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Blaser, Andreas D.

doi:10.1023/a:1015555919781

Cited by 19 publications

(5 citation statements)

References 27 publications

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“…They are usually incomplete [18][19][20], i.e., they only contain roads and road sections alongside the route, and landmarks at decision points [21]. Such sketch maps are a graphical representation of the task-oriented cognitive map of their creators [22].…”

Section: Introductionmentioning

confidence: 99%

Reduction of Map Information Regulates Visual Attention without Affecting Route Recognition Performance

Keil

Mocnik

Edler

et al. 2018

IJGI

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Map-based navigation is a diverse task that stands in contradiction to the goal of completeness of web mapping services. As each navigation task is different, it also requires and can dispense with different map information to support effective and efficient wayfinding. Task-oriented reduction of the elements displayed in a map may therefore support navigation. In order to investigate effects of map reduction on route recognition and visual attention towards specific map elements, we created maps in which areas offside an inserted route were displayed as transparent. In a route memory experiment, where participants had to memorize routes and match them to routes displayed in following stimuli, these maps were compared to unmodified maps. Eye movement analyses revealed that in the reduced maps, areas offside the route were fixated less often. Route recognition performance was not affected by the map reduction. Our results indicate that task-oriented map reduction may direct visual attention towards relevant map elements at no cost for route recognition.

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Section: Introductionmentioning

confidence: 99%

Reduction of Map Information Regulates Visual Attention without Affecting Route Recognition Performance

Keil

Mocnik

Edler

et al. 2018

IJGI

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“…This also implies that generalization operators are theoretical concepts independent of any particular data model, unlike generalization algorithms that are designed to work with specific input data format. We opted for a vector-based representation of data for our algorithm as it is best suited to represent the sketch map data that predominantly consists of linear and aerial objects [34].…”

Section: Existing Algorithms On Generalization Operatorsmentioning

confidence: 99%

An algorithmic approach to detect generalization in sketch maps from sketch map alignment

Manivannan,

Krukar,

Schwering

2024

PLoS ONE

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Sketch maps are valuable tools used across various disciplines including spatial cognition, environmental psychology, and spatial reasoning. A common approach to evaluate sketch maps in research is to align and compare them with metric maps. However, sketch maps are highly abstract and contain generalized information causing difficulty in their alignment. Current approaches to study sketch maps cannot handle generalized information. They require a one-on-one correspondence between features in the metric map and features in the sketch map. But memory is often generalized. This paper makes two contributions to the research on sketch maps: (i) we present an algorithmic approach to detect generalization in sketch maps (ii) we present an online tool that creates a generalized metric map corresponding to features in sketch maps. Previously, we identified nine types of generalization in sketch maps. In this paper, we develop formal operators to detect these generalizations and implement them as an online tool. We evaluated our algorithm with a set of 11 sketch maps containing 84 instances of generalization. The results indicated that our algorithm consistently detects instances of generalization in sketch maps.

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“…The purpose of analysing map drawings in addition to checking the accuracy of landmark locations which is a milestone in individuals' perception of the environment is to evaluate individuals' perception of the structure and shape of space by comparing trajectories drawn with the actual state to provide an overview of how individuals perceive the environment [21]. However, given that these maps are merely a simple and abstract representation of reality, the analysis and assessment of these maps is challenging [62]. Notwithstanding, based on these two important items, that is, landmarks and paths, mental maps can be analysed more accurately.…”

Section: The Significant Factors For Analyzing Mental Mapsmentioning

confidence: 99%

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

et al. 2019

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Considering citizens’ perceptions of their living environment is very helpful in making the right decisions for city planners who intend to build a sustainable society. Mental map analyses are widely used in understanding the level of perception of individuals regarding the surrounding environment. The present study introduces Aram Mental Map Analyzer (AMMA), an open-source program, which allows researchers to use special features and new analytical methods to receive outputs in numerical data and analytical maps with greater accuracy and speed. AMMA performance is contingent upon two principles of accuracy and complexity, the accuracy of the program is measured by Accuracy Placed Landmarks (APL) and General Orientation (GO), which respectively analyses the landmark placement accuracy and the main route mapping accuracy. Also, the complexity section is examined through two analyses Cell Percentage (CP) and General Structure (GS), which calculates the complexity of citizens’ perception of space based on the criteria derived from previous studies. AMMA examines all the dimensions and features of the graphic maps and its outputs have a wide range of valid and differentiated information, which is tailored to the research and information subject matter that is required.

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Untitled

Cited by 19 publications

References 27 publications

Reduction of Map Information Regulates Visual Attention without Affecting Route Recognition Performance

Reduction of Map Information Regulates Visual Attention without Affecting Route Recognition Performance

An algorithmic approach to detect generalization in sketch maps from sketch map alignment

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

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