Header

UZH-Logo

Maintenance Infos

Do the visual complexity algorithms match the generalization process in geographical displays?


Brychtova, Alzbeta; Coltekin, Arzu; Paszto, Vit (2016). Do the visual complexity algorithms match the generalization process in geographical displays? In: XXIII ISPRS Congress, Commission II, Prague, 12 July 2016 - 19 July 2016, 375-378.

Abstract

In this study, we first develop a hypothesis that existing quantitative visual complexity measures will overall reflect the level of cartographic generalization, and test this hypothesis. Specifically, to test our hypothesis, we first selected common geovisualization types (i.e., cartographic maps, hybrid maps, satellite images and shaded relief maps) and retrieved examples as provided by Google Maps, OpenStreetMap and SchweizMobil by swisstopo. Selected geovisualizations vary in cartographic design choices, scene contents and different levels of generalization. Following this, we applied one of Rosenholtz et al.’s (2007) visual clutter algorithms to obtain quantitative visual complexity scores for screenshots of the selected maps. We hypothesized that visual complexity should be constant across generalization levels, however, the algorithm suggested that the complexity of small-scale displays (less detailed) is higher than those of large-scale (high detail). We also observed vast differences in visual complexity among maps providers, which we attribute to their varying approaches towards the cartographic design and generalization process. Our efforts will contribute towards creating recommendations as to how the visual complexity algorithms could be optimized for cartographic products, and eventually be utilized as a part of the cartographic design process to assess the visual complexity.

Abstract

In this study, we first develop a hypothesis that existing quantitative visual complexity measures will overall reflect the level of cartographic generalization, and test this hypothesis. Specifically, to test our hypothesis, we first selected common geovisualization types (i.e., cartographic maps, hybrid maps, satellite images and shaded relief maps) and retrieved examples as provided by Google Maps, OpenStreetMap and SchweizMobil by swisstopo. Selected geovisualizations vary in cartographic design choices, scene contents and different levels of generalization. Following this, we applied one of Rosenholtz et al.’s (2007) visual clutter algorithms to obtain quantitative visual complexity scores for screenshots of the selected maps. We hypothesized that visual complexity should be constant across generalization levels, however, the algorithm suggested that the complexity of small-scale displays (less detailed) is higher than those of large-scale (high detail). We also observed vast differences in visual complexity among maps providers, which we attribute to their varying approaches towards the cartographic design and generalization process. Our efforts will contribute towards creating recommendations as to how the visual complexity algorithms could be optimized for cartographic products, and eventually be utilized as a part of the cartographic design process to assess the visual complexity.

Statistics

Altmetrics

Downloads

8 downloads since deposited on 02 Feb 2017
8 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), not refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Event End Date:19 July 2016
Deposited On:02 Feb 2017 10:30
Last Modified:11 Oct 2017 06:19
Publisher:ISPRS
Number:XLI-B2
Publisher DOI:https://doi.org/10.5194/isprs-archives-XLI-B2-375-2016, 2016
Official URL:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B2/375/2016/

Download

Download PDF  'Do the visual complexity algorithms match the generalization process in geographical displays?'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 436kB
View at publisher