Book Chapter10.1007/978-3-319-57336-6_31
Data Classification for Highlighting Polygons with Local Extreme Values in Choropleth Maps
Jochen Schiewe
- 02 Jul 2017
- pp 449-459
6
TL;DR: A new method (called PLEX) is presented for the preservation and highlighting of local extreme values in choropleth maps, and the application and the effectiveness of this method will be demonstrated using real-world examples.
read more
Abstract: Following the general demand for task-orientation in map design, one specific task will be examined here: the preservation and highlighting of local extreme values in choropleth maps Extreme value polygons are ones that show a larger (local maximum) or smaller (local minimum) attribute value compared to all directly neighboring polygons For a visual identification in a classified choropleth map, such a polygon must belong to a class other than the surrounding polygons However, data classification methods that are commonly used in the process of generating choropleth maps are data-driven, ie, the intervals are determined solely on the basis of the present frequency distribution of the original values With such a division along the number line, the spatial context of the underlying data is completely neglected and with that the desired categorization for local extreme values is not guaranteed As a consequence, a new method (called PLEX) is presented for this purpose The application and the effectiveness of this method will be demonstrated using real-world examples
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Advances in Cartography and GIScience
Michael P. Peterson
- 01 Jan 2017
TL;DR: De Menezes et al. as discussed by the authors used ArcGIS 10.1 software with different transformations: zero order polynomial, 1st Order Polynomial (Affine), 2nd Order Polymorphial (2PO), 3PO, Adjust, Projective Transformation, and Spline.
38
An open source tool for preserving local extreme values and hot/cold spots in choropleth maps
Juiwen Chang,Jochen Schiewe +1 more
- 01 Nov 2018
TL;DR: Schiewe et al. as mentioned in this paper showed that 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, and that important spatial characteristics like extreme values, hot spots or dusters might get lost due to an unfavorably setting of class breaks.
3
Development and comparison of uncertainty measures in the framework of a data classification
TL;DR: This article aims to define those which are concerned with the preservation of spatial patterns as well as with visual perception, and shows that the uncertainty measures can not only be used individually or combined for pure evaluation purposes, but also for a-posteriori improvement of classification methods.
Data classification methods for preserving spatial patterns
Jochen Schiewe
TL;DR: Researchers propose a task-oriented data classification method to preserve spatial patterns in choropleth maps, developing algorithms for specific patterns such as extreme values, spatial clusters, and hot/cold spots, to ensure accurate representation of spatial relationships.
Identifying representative watershed for the Urmia Lake Basin, Iran
TL;DR: A quantitative-based method of Representative Watershed Index (RWI) with potential range from 0 to 100 has been formulated using four important criteria and available national-wide raster data of elevation, slope, rainfall erosivity factor, and land use for the Urmia Lake Basin, north-western Iran, as a case study.
References
•Book
How to Lie with Maps
Mark Monmonier
- 01 Jan 1991
TL;DR: The second edition is updated with the addition of two new chapters, 10 color plates, and a new foreword by renowned geographer H. J. de Blij.
1.3K
It's About Time: A Conceptual Framework for the Representation of Temporal Dynamics in Geographic Information Systems
TL;DR: In this article, a Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields is presented.
737
•Book
Exploratory Analysis of Spatial and Temporal Data: A Systematic Approach
Natalia Andrienko,Gennady Andrienko +1 more
- 02 Dec 2005
TL;DR: The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular, developing a general view of data structures and characteristics and building on top of this a general task typology.
651
Exploratory cartographic visualization: advancing the agenda
TL;DR: It is argued that a use-based approach is needed in order to develop information processing environments appropriate to distinct stages of scientific research and decision making.
431
Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series
TL;DR: The authors compared seven methods using responses by fifty-six subjects in a two-part experiment involving nine series of U.S. mortality maps and found that matched legends across a series of maps (when possible) increased map-comparison accuracy by approximately 28 percent.
429