Content uploaded by Sara Irina Fabrikant
Author content
All content in this area was uploaded by Sara Irina Fabrikant on Jan 24, 2016
Content may be subject to copyright.
A preview of the PDF is not available
Evaluating the Effectiveness and Efficiency of Visual Variables for Geographic Information Visualization
Abstract and Figures
We propose an empirical, perception-based evaluation approach for assessing the effectiveness and efficiency of longstanding
cartographic design principles applied to 2D map displays. The approach includes bottom-up visual saliency models that are
compared with eye-movement data collected in human-subject experiments on map stimuli embedded in the so-called flicker paradigm.
The proposed methods are applied to the assessment of four commonly used visual variables for designing 2D maps: size, color
value, color hue, and orientation. The empirical results suggest that the visual variable size is the most efficient (fastest)
and most effective (accurate) visual variable to detect change under flicker conditions. The visual variable orientation proved
to be the least efficient and effective of the tested visual variables. These empirical results shed new light on the implied
ranking of the visual variables that have been proposed over 40 years ago. With the presented approach we hope to provide
cartographers, GIScientists and visualization designers a systematic assessment method to develop effective and efficient
geovisualization displays.
Content may be subject to copyright.
... (Williams 1966). Garlandini conducted a controlled experiment to investigate the perceptual salience of four visual variables in 2D static maps under a flicker condition, and the results showed that the size and color value could guide a participant's visual attention better than color hue and orientation (Garlandini and Fabrikant 2009). Wolfe's summary survey of visual variable guidance led to similar conclusions: color and size provide high levels of guidance, while shape is weaker in the context of 2D visualization (Wolfe and Horowitz 2004). ...
... This is different from 2D and 3D visualization, where color can provide the highest guidance (Wolfe and Horowitz 2004) because color perception in AR visualization is readily disturbed by the external environment (Livingston et al. 2013). Size can also provide high guidance in 2D visualization (Garlandini and Fabrikant 2009), but its guidance is limited in 3D (Liu, Dong, and Meng 2017). However, our research has found that traditional size, or LS in this paper, can no longer provide effective guidance in AR geovisualization, while AS still provides guidance, and its guidance is higher than that of NMC. ...
The visual perception of augmented reality (AR) geovisualization is significantly different from traditional controllable 2D and 3D visualization. In this study, we extended the rendering styles of color variables to include natural material color (NMC) and illuminating material color (IMC) and extended the size to include linear size (LS) and angular size (AS). Outdoor AR geovisualization user experiments were conducted, examining the guidance characteristics of five static variables (NMC, IMC, shape, AS, LS) and two dynamic variables (vibration, flicker). The results showed that the two dynamic variables provided the highest guidance, and among all the static variables, the order of guidance was shape, IMC, AS, NMC, and finally LS. This is a new finding that is different from the color, size, and shape guidance order in 2D visualization and the color, shape, and size order in 3D visualization. The results could be utilized to guide the selection of visual variables for symbol design in AR geovisualization.
... Animated maps offer a multitude of visual and dynamic variables that contribute to their effectiveness in conveying spatial information. Visual variables, such as color, size, shape, and texture, allow for the representation of different geospatial attributes and their variations over time [11,12]. These variables provide a means to encode and differentiate multiple layers of information simultaneously, aiding in the comprehension and interpretation of complex spatial patterns [13]. ...
The primary objective of this study is to assess how the motion of dynamic point symbols impacts preattentive processing on a map. Specifically, it involves identifying the motion velocity parameters for cartographic animated pictorial symbols that contribute to the preattentive perception of the target symbols. We created five pictorial symbols, each accompanied by a unique animation tailored to convey the meaning associated with each symbol. The animation dynamics of symbols on the administrative map were distributed across arithmetic, logarithmic, and exponential scales. Eye-tracking technology was utilized to explain the user’s visual attention. The key findings reveal that, although movement does not uniformly hold the same designation in cartographic communication, it could guide user attention to identify the value peaks in quantitative map visualization. Motion velocity enhances the salience of animated symbols, making them stand out, not only against static elements but also against other animated distractors. Additionally, motion distributions between symbol classes based on exponential or arithmetic scales were identified as the most successful. Nevertheless, certain types of motion, such as rotational, do not perform well with pictorial symbols, even on the most effective motion distribution scale.
... Additionally, we considered time that each participant needed to provide the answer. This could be related to the effectiveness and efficiency measures (Çöltekin et al. 2009;Garlandini and Fabrikant 2009). The eye-tracking analysis was focused on fixation-based metrics and area of interest (AOI), especially, fixation location on the map display, fixation duration, total number of fixations, AOI viewed time, and AOI revisits. ...
This study investigated the impact of graphical user interface (GUI) design on the efficiency and effectiveness of map-based tasks on mobile devices, using time-based weather data as a case study. Three different GUI designs (button-type, circle-type, and slidebar) were tested in a between-subjects design, with 50 participants completing a set of map-based tasks on each GUI design. The results showed that GUI design significantly affected the effectiveness of map-based tasks. Participants performed better at tasks involving the search for the highest and lowest temperature amplitudes on the button-type GUI whereas the circle-type GUI showed lower effectiveness for tasks involving the search for day temperatures. Analysis of the visual attention distribution based on fixation count revealed that different GUI designs led to different patterns of visual attention. The study highlights the importance of considering GUI design in the development of mobile map applications, particularly for map-based tasks involving time-based data. The study shows that separating the date from the time navigation panel reduces necessary visual focus on the GUI itself and is a valuable insight for future GUI design.
... Some experiments have highlighted how Bertin's visual variables (Bertin, 1967) can be used to differentiate map content, thus facilitating the recognition of a particular form over another (e.g. (Garlandini & Fabrikant, 2009)). But the geographical complexity inherent in a map, coupled with the varying cognitive styles of map users and the multi-scaled nature of those interactions has led some to question the veracity of such experiments (Petchenik, 1983). ...
In the present study, a cartographic experiment is designed and conducted to evaluate the effectiveness and efficiency of five alternative methods of presenting elevation information. The evaluation of the methods is based on the examination of the responses of the experimental participants during the performance of two typical map reading tasks. The recording of participants' responses is complemented by the implementation of remote (web-based) mouse tracking and analysis techniques. The analysis of the results is based on the calculation of statistical indices related to the participants' correct performance of the tasks and their response times. Statistical heatmaps are generated in order to describe the (overall) cumulative response behavior. The results indicate that contour methods lead to less efficient searches compared to these of elevation zones, hill shading and perspective (3D) terrain visualization.
The present study aims to model the visual perception of cartographic backgrounds utilized in popular web services. More specifically, in the framework of this study, a cartographic experiment based on the application of eye movement recording and analysis techniques is designed and implemented. The main objective of this experiment is related to the computation of characteristic values of typical metrics derived by the two fundamental types of eye movements (fixations and saccades). In addition, the collected experimental data are used in order to produce cumulative (grayscale) statistical heatmaps towards describing the overall observing behavior. Totally, 30 individuals participated in the cartographic experiment who asked to observe, under free viewing conditions (no specific task required), 75 visual scenes consisted of cartographic backgrounds derived from five different web services (Google Maps, Wikimedia, Bing maps, ESRI, & OpenStreetMap). The experimental visual scenes consist of cartographic backgrounds that correspond to three different zoom levels while five different cities in Greece are selected for each one of the examined zoom levels. The identification of typical indices that describe the visual perception of cartographic backgrounds, as well as the analyses of overall viewing behaviors, allow the performance of comparisons while, at the same time, they could indicate important elements related to the complexity of map reading process.
The presented study aims to examine the process of preattentive processing of dynamic point symbols used in cartographic symbology. More specifically, we explore different motion types of geometric symbols on a map together with various motion velocity distribution scales. The main hypothesis is that, in specific cases, motion velocity of dynamic point symbols is the feature that could be perceived preattentively on a map. In a controlled laboratory experiment, with 103 participants and eye tracking methods, we used administrative border maps with animated symbols. Participants' task was to find and precisely identify the fastest changing symbol. It turned out that not every type of motion could be perceived preattentively even though the motion distribution scale did not change. The same applied to symbols' shape. Eye movement analysis revealed that successful detection was closely related to the fixation on the target after initial preattentive vision. This confirms a significant role of the motion velocity distribution and the usage of symbols' shape in cartographic design of animated maps.
Large changes that occur in clear view of an observer can become difficult to notice if made during an eye movement, blink, or other such disturbance. This change blindness is consistent with the proposal that focused visual attention is necessary to see change, with a change becoming difficult to notice whenever conditions prevent attention from being automatically drawn to it. The phenomenon of change blindness can provide new results on the nature of visual attention, including estimates of its capacity, and the extent to which it can bind visual properties into coherent descriptions. It is also shown how the resultant characterization of attention can provide new insights into the role that it plays in the perception of scenes and events.
This section considers the application of eye movements to user interfaces—both for analyzing
interfaces, measuring usability, and gaining insight into human performance—and as an actual control
medium within a human-computer dialogue. The two areas have generally been reported separately; but
this book seeks to tie them together. For usability analysis, the user’s eye movements while using the
system are recorded and later analyzed retrospectively, but the eye movements do not affect the interface in
real time. As a direct control medium, the eye movements are obtained and used in real time as an input to
the user-computer dialogue. They might be the sole input, typically for disabled users or hands-busy
applications, or they might be used as one of several inputs, combining with mouse, keyboard, sensors, or
other devices.
Interestingly, the principal challenges for both retrospective and real time eye tracking in humancomputer
interaction (HCI) turn out to be analogous. For retrospective analysis, the problem is to find
appropriate ways to use and interpret the data; it is not nearly as straightforward as it is with more typical
task performance, speed, or error data. For real time use, the problem is to find appropriate ways to respond
judiciously to eye movement input, and avoid over-responding; it is not nearly as straightforward as
responding to well-defined, intentional mouse or keyboard input. We will see in this chapter how these two
problems are closely related.
These uses of eye tracking in HCI have been highly promising for many years, but progress in
making good use of eye movements in HCI has been slow to date. We see promising research work, but we
have not yet seen wide use of these approaches in practice or in the marketplace. We will describe the
promises of this technology, its limitations, and the obstacles that must still be overcome. Work presented
in this book and elsewhere shows that the field is indeed beginning to flourish.
We propose a research agenda for empirically assessing the effectiveness of dynamic displays with the eye-movement data collection method. The proposed framework is based on the relationship between perceptual salience and thematic relevance in static (e.g., visual variables: color hue, color value and orientation) and animated displays (e.g., dynamicvariables including transitions). The proposed empirical studies adhere to experimental design standards in cognitivepsychology, but are additionally grounded on a solid dynamic design framework borrowed from cartography, computer graphics and cinematography, to investigate how different dynamic and visual variables, and various levels of interactivity affect people’s knowledge construction processes from dynamic displays as compared to static displays.
This paper discusses visual search theories that explain how humans search for objects on maps. A map-reading experiment considered variations in visual search processes related to searching for targets with unique features and targets that share features with other objects. Experimental objects differing in colour, shape, size, and orientation were constructed. The importance of these characteristics was evaluated, as was the effect of the location of the target on the map. The time needed to find a target in a display and the proportion of incorrect decisions were measures of efficiency in spatial-search studies. The most efficient spatial searches occur when targets 'pop out' of the map. These searches use parallel processes and are indicated by reaction times being independent of the number of symbols on the map. Pop-out' effects occur when targets have some unique characteristics that distinguish them from other symbols. Results indicated that 'pop-out' effects could be produced by colour differences between targets and distractor symbols, or by differences that combined colour with other dimensions. The location of the target on the map also had a significant effect on reaction time. This could be partially explained by the size of the map relative to people's fields of vision.
The work that Bertin has published during the last fifteen years is examined and his theories studied in relation to the main issues concerning contemporary research in thematic cartography. It is demonstrated that Bertin's particular views run counter to current theory postulated by N American cartographic schools and deny some of their research priorities. -from Author