration purpose, our DrugTracker system is populated with a database that contains about 10 million tweets from the year 2017, that were annotated as drug abuse risk behavior positive by our deep learning model.

Abstract: Choropleth mapping is an essential visualization technique for exploratory spatial data analysis. Visualizing multiple choropleth maps is a technique that spatial analysts use to reveal spatiotemporal patterns of one variable or to compare the geographical distributions of multiple variables. Critical features for effective exploration of multiple choropleth maps are (1) automated computation of the same class intervals for shading different choropleth maps, (2) dynamic visualization of local variation in a variable, and (3) linking for synchronous exploration of multiple choropleth maps. Since the 1990s, these features have been developed and are now included in many commercial geographic information system (GIS) software packages. However, many choropleth mapping tools include only one or two of the three features described above. On the other hand, freely available mapping tools that support side-by-side multiple choropleth map visualizations are usually desktop software only. As a result, most existing tools supporting multiple choropleth-map visualizations cannot be easily integrated with Web-based and open-source data visualization libraries, which have become mainstream in visual analytics and geovisualization. To fill this gap, we introduce an open-source Web-based choropleth mapping tool called the Adaptive Choropleth Mapper (ACM), which combines the three critical features for flexible choropleth mapping.

Abstract: The “Technological Transition” has had a tremendous impact on cartographic processes and outputs. Atlases, whether national, regional or urban, were affected as they moved from a static to an animated and interactive era. The overall positive development, consolidated by map automation and map animation, has taken various forms and directions. Nevertheless, some graphic and cartographic outputs, especially atlases, still suffer from serious pitfalls, regarding some semiological aspects of the resulting maps and graphics. The Digital Urban Atlas of Jeddah (DUAJ) is a research in progress aware of such deficiencies. It tries to spare it from some frequent errors in map design related to: the choice of the base map, the use of some frequent symbols such as columns and pie charts for multivariate quantitative data, and the alternative solutions to choropleth maps. These deficiencies are selected and examined among others. The authors are convinced that the generated maps and diagrams that should be produced in digital atlases must be examined with regards to the semiological rules that drew upon the theory of signs perception. They try to incorporate the basic principles of graphic semiology reviewed, corrected and adapted to the GIS requirements. This is also meant to avoid map noises and deficiencies. The goal is to attract future Digital Atlases producers towards developing higher interest in map look and design and users to grasp messages rapidly. Specifically, the use of GIS and linked spatial databases within the DUAJ should not pay attention only to data handling and crossing, but also, to the semiological features of the outputs and relevant visual communication. In its preliminary stage, the DUAJ should give answers not only to the three questions raised in this research but also to others not examined here. This is to prevent from incorrect, irrelevant or inadequate use of the cartographic tools and, following the analysis of concrete examples, to propose a set of recommendations in establishing maps and graphics. When necessary, the DUAJ GIS-based outputs are inserted in CAD or CAC systems to benefit from some their specific visual tricks and subtleties that yield better legibility and efficiency of communication for Atlases users as recommended by authors. This experience is discussed regarding its eventual contribution to better map reading through some examples of maps and graphics from the DUAJ project (in progress).

Abstract: The prompt acquisition and distribution of precise disaster-related information are crucial for minimizing damage during disasters. Then, the prompt acquisition and distribution of precise disaster-related information are crucial. Therefore, the usefulness of social media such as Twitter, for disaster mitigation is gaining worldwide notice. In this study, by extracting words representing areas (prefecture names and municipality names) from Japanese tweets posted during large-scale disasters occurred in 2018 in Japan (Osaka Northern Earthquake that occurred in June and Heavy Rain Disaster in western Japan that occurred in July), we analyze the attention areas (areas mentioned a lot in tweets). Moreover, we implement an application to visualize the tweets analysis result in the form of a choropleth map and co-occurrence network. By using the proposed visualization application, we can easily understand how the attention area changes over time.

Abstract: We use data from the Behavioral Risk Factor Surveillance System, BRFSS, to investigate the important topic of health insurance coverage. Here, our investigation is about coverage in Florida at the county level and for important subpopulations defined by age, gender, and race. As large US government administered surveys are designed to provide reliable estimates of finite population characteristics for large geographical areas such as the entire US or for individual states, they are not designed to make direct inferences for small geographical regions and/or subpopulations. Given the importance of this topic, we use Bayesian predictive inference for the finite population quantities of interest, thus avoiding approximations necessary in other approaches. There are careful diagnostic checks of the model that we propose, including residual checks and cross-validation, together with formal tests of the concordance between the observed data and model. We check whether there is a selection bias investigating, in particular, the possible role of the conventional survey weights in correcting for selection bias and in improving inferences. We display our results in choropleth maps, together with displays of map variation. The latter maps can be used to assess the visual appearance of the "mean map", ie, the one usually presented, relative to a sequence of possible maps. Finally, we compare our county estimates of health insurance coverage with estimates from the BRFSS produced by the Centers for Disease Control and Prevention and from the US Census Bureau under their SAHIE program.

Abstract: . Small-scale thematic maps help to visualize world-wide data, yet small nations can be difficult to discern or are omitted completely. This occurs for small island developing states (SIDS), a group of more than fifty states recognized by the United Nations for their social, economic and environmental vulnerabilities. Through this study we proposed and evaluated alternative maps to increase the perceptibility of SIDS using indicator data of the Sustainable Development Goals (SDGs). These goals link social, economic and environmental objectives to achieve globally by 2030. Five cartographic solutions were refined to one based on input from two focus groups of geoinformation scientists and cartographers as well as an interview with a SIDS resident. The selected map was evaluated by a larger audience in an online survey. Most survey participants had some experience with SIDS, worked in international organizations and/or had graduate-level degrees in a geographic-related science. While recommendations for improvement were provided, nearly seventy percent of the participants agreed the presented design was appropriate to represent SIDS in choropleth world maps.

Abstract: . The need for presenting information in maps is increasingly high in various scientific fields. All scientific fields need to present effective data for decision making. Good decision making based on maps requires good understanding but not all scientific fields are familiar with using maps. Supporting factors for easy maps to understand are classification method and color symbol scheme. The purpose of this study was to select and test the classification method and the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The classification methods used in this study are constant interval, arithmetic progression, geometric progression, quantile, standard deviation and dispersal graph. The effectiveness test method for the most effective classification method is the proportion assessment. The color symbol scheme used in this study is a sequential color scheme, diverging color schemes, Corel Draw color schemes and color symbol schemes provided in ArcMap 10.3 software. The effectiveness test method for the most effective color symbol scheme is conventional eye tracking. The results showed that according to the proportion test the most effective classification method was the arithmetic interval classification method with results of 0.26. The most effective color symbol scheme in accordance with the effectiveness test using the conventional eye tracking method shows that the most effective color symbol scheme is a diverging color scheme. The important aspects to consider are average answering duration of 8.15 seconds, the accuracy of the answer is 98.9%, and easiness level of symbolization readings is 341. This research can be one of the references on the most effective classification method and reference regarding the selection of the most effective color symbol scheme on Choropleth Map of Population Density in Special Region of Yogyakarta, so that further research can continue the analysis of appropriate classification methods for demographic data. The method discussed in this study is also expected to be applicable to other data.

Abstract: Background In the last decades, the issues related to health risk communication to stakeholders and citizens involving health care practitioners and local political authorities have been increasingly debated. The study evaluated an alternative strategy to communicate cancer risk to local communities, involving an expert panel of public health operators in comparing two different graphic tools, Funnel Plot and Choropleth map. Study design A Delphi method process was implemented to achieve a unified consensus on an expert panel of public health operators with regard to weaknesses and strengths of the Funnel Plot and the Choropleth map as tools for cancer risk communication to local communities and other stakeholders. Methods Participants were asked to score the efficacy of the two tools using a scale. Six properties were explored through two consecutive consensus rounds. Scales were used to calculate frequencies and the content validity ratio for each domain within the consensus rounds. Results After the two consecutive rounds, participants expressed their preference in favour of the Choropleth map for its ability to define the spatial location of the risk and to locate any potential cluster, while reaching a consensus with regard to the Funnel Plot properties to identify hot spots, displaying the scope of the phenomenon under investigation, and to show the precision of estimates and communicating the significance of estimates. Conclusions The Delphi process allowed us to conclude that Funnel Plot could be used as a complement to the current and commonly used graphical and visual formats to effectively communicate cancer epidemiological data to communities and local authorities, representing a useful tool for empowering the general population.

Abstract: . The choropleth is a widely used thematic map type. But it is not always ideal to visualize social data in engaging and accurate ways, especially as a standalone map. In this paper we discuss choropleths and two thematic map types with altered geometry: area cartograms and tile maps with repeating icons. To identify benefits and drawbacks of each, we created a choropleth, contiguous cartogram, and repeating icon tile map visualizing the same data from the United Nations Sustainable Development Goal (SDG) indicator about the proportion of women and girls aged 15–49 who have undergone female genital mutilation/cutting in African countries, from SDG 5, on Gender Equality. We conducted a qualitative online survey to collect users evaluations, through informational tasks, quality ratings, and open-ended questions based on interaction with the maps. Results of this preliminary investigation suggest that though users are familiar and therefore more comfortable with choropleth maps, they interpreted thematic map types differently. Specifically, the relative novelty and unfamiliarity of the distorted geometry of cartograms and tile maps may have caused users to engage more thoughtfully with the visualized data and in the cartogram and tile map which are generally considered non-standard thematic maps.

Abstract: The choropleth is a widely used thematic map type. But it is not always ideal to visualize social data in engaging and accurate ways, especially as a standalone map. In this paper we discuss choropleths and two thematic map types with altered geometry: area cartograms and tile maps with repeating icons. To identify benefits and drawbacks of each, we created a choropleth, contiguous cartogram, and repeating icon tile map visualizing the same data from the United Nations Sustainable Development Goal (SDG) indicator about the proportion of women and girls aged 15-49 who have undergone female genital mutilation/cutting in African countries, from SDG 5, on Gender Equality. We conducted a qualitative online survey to collect users evaluations, through informational tasks, quality ratings, and open-ended questions based on interaction with the maps. Results of this preliminary investigation suggest that though users are familiar and therefore more comfortable with choropleth maps, they interpreted thematic map types differently. Specifically, the relative novelty and unfamiliarity of the distorted geometry of cartograms and tile maps may have caused users to engage more thoughtfully with the visualized data and in the cartogram and tile map which are generally considered non-standard thematic maps.

Abstract: New Zealand has two top-level sets of administrative divisions: the District Health Boards and the Regions. In this note I describe a hexagonal layout for creating stylised maps of these divisions, and using colour, size, and triangular subdivisions to compare data between divisions and across multiple variables. I present an implementation in the DHBins package for R using both base graphics and ggplot2; the concepts and specific hexagonal layout could be used in any software.

Abstract: Small-scale thematic maps help to visualizeworld-wide data, yet small nations can be difficult to discern or are omitted completely. This occursfor small island developing states (SIDS), a group of more than fifty states recognized by the United Nations for their social, economic and environmental vulnerabilities. Through this study we proposed and evaluated alternative maps to increase the perceptibility of SIDS using indicator data of the Sustainable Development Goals (SDGs). These goals link social, economic and environmental objectives to achieve globally by 2030. Five cartographic solutions were refined to one based on input from two focus groups of geoinformation scientists and cartographers as well as an interview with a SIDS resident. The selected map was evaluated by a larger audience in an online survey. Most survey participants had some experience with SIDS, worked in international organizations and/or had graduate-level degrees in a geographic-related science. While recommendations for improvement were provided, nearly seventy percent of the participants agreed the presented design was appropriate to represent SIDS in choropleth world maps.

Abstract: The advent of Smart City and Big Data have generated many data on demographical factors, such as health, public transportation, basic sanitation, education, among others. However, this growing volume of data is little related to their demographic contexts, and when maps represent these data, they generally do not have the interactivity to allow exploration, either by changing the studied territory, increasing or decreasing its scope, relating other data for analysis, visually encoding a data, among other possibilities. Thus, this work aims to present a system that represents demographic data, specifically in geographic maps, and how to make it interactive for the user, presenting the software ChoroLibre as a final product: an opensource tool for visualizing hierarchical and interactive Choropleth geographic maps for the Web. To this end, this paper describes the architecture, implementation, methodology, technologies, and the developed functionalities of the ChoroLibre tool.

Abstract: The purpose of this study is to provide practical evidences that thematic maps that do not comply with the thematic mapping principles can make it difficult for students to intuitively understand geographical facts and may even lead to inaccurate understanding of geographical facts. For this, a questionnaire was developed to evaluate the understanding of geographical facts by using thematic maps in secondary school textbooks, which did not comply with thematic mapping principles. The main findings were as follows. First, students showed difficulty in intuitive interpretation of data in thematic maps with color arrangements that do not follow data characteristics. Students also showed a tendency to interpret data in the light of contextual knowledge or personal experience rather than maps themselves. In addition, there is a possibility of incorrectly understanding the data due to color arrangements which does not fit the characteristics of the data. Second, in the case of the thematic map which does not reflect the critical value for the interpretation of the data in data classification, the students have difficulty in intuitively interpreting the data by attempting additional analysis. Finally, in the case of a thematic map displaying totals, the area difference of the basic spatial units in which the data are aggregated greatly influences the interpretation of the data, thereby causing the students to interpret the data represented on the map differently from the actual.

Abstract: This paper presents IDUVis, an interactive visualization tool for the analysis of the VAST 2019 Mini-Challenge 1 dataset. Four connected visualizations compose the tool: a timeline for temporal overview tasks, choropleth maps for spatial overview tasks, horizon-histograms for comparing data distributions and uncertainties, and steamgraphs for details on-demand on how distributions change over time. The timeline allows selecting specific time ranges for analysis, while maps and histograms allow selecting locations and categories to visualize their distribution over time with steamgraphs.

Abstract: During the Second World War, the U.S. Bureau of the Census published a novel population density map for the U.S. that used minor civil divisions as its areal basis. Prior to that time, the ...

Abstract: Map can show information needed by map users from various scientific fields, especially in Indonesia. Effective maps can help users understand. One of the factors that influence the effectiveness of map reading is the color symbol scheme used in symbolization. Effectiveness’ study of color symbol scheme applied on choropleth mapping. Choropleth map is using population density data in Special Region of Yogyakarta. The selection of the study area in the Special Province of Yogyakarta is because the Special Region of Yogyakarta is one of the provinces in Indonesia which has a fairly high population density in the area of 3,185.80 km2 . In 2016, the population density of the Special Province of Yogyakarta ranked 4th in the Indonesian Statistics 2017 by the Central Bureau of Statistics, which amounted to 1,188 population per km2 . The effectiveness of color symbol schemes adapts the capabilities of each user. This study is expected to be able to study the effect of age group differences on maps with the best color symbol scheme. All scientific field that used choropleth map of population density consist of 2 age groups, those are 20-25 years old and >5 years old respondents. The purpose of this study was to observe age group influence for the most effective color symbol scheme for mapping population density in the Special Region of Yogyakarta. The result of this study shows the difference between age group based on the important aspects of conventional-eye tracking. The important aspects to consider are average answering duration, the accuracy of the answer and easiness level of symbolization readings. The first group (20-25 years) shows map 3 (diverging color scheme) as a map with the most effective color symbol scheme. While group 2 (>25 years) shows map 1 (ArcGIS 10.3 color scheme) as a map with the most effective color symbol scheme. This research is expected to be able to show the influence of age in determining the best color symbol scheme on population density maps so that its effectiveness can be adjusted specifically to map users.

Abstract: . The ability of identifying objects and elements based on colour is important in order to decode the information in a map or other information graphics. For this reason, the colours need to appear correct and be perceived in the desired and intended way. Map reading is reported as a challenging task for people with impaired colour vision. In reviews of the challenges of colour vision deficiencies (CVD) in everyday life (Cole, 2004), up to 60 % of the subjects in the studies reported problems in reading colour coded charts, slides and prints. Other studies (Carter and Silverstein, 2010) describes the difficulties to distinguish and identify coloured objects in weather, financial and other maps and charts. Colour vision deficiencies are common, where congenital CVD affects about 8 % of the male population and 0.4 % of the female population. In addition, colour vision and colour perception may be affected by medical conditions or injury (acquired CVD) and situational conditions (situation induced CVD). Reviews of visual usability and accessible map design conclude that few maps appear to have been designed with CVD users in mind (Cartwright, 2015) and that the design efforts or research of accessible colours palettes for CVD observers are mostly limited to thematic maps such as choropleths (Kvitle, 2018). Daltonization methods are image processing methods to automatically enhance information in existing images. A common enhancement method is re-colouring, changing the colours in the original image to make be more distinguishable to the CVD observers. The daltonization method targets a specific type of CVD, and may also have been designed for specific applications (natural images, scientific images, information graphics etc). Therefore, the evaluation of the methods is often based on a limited set of test images. Using one specific map image as input will give very different results based on the daltonization methods. The aim of the work is primarily to examine how the colour palettes in a map are altered by different daltonization methods. Second, the aim is to explore how different map types are influenced by the daltonization methods and to propose requirements and guidelines for test images for future work. The set of test images in this work includes Information graphics (such as a tube map). Choropleth map. Reference map based on different map providers. To illustrate the visual differences, CVD simulation methods are applied on the original images and the daltonized versions of the images.

Abstract: The analysis of oceanographic data is a difficult task due to the large volume and multidimensionality of the data. Often is it necessary to aggregate other datasets to establish relationships and more complex analysis in order to answer environmental questions. Thus, this work aims to present different information visualization techniques (InfoVis) for oceanographic data concerning the most frequently used techniques, such as 2D and 3D Charts, Surface Map, Choropleth Map, and Line Map. For this purpose, a dataset of oceanographic buoys from the National Oceanic and Atmospheric Administration (NOAA) covering a period of 02 years (from 2015 to 2016) was used. This set of data was treated and classified according to the seasonal periods (winter, spring, summer, and autumn). The Rose Wind technique revealed that the wind speed average was between 10- 12 m/s. The Circle Parking technique showed a predominance of wind and waves from NE. In 2015, highest waves were recorded, mainly during the winter. The obtained results can be considered a useful tool for the assessment of the wind and waves relationship and help to coastal management strategies.

Abstract: Background: There are interests in the use geospatial data for development of acute stroke services given the importance of timely acess to acute reperfusion therapy. This paper aims to introduce clinicians and citizen scientists to the possibilities offered by open source softwares (R and Python) for analyzing geospatial data. It is hope that this introduction would stimulate interest in the field as well as generate ideas for improving stroke services. Method: Instructions on installation of libraries for R and Python, source codes and links to census data are provided in a notebook format to enhance experience with running these softwares. These codes illustrate different aspects of using geospatial analysis: 1)- creation of choropleth (thematic) map which depicts estimate of stroke cases per post codes; 2) use of map to help define service regions for rehabilitation after stroke. Results: Choropleth map showing estimate of stroke per post codes and service boundary map for rehabilitation after stroke. Conclusions The examples in this article illustrate the use of a range of components that underpin geospatial analysis. By providing an accessible introduction to these areas, clinicians and researchers can create code to answer clinically relevant questions on topics such as service delivery and service demand.