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Quantifying the Significance of Semantic Landmarks in Familiar and Unfamiliar Environments
Abstract and Figures
During navigation, people tend to associate objects that have outstanding characteristics to useful landmarks. The landmarkness is usually divided into three categories of salience: the visual, the structural, and the semantic. Actually, the roles of visual and structural landmarks have been widely explored at the expense of the semantic salience. Thus, we investigated its significance compared to the two others through an exploratory experiment conducted on the Internet. Specifically, 63 participants were asked to select landmarks along 30 intersections located in Quebec City. Participants were split by gender and familiarity with the study area. Unsurprisingly, the results show that unlike strangers, locals tended to focus on highly semantic landmarks. In addition, we found that women were more influenced by the structural salience than men. Finally, our findings suggest that the side where travelers move compared to the road impacts on the landmark selection process.
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... The common perception is that highly visible objects are highly attracting people's attention (Lynch, 1960;Davis & Peebles, 2010;Dong et al., 2020). Nevertheless, some scholars point out the important role of meaning and knowledge about imageability (Tuan, 1979;Quesnot & Roche, 2015;Damayanti & Kossak, 2016). Henderson and Hayes (2017) found that the semantic salience of the landmarks dominates visual attention. ...
... Henderson and Hayes (2017) found that the semantic salience of the landmarks dominates visual attention. Quesnot and Roche (2015) verify that local people's memory holds semantically salient landmarks and strangers focus on visually salient landmarks. According to this discussion, a salient landmark means a most imageable landmark. ...
... Dong et al. (2020) present a quantitative method (computer vision model) to compare the roles of landmarks' visual salience and semantic salience. At the same time, Raubal and Winter (2002), Duckham et al. (2010) and Quesnot and Roche (2015) also compute landmarks salience by using models. In contrast, this research followed a qualitative research approach. ...
The concepts of imageability and legibility are important aspects of urban design. Many scholars use the terms “imageability” and “legibility” interchangeably, usually examining one concept and applying the implications to the other. This research explores the relationship between these two concepts by answering the research questions: 1. how do people perceive the saliency of landmarks (imageability) and 2. how does the spatial configuration facilitate the visibility level of landmarks (legibility)? The Galle Heritage City in Sri Lanka is considered as the case study. The first part of the empirical study is to assess the level of imageability of urban space users by completing 100 cognitive maps and producing a composite cognitive map that indicates the structural landmarks’ salience or the level of imageability. The second part is the level of legibility of the landmarks by employing the visibility assessment process and the third part compares the two results with a concurrence matrix. The findings highlight that there is a positive relationship between people’s perception (imageability) and level of visibility (legibility). Further, imageability mostly depends on semantic properties than legibility, but legibility predominantly depends on structural properties and visual properties are almost equally important to both concepts.
... Recently, he repeated the same experiment in other cities to study the robustness of the previous findings (Kattenbeck, Nuhn & Timpf, 2018). Furthermore, some studies also explored the influence of user characteristics on landmark selection, such as gender, age (Elias, Paelke & Chaouali, 2009), sense of direction (Ishikawa & Nakamura, 2012), and familiarity with the environment (Quesnot & Roche, 2015). Due to the difficulty in controlling various variables involved in the landmark selections in the real world, several empirical studies were also completed in virtual environments (Peters, Wu & Winter, 2010;Röser, Krumnack, Hamburger & Knauff, 2012) and the results were often consistent with the real-world experiments (Kattenbeck, 2015). ...
... Each participant in either group was asked to select suitable indoor landmarks for route-receivers of different familiarity with the building: peer (i.e., colleagues in the case of staff and classmates in the case of students), and visitors who had never been to the building before. The setting is similar to the previous studies (Li & Klippel, 2016;O'Neill, 1992;Peron, Baroni, Job & Salmaso, 1990;Quesnot & Roche, 2015), where the familiarity was differentiated between residents who live in the study area for a certain period and visitors who have never visited the study area before. ...
... Thus, the four dimensions of salience were not manipulated and differentiated among individual experience and perceptions. This part of design is derived from the previous work on exploring the predominance of salience dimensions in landmark selection in outdoor environments (Kattenbeck, 2015;Kattenbeck et al., 2018;Peters et al., 2010;Quesnot & Roche, 2015;Winter, 2003). ...
When conveying information about routes to follow in complex environments, human route-givers adapt to route-receivers’ familiarity with the environments in their choice of landmarks. Meanwhile, as route-givers themselves have experienced the environments within a social role, the landmarks they select may also differ significantly. This research investigated how these two factors influence landmark selection when communicating routes in indoor environments. Two groups of participants were recruited to conduct indoor landmark selection experiments for familiar and unfamiliar route-receivers in a multi-functional university building. The results show an interaction effect between these factors in indoor landmark selection. These findings lay an empirical ground for developing human-centered mobile navigation systems that can adapt to users’ social roles and their familiarity with the environment.
... The importance of features that are highly visible to people during navigation tasks has been recognized in the literature (Caduff & Timpf, 2008), and the high frequency of use of streets as a relatum in our data confirms this. Furthermore, work on landmark salience has verified the key role of buildings in wayfinding (Raubal & Winter, 2002), so these findings are consistent with the previous salience literature (Quesnot & Roche, 2015). Much of the salience work focused on the wayfinding task, which is different from the scenario for our experiments, but these results point to similarities in the kinds of objects that are salient for the different tasks. ...
... This difference goes beyond language and vocabulary differences, as the actual geographic features selected (not the terms used for them) were more numerous than in BP. It is not clear why this might be, and while there has been significant work on the salience of geographic features for wayfinding (e.g., Caduff & Timpf, 2008;Quesnot & Roche, 2015;Raubal & Winter, 2002), we are not aware of any cross-linguistic studies that address the issue. Vocabulary studies show that the most frequently used word class in English is nouns (Kang & Yu, 2011;Tardif, Gelman, & Xu, 1999), whereas in BP verbs are used most frequently (Estivalet & Meunier, 2015), which might make English speakers more attuned to objects in their environment, but more studies are required to determine the cause of this variation in relata and locata selection frequency. ...
Humans use spatial language on a daily basis, to describe locations, give directions, and ask for information about places. Better understanding of spatial language can assist in developing natural language interfaces and querying tools for GIS and web mapping. However, most previous studies focus on artificial, indoor situations. We conduct cross-linguistic experiments to compare natural language relative location descriptions (e.g., the house beside the river) in New Zealand English (NZE) and Brazilian Portuguese (BP) using eight real outdoor locations to discover the differences that occur when people describe the same location in the two languages. Our results show that NZE uses a wider range of spatial relation terms (e.g., beside) and reference objects (e.g., river) than BP, that BP uses more projective spatial relation terms than NZE, which prefers directional terms, and that translation between spatial relation terms is context-dependent.
... Landmark kognitif lebih sulit dikenali daripada landmark visual karena memiliki sifat yang lebih personal dan tergantung dengan familiaritas terhadap lingkungan (Yesiltepe et al, 2021). Karenanya, orang yang mengenal lingkungan akan lebih terfokus pada landmark kognitif walaupun tidak memiliki saliensi visual yang tinggi (Quesnot & Roche, 2015). ...
Penelitian ini meninjau aspek-aspek arsitektur tradisional yang menjadi landmark di kota-kota besar di Indonesia dan popularitasnya dibandingkan landmark yang sepenuhnya modern dengan memeriksa jenis, aspek, kategori, dan daya tarik landmark di ibukota provinsi di Indonesia. Analisis deskriptif dan one-way ANOVA digunakan untuk mengklasifikasikan landmark dan memeriksa secara kuantitatif relasi antara landmark dengan daya tariknya bagi masyarakat kota. Hasil mengungkapkan bahwa 39 dari 121 landmark yang disurvai memiliki aspek arsitektur tradisional. Arsitektur tradisional dapat dilihat dalam aspek atap, bangunan, dan ornamen. Kategori landmark yang mengandung aspek arsitektur tradisional adalah masjid, museum, taman, jalan, kompleks bangunan, kuil/wihara/kelenteng, pura, benteng, keraton, monumen, dan pasar. Hasil analisis ANOVA menunjukkan bahwa landmark yang mengandung aspek arsitektur dan menonjol secara visual memiliki daya tarik lebih tinggi dari landmark yang hanya mengandung salah satu karakteristik tersebut. Hasil ini meningkatkan pemahaman mengenai pentingnya aspek arsitektur tradisional untuk diterapkan dalam desain landmark dan menyarankan penambahan aspek-aspek arsitektur tradisional pada landmark yang telah ada maupun pada desain landmark yang akan datang
... Mental maps to support wayfinding (Downs & Stea, 1973;Golledge, 1999;Lynch, 1960;Meilinger, 2008;Siegel & White, 1975) (Hannes et al., 2012;Kuipers, 1978;McDermott & Davis, 1984) Computational models of mental maps (Duckham et al., 2010;Quesnot & Roche, 2015;Sadeghian & Kantardzic, 2008) Computational models of landmark salience ...
Spatial language incorporates descriptions of locations, routes, and landscapes, and is used by humans daily. Research has addressed a wide range of aspects of spatial language, including its form; the ways in which it is selected and applied; and cognitive, geometric, and functional factors affecting its use. Furthermore, much work has been done on the automation of spatial language extraction, analysis, interpretation, and generation. To introduce the Special Issue on this broad topic, this paper reviews spatial language research framed by an extension to the well-known semantic triangle, the “spatial semantic pyramid,” which represents both human spatial language and relevant computational research. By introducing it, we hope to stimulate discussion about gaps and future directions in this important research field.
... In the core of any navigation task or phase is the continuous interplay of extracting cues -landmarks, street names, company logos etc. -either from the environment or a map. The navigator's attention tends to focus on visually, structurally or semantically salient cues, depending on her familiarity of the area [51]. These cues are then matched with each other and with a mental model to infer and maintain location and orientation during navigation. ...
... Empirical evidence has been provided that the use of landmarks has a positive impact on wayfinding performance (see, e.g., Ross, May & Thompson, 2004;Tom & Denis, 2004) and that the absence of landmarks in an environment is compensated by an increased granularity in verbal humanto-human route instructions (see Hirtle, Richter, Srinivas & Firth, 2010). Research on incorporating landmarks (see Richter & Winter, 2014, for a thorough overview of the concept) in route instructions for wayfinding assistance systems has, consequently, become a predominant research topic, including modeling (see, e.g., Caduff & Timpf, 2008;Nothegger, Winter & Raubal, 2004;Nuhn & Timpf, 2017;Raubal & Winter, 2002;Winter, 2003), empirical assessment (see, e.g., Götze & Boye, 2016;Kattenbeck, 2017;Kattenbeck, Nuhn & Timpf, 2018;Quesnot & Roche, 2015) of salience and the automatic selection of landmarks (see, e.g., Duckham, Winter & Robinson, 2010;Lander, Herbig, Löchtefeld, Wiehr & Krüger, 2017;Lazem & Sheta, 2005;Rousell & Zipf, 2017;Wang & Ishikawa, 2018). ...
Despite the increased research interest in wayfinding assistance systems, research on the appropriate point in time or space to automatically present a route instruction remains a desideratum. We address this research gap by reporting on the results of an outdoor, within-subject design wayfinding study (N=52). Participants walked two different routes for which they requested spoken, landmark-based turn-by-turn route instructions. By means of a survival analysis, we model the points in space at which participants issue such requests, considering personal, environmental, route- and trial-related variables. We reveal different landcover classes (e.g., densely built-up areas) and personal variables (e.g., egocentric orientation and age) to be important, discuss potential reasons for their impact and derive open research questions.
Landmark‐based pedestrian navigation can assist pedestrians in navigating successfully. Previous studies have investigated the factors affecting the cognitive efficiency of landmark visualization in terms of both the visual salience of landmarks and the personal characteristics of users. However, empirical studies and applications that consider the influence of spatial familiarity on landmark representation are limited. In this article, we propose a personalized landmark adaptive visualization method for pedestrian navigation maps considering user familiarity. We first explore the influence of spatial familiarity on landmark salience and symbols using cognitive experiments. The results showed that unfamiliar people preferred strong visual salience landmarks and image‐based symbols, while familiar people preferred strong semantic salience landmarks and text‐based symbols. Based on these results, a mathematical model of landmark salience for selecting personalized landmarks is proposed, and association rules between landmark salience and symbols are mined. Finally, the framework of a landmark visualization method is proposed based on the rules. To verify the effectiveness of the proposed method, a prototype system is developed, and a comparative experiment is conducted with a Baidu map. Experimental results showed that the proposed method has direct practical implications for the development of pedestrian navigation systems, depending on different target users.
While the role of landmarks is well documented, little research has focused on the characteristics that allow landmarks to benefit the construction of spatial representations. Although their visual saliency has already been explored, cognitive saliency deserves attention. It could benefit to older people who experience decline in their spatial abilities. To explore this issue, young and older participants watched virtual itineraries including landmarks varying in their visual and cognitive saliency. They then performed various landmark and direction-related tasks. The combination of visual and cognitive saliency improved performance in both age groups, without canceling age-related differences but reducing them in some cases. Our results provide evidence that visually and cognitively salient landmarks facilitate the construction of mental representations of environments.
For human-centered mobile navigation systems, a computational landmark selection model is critical to automatically include landmarks for communicating routes with users. Although some empirical studies have shown that landmarks selected by familiar and unfamiliar wayfinders, respectively, differ significantly, existing computational models are solely focused on unfamiliar users and ignore selecting landmarks for familiar users, particularly in indoor environments. Meanwhile, it is unclear how the importance of salience metrics employed by machine learning approaches differs from that reported by human participants during landmark selection. In this study, we propose a LambdaMART-based ranking approach to computationally modelling indoor landmark selection. Two models, one for familiar and one for unfamiliar users, respectively, were trained from the human-labelled indoor landmark selection data. The importance of different salience measures in each model was then ranked and compared with human participants’ self-report results of a survey. The evaluation results demonstrate that familiarity does indeed matter in the computational modelling of indoor landmark selection. The ranking differences of salience measures in the trained models show that the salience varies with the familiarity of wayfinders. Moreover, the calculated intraclass correlation coefficients (0.62 for familiar, 0.65 for unfamiliar) illustrate the median consistency between the computational results on feature importance and the self-reported importance results by human participants, confirming the reliability and interpretability of the proposed approach.
Sharing "location" information on social media became commonplace since the advent of smartphones. Location-based social networks introduced a derivative form of Volunteered Geographic Information (VGI) known as Social Location Sharing (SLS). It consists of claiming "I am/was at that Place". Since SLS represents a singular form of place-based (i.e. platial) communication, we argue that SLS data are more platial than locational. According to our data classification of VGI, locational data (e.g. a geotagged tweet which geographic dimension is limited to its coordinate information) are a reduced form of platial data (e.g. a Swarm check-in). Therefore, we believe these two kinds of data should not be analyzed on the same spatial level. This distinction needs to be clarified because a large part of geosocial data (i.e. spatial data published from social media) tends to be analyzed on the basis of a locational equivalence and not on a platial one.
Research in the area of spatial cognition demonstrated that references to landmarks are essential in the communication and the interpretation of wayfinding instructions for human being. In order to detect landmarks, a model for the assessment of their salience has been previously developed by Raubal and Winter. According to their model, landmark salience is divided into three categories: visual, structural, and semantic. Several solutions have been proposed to automatically detect landmarks on the basis of these categories. Due to a lack of relevant data, semantic salience has been frequently reduced to objects’ historical and cultural significance. Social dimension (i.e., the way an object is practiced and recognized by a person or a group of people) is systematically excluded from the measure of landmark semantic salience even though it represents an important component. Since the advent of mobile Internet and smartphones, the production of geolocated content from social web platforms—also described as geosocial data—became commonplace. Actually, these data allow us to have a better understanding of the local geographic knowledge. Therefore, we argue that geosocial data, especially Social Location Sharing datasets, represent a reliable source of information to precisely measure landmark semantic salience in urban area.
User-generated content currently revolutionizes data collection and maintenance. The advent of powerful mobile devices, Web 2.0 technology, and ubiquitous network connectivity enables and encourages users of a service to contribute their data to improve the utility of that service. This paper reports preliminary work on integrating landmarks in OpenStreetMap, illustrating the power of user-generated content for gaining semantic information. Landmarks are crucial in human wayfinding, but desperately lacking in navigation systems. Today's approaches to landmark integration require large amounts of geometric, attribute, and semantic data, rendering it impossible to include them in commercial systems due to the immense data collection costs. Distributing this task to users relieves these issues, but requires intelligent methods to avoid cumbersome interfaces that hinder collection of data or its future use.
Wayfinding is the process of finding your way to a destination in a familiar or unfamiliar setting using any cues given by the environment. Due to its ubiquity in everyday life, wayfinding appears on the surface to be a simply characterized and understood process; however, this very ubiquity and the resulting need to refine and optimize wayfinding has led to a great number of studies that have revealed that it is in fact a deeply complex exercise. In this article, we examine the motivations for investigating wayfinding, with particular attention being paid to the unique challenges faced in transportation hubs, and discuss the associated principles and factors involved as they have been perceived from different research perspectives. We also review the approaches used to date in the modelling of wayfinding in various contexts. We attempt to draw together the different perspectives applied to wayfinding and postulate the importance of wayfinding and the need to understand this seemingly simple, but concurrently complex, process.
Abstract In this paper, we propose a conceptual framework for assessing the salience of landmarks for navigation. Landmark salience is derived as a result of the observer’s point of view, both physical and cognitive, the surrounding environment, and the objects contained therein. This is in contrast to the currently held view that salience is an inherent property of some spatial feature. Salience, in our approach, is expressed as a three-valued Saliency Vector. The components that determine this vector are Perceptual Salience, which defines the exogenous (or passive) potential of an object or region for acquisition of visual attention, Cognitive Salience, which is an endogenous (or active) mode of orienting attention, triggered by informative cues providing advance information about the target location, and Contextual Salience, which is tightly coupled to modality and task to be performed. This separation between voluntary and involuntary direction of visual attention in dependence of the context allows defining a framework that accounts for the interaction between observer, environment, and landmark. We identify the low-level factors that contribute to each type of salience and suggest a probabilistic approach for their integration. Finally, we discuss the implications, consider restrictions, and explore the scope of the framework.
Until today there exist few theoretical assumptions about the concept of landmark salience. They could be divided into two fields: a more physical view (inherent aspects of the landmarks) and a more cognitive/personal view (the validation of the specific landmark from the individual cognitive features). We here combine these two aspects and present first empirical evidence for the interdependence of visibility and structural salience.
This concluding chapter reflects on some of the core themes that crosscut the contributed chapters, and further outlines some of the stimulating and significant relationships between volunteered geographic information (VGI) and the discipline of geography. We argue that future progress in VGI research depends in large part on building strong linkages with a diversity of geographic scholarship. We situate VGI research in geography's core concerns with space and place and offer several ways of addressing persistent challenges of quality assurance in VGI. We develop an argument for further research on the heterogeneous social relations through which VGI is produced and their implications for participation, power, and collective or civic action. The final two sections, closely related, position VGI as part of a shift toward hybrid epistemologies and potentially a fourth paradigm of data-intensive inquiry across the sciences. © 2013 Springer Science+Business Media Dordrecht. All rights reserved.
What characteristics constitute a "helpful" landmark for wayfinding and how are they represented in the human brain? Experiment 1 compared recognition and wayfinding performance for visual, verbal, and acoustic landmarks (animals) learned in our virtual environment SQUARELAND. Experiment 2 investigated landmark semantics, namely, famous versus unfamiliar buildings. The results showed that, first, the best recognition performance was observed for words (verbal condition) followed by sounds. Performance was worst for the pictorial landmark information. In the wayfinding phase, a similar level of performance was observed for all three modalities. Second, famous buildings were better recognized than unfamiliar ones, indicating a semantic influence. We conclude that nonvisual information may successfully constitute a landmark and discuss this within the context of current research on landmarks and human wayfinding.