Enriching Navigation Instructions to Support the Formation of Mental Maps

Sester, Monika; Dalyot, Sagi

doi:10.1007/978-3-319-19950-4_2

Cited by 6 publications

(6 citation statements)

References 17 publications

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“…Accordingly, methods are investigated to automatically extract geotagged photos that show tourism context for retrieving knowledge and insights about tourism activity. The increasing diversity of authoritative open-source data (e.g., governmental, municipal) and user-generated personal content (e.g., geotagged locations and photos shared on online social media) has generated an increasing interest in multiple recommendations and planning systems [27]. Accordingly, when handling these data and information, two challenges exist: (1) what can be considered as relevant and informative content-and from what sources, namely requiring the retrieval of the relevant information, such as places of interest (POI), and (2) how to weight and generate routes between the predefined locations and POIs (e.g., [24,28]).…”

Section: Related Researchmentioning

confidence: 99%

3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos

Mor

Fisher-Gewirtzman

Yosifof

et al. 2021

IJGI

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Social media is used nowadays for various location-based applications and services, aspiring to use the vast and timely potential of user-generated content. To evaluate the correctness, reliability and potential of these applications and services, they are mostly evaluated in terms of optimization or compared to existing authoritative data sources and services. With respect to route planning, criterion optimization is mostly implemented to evaluate the service effectiveness, in terms of, e.g., length, time or visited places. These evaluations are mostly limited in their effectiveness at presenting the complete experience of the route, since they are limited to a predefined criterion and are mostly implemented in two-dimensional space. In this research, we propose a comprehensive evaluation process, in which a tourism walking route is analyzed with respect to three-dimensional visibility that measures the attractiveness of the route relating to the user perception. To present our development, we showcase the use of Flickr, a social media photo-sharing online website that is popular among travelers that share their tourism experiences. We use Flickr photos to generate tourism walking routes and evaluate them in terms of the visible space. We show that the 3D visibility analysis identifies the various visible urban elements in the vicinity of the tourism routes, which are more attractive, scenery and include many tourism attractions. Since urban attractivity is often reflected in the photo-trails of Flickr photographers, we argue that using 3D visibility analysis that measures urban attractiveness and scenery should be considered for the purpose of analysis and evaluation of location-based services.

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Section: Related Researchmentioning

confidence: 99%

3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos

Mor

Fisher-Gewirtzman

Yosifof

et al. 2021

IJGI

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“…Geographic crowdsourcing and participatory mapping paradigms (GeoWeb 2.0) are commonly used for contributing and uploading geographic data by groups of people who have the potential to replace surveying experts and professional cartographers in their mapping tasks (e.g. Koukoletsos et al, 2012;Sester and Dalyot, 2015;Shangguan et al, 2014). In terms of data completeness and accuracy, research advocates the maturity of crowdsourced geographic sources (e.g.…”

Section: Open Source Geographic Datamentioning

confidence: 99%

Route planning for blind pedestrians using OpenStreetMap

Cohen

Dalyot

2020

Environment and Planning B: Urban Analytics and City Science

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While most of us take wayfinding and orientation for granted, instinctively utilizing our visual channels to do so, millions of blind people around the world face challenges and obstacles when attempting to perform the most basic tasks, such as walking to the corner store or using public transportation. As blind pedestrians lack critical information about the space they traverse outside the familiarity of their home, they are restricted, dependent on others, and have decreased quality of life. While assistive technologies for providing specific navigation solutions do exist, research is still limited regarding customized wayfinding solutions for blind pedestrians. This research aims at developing a wayfinding algorithm that relies on the OpenStreetMap mapping catalogue for planning accessible and safe routes specifically suited to blind pedestrians. In-depth investigations, observations, and interviews were conducted with blind people and with orientation and mobility instructors, in order to define and categorize spatial criteria relating to mobility, accessibility, and safety. Using controlled iterative experiments, weighted network graph criteria were defined, leading to the development of a route planning software that generates optimized routes for blind pedestrians. The developed software was then tested on a variety of routes, with the help of blind volunteers and orientation and mobility instructors. The results show that the optimal routes generated by the software were identical or very similar to those suggested by the experienced orientation and mobility instructors. Moreover, the blind volunteers also stated that the software planned routes were indeed more accessible and safer for them to walk along compared to routes suggested by existing commercial software developed for seeing pedestrians. The findings of this research indicate that our solution, based on OpenStreetMap and developed for the benefit of blind pedestrians, is effective and practical, and could improve the mobility, independence, and quality of life of this population, as well as increasing their integration into society.

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“…However, the increasing availability and popularity of User-Generated Content (UGC), e.g., geotagged locations and information shared on online social media, gradually turn it into a valuable alternative [24]. Data and information retrieved from UGC can serve as an enriched source for the retrieval of more informal information, such as vernacular places and local knowledge, which is heavily used by people in their daily lives, but not represented in authoritative digital maps [25]. Online UGC, such as the collection of geotagged photos on social media, e.g., Flickr, can be used to measure the popularity of locations and to infer users' preferences of landmarks for travel suggestions [26][27][28].…”

Section: Advantages Of User-generated Content For Landmark Miningmentioning

confidence: 99%

“…Wikipedia, the UGC largest encyclopedia, is an enormous body of expertise that contains vernacular and local knowledge and reflects public interests across numerous dimensions. This study proposes an innovative method to use Wikipedia's potential to enrich existing sources, as it offers cost-effective information of geospatial entities [24,25,33].…”

Section: Advantages Of User-generated Content For Landmark Miningmentioning

confidence: 99%

Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model

Binski

Natapov

Dalyot

2019

IJGI

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Landmarks are important for assisting in wayfinding and navigation and for enriching user experience. Although many user-generated geotagged sources exist, landmark entities are still mostly retrieved from authoritative geographic sources. Wikipedia, the world’s largest free encyclopedia, stores geotagged information on many geospatial entities, including a very large and well-founded volume of landmark information. However, not all Wikipedia geotagged landmark entities can be considered valuable and instructive. This research introduces an integrated ranking model for mining landmarks from Wikipedia predicated on estimating and weighting their salience. Other than location, the model is based on the entries’ category and attributed data. Preliminary ranking is formulated on the basis of three spatial descriptors associated with landmark salience, namely permanence, visibility, and uniqueness. This ranking is integrated with a score derived from a set of numerical attributes that are associated with public interest in the Wikipedia page―including the number of redirects and the date of the latest edit. The methodology is comparatively evaluated for various areas in different cities. Results show that the developed integrated ranking model is robust in identifying landmark salience, paving the way for incorporation of Wikipedia’s content into navigation systems.

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Enriching Navigation Instructions to Support the Formation of Mental Maps

Cited by 6 publications

References 17 publications

3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos

3D Visibility Analysis for Evaluating the Attractiveness of Tourism Routes Computed from Social Media Photos

Route planning for blind pedestrians using OpenStreetMap

Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model

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