Topic
Choropleth map
About: Choropleth map is a research topic. Over the lifetime, 369 publications have been published within this topic receiving 8331 citations. The topic is also known as: blot map.
Papers published on a yearly basis
Papers
TL;DR: The authors report results from 13 cognitive interviews that provide theory-based insights into how visual features influenced what participants saw and the meaning of what they saw as they viewed 3 formats of water test results for private wells.
Abstract: Theory-based research is needed to understand how maps of environmental health risk information influence risk beliefs and protective behavior. Using theoretical concepts from multiple fields of study including visual cognition, semiotics, health behavior, and learning and memory supports a comprehensive assessment of this influence. The authors report results from 13 cognitive interviews that provide theory-based insights into how visual features influenced what participants saw and the meaning of what they saw as they viewed 3 formats of water test results for private wells (choropleth map, dot map, and a table). The unit of perception, color, proximity to hazards, geographic distribution, and visual salience had substantial influences on what participants saw and their resulting risk beliefs. These influences are explained by theoretical factors that shape what is seen, properties of features that shape cognition (preattentive, symbolic, visual salience), information processing (top-down and bottom-up), and the strength of concrete compared with abstract information. Personal relevance guided top-down attention to proximal and larger hazards that shaped stronger risk beliefs. Meaning was more local for small perceptual units and global for large units. Three aspects of color were important: preattentive "incremental risk" meaning of sequential shading, symbolic safety meaning of stoplight colors, and visual salience that drew attention. The lack of imagery, geographic information, and color diminished interest in table information. Numeracy and prior beliefs influenced comprehension for some participants. Results guided the creation of an integrated conceptual framework for application to future studies. Ethics should guide the selection of map features that support appropriate communication goals.
43 citations
25 Jul 2001
TL;DR: Dynamaps is a generalized map-based information visualization tool for dynamic queries and brushing on choropleth maps that can be used to explore complex data sets more rapidly and effectively.
Abstract: Users who must combine demographic, economic or other data in a geographic context are often hampered by the integration of tabular and map representations. Static, paper-based solutions limit the amount of data that can be placed on a single map or table. By providing an effective user interface, we believe that researchers, journalists, teachers, and students can explore complex data sets more rapidly and effectively. This paper presents Dynamaps, a generalized map-based information visualization tool for dynamic queries and brushing on choropleth maps. Users can use color coding to show a variable on each geographic region, and then filter out areas that do not meet the desired criteria. In addition, a scatterplot view and a details-on-demand window support overviews and specific fact-finding.
43 citations
TL;DR: Two approaches to incorporate both point and areal data in the spatial interpolation of continuous soil attributes are presented and sensitivity analysis indicates that the new procedures improve prediction over ordinary kriging and traditional residual kriged based on the assumption that the local mean is constant within each mapping unit.
Abstract: Information available for mapping continuous soil attributes often includes point field data and choropleth maps (e.g. soil or geological maps) that model the spatial distribution of soil attributes as the juxtaposition of polygons (areas) with constant values. This paper presents two approaches to incorporate both point and areal data in the spatial interpolation of continuous soil attributes. In the first instance, area-to-point kriging is used to map the variability within soil units while ensuring the coherence of the prediction so that the average of disaggregated estimates is equal to the original areal datum. The resulting estimates are then used as local means in residual kriging. The second approach proceeds in one step and capitalizes on: 1) a general formulation of kriging that allows the combination of both point and areal data through the use of area-to-area, area-to-point, and point-to-point covariances in the kriging system, 2) the availability of GIS to discretize polygons of irregular shape and size, and 3) knowledge of the point-support variogram model that can be inferred directly from point measurements, thereby eliminating the need for deconvolution procedures. The two approaches are illustrated using the geological map and heavy metal concentrations recorded in the topsoil of the Swiss Jura. Sensitivity analysis indicates that the new procedures improve prediction over ordinary kriging and traditional residual kriging based on the assumption that the local mean is constant within each mapping unit.
43 citations
TL;DR: This paper explores the use of the Box-Cox family of power transformations to semiautomatically adjust visual parameters for more effective data visualization, focusing on time-series scaling, axis transformations, and color binning for choropleth maps.
Abstract: The concept of preconditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assumptions of statistical inference procedures, as well as making the data more symmetric and easier to visualize and interpret. In this paper, we explore the use of the Box-Cox family of power transformations to semiautomatically adjust visual parameters. We focus on time-series scaling, axis transformations, and color binning for choropleth maps. We illustrate the usage of this transformation through various examples, and discuss the value and some issues in semiautomatically using these transformations for more effective data visualization.
41 citations
TL;DR: In this article, the authors evaluated the potential of detailed observations made by a mobile, non-invasive proximal soil sensor to upgrade a part of the 1/20,000 choropleth soil map of Belgium.
39 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 19 |
| 2020 | 17 |
| 2019 | 26 |
| 2018 | 17 |
| 2017 | 19 |
| 2016 | 14 |