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An evaluation of measures for quantifying map information

Harrie, Lars LU and Stigmar, Hanna LU (2010) In ISPRS Journal of Photogrammetry and Remote Sensing 65(3). p.266-274
Abstract
A real-time map must not contain too much information. Therefore, we need measures of map information that could guideline the selection of data layers and the real-time generalisation process. In this paper we evaluate

measures of amount of information and distribution of information. The evaluation is performed by (1) defining measures, (2) implementing the measures, (3) computing the measures for some test maps, and finally (4)

comparing the values of the measures with human judgement of the map information. For amount of information, we found that the measures number of objects, number of points and object line length had better correspondence with human judgement than object area. We also found that measures based on... (More)
A real-time map must not contain too much information. Therefore, we need measures of map information that could guideline the selection of data layers and the real-time generalisation process. In this paper we evaluate

measures of amount of information and distribution of information. The evaluation is performed by (1) defining measures, (2) implementing the measures, (3) computing the measures for some test maps, and finally (4)

comparing the values of the measures with human judgement of the map information. For amount of information, we found that the measures number of objects, number of points and object line length had better correspondence with human judgement than object area. We also found that measures based on the size of Voronoi regions (of objects respective points) can be used for identifying distribution of information. The

results are based on the testing of only building objects. Future work should extend the test, using all object types. (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
Analysis, Generalisation, Cartography, Visualization, Simplification
in
ISPRS Journal of Photogrammetry and Remote Sensing
volume
65
issue
3
pages
266 - 274
publisher
Elsevier
external identifiers
  • WOS:000278531700003
  • Scopus:77953136681
ISSN
0924-2716
DOI
10.1016/j.isprsjprs.2009.05.004.
language
English
LU publication?
yes
id
a9401d81-54fc-4917-819f-a7b60247ac33 (old id 706072)
date added to LUP
2010-12-29 13:02:53
date last changed
2016-10-13 04:31:23
@misc{a9401d81-54fc-4917-819f-a7b60247ac33,
  abstract     = {A real-time map must not contain too much information. Therefore, we need measures of map information that could guideline the selection of data layers and the real-time generalisation process. In this paper we evaluate<br/><br>
measures of amount of information and distribution of information. The evaluation is performed by (1) defining measures, (2) implementing the measures, (3) computing the measures for some test maps, and finally (4)<br/><br>
comparing the values of the measures with human judgement of the map information. For amount of information, we found that the measures number of objects, number of points and object line length had better correspondence with human judgement than object area. We also found that measures based on the size of Voronoi regions (of objects respective points) can be used for identifying distribution of information. The<br/><br>
results are based on the testing of only building objects. Future work should extend the test, using all object types.},
  author       = {Harrie, Lars and Stigmar, Hanna},
  issn         = {0924-2716},
  keyword      = {Analysis,Generalisation,Cartography,Visualization,Simplification},
  language     = {eng},
  number       = {3},
  pages        = {266--274},
  publisher    = {ARRAY(0xa8f02d8)},
  series       = {ISPRS Journal of Photogrammetry and Remote Sensing},
  title        = {An evaluation of measures for quantifying map information},
  url          = {http://dx.doi.org/10.1016/j.isprsjprs.2009.05.004.},
  volume       = {65},
  year         = {2010},
}