Advanced

Analytical Estimation of Map Readability

Harrie, Lars LU ; Stigmar, Hanna LU and Djordjevic, Milan (2015) In ISPRS International Journal of Geo-Information 4(2). p.418-446
Abstract
Readability is a major issue with all maps. In this study, we evaluated whether we can predict map readability using analytical measures, both single measures and composites of measures. A user test was conducted regarding the perceived readability of a number of test map samples. Evaluations were then performed to determine how well single measures and composites of measures could describe the map readability. The evaluation of single measures showed that the amount of information was most important, followed by the spatial distribution of information. The measures of object complexity and graphical resolution were not useful for explaining the map readability of our test data. The evaluations of composites of measures included three... (More)
Readability is a major issue with all maps. In this study, we evaluated whether we can predict map readability using analytical measures, both single measures and composites of measures. A user test was conducted regarding the perceived readability of a number of test map samples. Evaluations were then performed to determine how well single measures and composites of measures could describe the map readability. The evaluation of single measures showed that the amount of information was most important, followed by the spatial distribution of information. The measures of object complexity and graphical resolution were not useful for explaining the map readability of our test data. The evaluations of composites of measures included three methods: threshold evaluation, multiple linear regression and support vector machine. We found that the use of composites of measures was better for describing map readability than single measures, but we could not identify any major differences in the results of the three composite methods. The results of this study can be used to recommend readability measures for triggering and controlling the map generalization process of online maps. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
cartography, map readability, usability, user test, supervised learning
in
ISPRS International Journal of Geo-Information
volume
4
issue
2
pages
418 - 446
publisher
MDPI AG
external identifiers
  • wos:000358987600001
  • scopus:84948968569
ISSN
2220-9964
DOI
10.3390/ijgi4020418
language
English
LU publication?
yes
id
040af83d-1924-4c62-92ec-eb2fec56e89d (old id 7975596)
date added to LUP
2015-09-24 16:54:17
date last changed
2017-06-11 04:22:33
@article{040af83d-1924-4c62-92ec-eb2fec56e89d,
  abstract     = {Readability is a major issue with all maps. In this study, we evaluated whether we can predict map readability using analytical measures, both single measures and composites of measures. A user test was conducted regarding the perceived readability of a number of test map samples. Evaluations were then performed to determine how well single measures and composites of measures could describe the map readability. The evaluation of single measures showed that the amount of information was most important, followed by the spatial distribution of information. The measures of object complexity and graphical resolution were not useful for explaining the map readability of our test data. The evaluations of composites of measures included three methods: threshold evaluation, multiple linear regression and support vector machine. We found that the use of composites of measures was better for describing map readability than single measures, but we could not identify any major differences in the results of the three composite methods. The results of this study can be used to recommend readability measures for triggering and controlling the map generalization process of online maps.},
  author       = {Harrie, Lars and Stigmar, Hanna and Djordjevic, Milan},
  issn         = {2220-9964},
  keyword      = {cartography,map readability,usability,user test,supervised learning},
  language     = {eng},
  number       = {2},
  pages        = {418--446},
  publisher    = {MDPI AG},
  series       = {ISPRS International Journal of Geo-Information},
  title        = {Analytical Estimation of Map Readability},
  url          = {http://dx.doi.org/10.3390/ijgi4020418},
  volume       = {4},
  year         = {2015},
}