Special Issue "Volunteered Geographic Information: Emerging Applications in Public Science and Citizen Participation"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (15 March 2019)

Special Issue Editors

Guest Editor
Assist. Prof. Dr. Sagi Daylot

Mapping and Geoinformation, The Technion - Israel Institute of Technology
Website | E-Mail
Interests: user-generated content; crowdsourcing; citizen science; location-based services; spatial analysis and modeling; spatial cognition
Guest Editor
Dott. Geom. Enrico Rispoli

Consiglio Nazionale Geometri e Geometri Laureati (CNGeGL); FIG Commission 3 Spatial Information Management
Website | E-Mail
Interests: land management; geodetic spatial information; spatial analysis; planning and modelling; sustainable development

Special Issue Information

Dear Colleagues,

Recent technological advances in the context of GeoWeb 2.0 and mobile sensors have generated an increased participation by citizens and communities in environmental application and planning processes. More specifically, participatory mapping has generated various research in the area of citizen-centric land and environmentally-related planning, design, and management, making use of social technologies and services. Massive volumes of geographic datasets, which are produced and maintained by the public, are freely available and have the potential to complement, update or even replace data obtained from traditional sources, such as mapping agencies and companies. The availability of geographic data collection opportunities and the dissemination of online large repositories effectively necessitates new scientific data handling for mining, interpreting and analyzing, and for integrating citizens’ opinions into the various processes. This particularly calls for interdisciplinary approaches between land surveyors, data scientists, environmental and urban planners, geoinformatics professionals, and others.

The primary objective of this Special Issue is to promote a deeper understanding of land and environmentally-related perspectives related to user-generated geographic data to improve citizen-centric planning and development. We call researchers from around the world that are involved in the collection, processing, analysis and general use of geographic user-generated content to contribute their research and best-practice. The Special Issue will address a wide number of application and development areas, such as land administration and management (cadastre), urban and environmental planning, sustainable development, data integration, data standardization, data quality and analysis processes and use of OpenStreetMap (OSM).

Assist. Prof. Dr. Sagi Daylot
Dott. Geom. Enrico Rispoli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Geographic User-Generated Content
  • Crowdsourcing
  • Citizen Science
  • Land Surveying
  • Urban Planning and Design

Published Papers (8 papers)

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Open AccessArticle Capturing Flood Risk Perception via Sketch Maps
ISPRS Int. J. Geo-Inf. 2018, 7(9), 359; https://doi.org/10.3390/ijgi7090359
Received: 12 June 2018 / Revised: 3 August 2018 / Accepted: 20 August 2018 / Published: 30 August 2018
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Abstract
The fact that an increasing number of people and local authorities are affected by natural hazards, especially floods, highlights the necessity of adequate mitigation and preparedness within disaster management. Many governments, though, have only insufficient monetary or technological capacities. One possible approach to [...] Read more.
The fact that an increasing number of people and local authorities are affected by natural hazards, especially floods, highlights the necessity of adequate mitigation and preparedness within disaster management. Many governments, though, have only insufficient monetary or technological capacities. One possible approach to tackle these issues is the acquisition of information by sketch maps complemented by questionnaires, which allows to digitally capture flood risk perception. We investigate which factors influence information collected by sketch maps and questionnaires in case studies in an area prone to pluvial flooding in Santiago de Chile. Our aim is to gain more information about the methods applied. Hereby, we focus on the spatial acquisition scale of sketch maps and personal characteristics of the participants, for example, whether they live at this very location of the survey (residents) or are pedestrians passing by. Our results show that the choice of the acquisition scale of the base map influences the amount and level of detail of information captured via sketch maps. Thus, detail base maps lead to more precise results when compared to reference data, especially in the case of residents. The results also reveal that the place of living of the respondents has an effect on the resulting information because on the neighborhood level the risk perception of residents is more detailed than the one of pedestrians. The study suggests that the integration of citizens via sketch maps can provide information about flood risk perception, and thus can influence the flood mitigation in the area. Full article
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Open AccessArticle Relevance Assessment of Crowdsourced Data (CSD) Using Semantics and Geographic Information Retrieval (GIR) Techniques
ISPRS Int. J. Geo-Inf. 2018, 7(7), 256; https://doi.org/10.3390/ijgi7070256
Received: 26 April 2018 / Revised: 25 June 2018 / Accepted: 26 June 2018 / Published: 29 June 2018
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Abstract
Crowdsourced data (CSD) generated by citizens is becoming more popular as its potential utilization in many applications increases due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals [...] Read more.
Crowdsourced data (CSD) generated by citizens is becoming more popular as its potential utilization in many applications increases due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the data is not generated by professionals nor follows standard data-collection procedures. The quality of CSD can be assessed according to a range of characteristics including its relevance. In this paper, information relevance has been explored through using geographic information retrieval (GIR) techniques to identify the most highly relevant information from a set of crowdsourced data. This research tested a relevance assessment approach for CSD by adapting relevance assessment techniques available in the GIR domain. Thematic and geographic relevance were assessed by analyzing the frequency of selected terms which appeared in CSD reports using natural language processing techniques. The study analyzed crowdsourced reports from the 2011 Australian flood’s Crowdmap to examine a proof of concept on relevance assessment using a subset of this dataset based on a defined set of queries. The results determined that the thematic and geographic specificities of the queries were 0.44 and 0.67, respectively, which indicated the queries used were more geographically specific than thematically specific. The Spearman’s rho value of 0.62 indicated that the final ranked relevance lists showed reasonable agreement with a manually classified list and confirmed the potential of the approach for CSD relevance assessment. In particular, this research has contributed to the field of CSD relevance assessment through an integrated thematic and geographic relevance ranking process by using a user-query specificity approach to improve the final ranking. Full article
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Open AccessArticle Mapping Rural Road Networks from Global Positioning System (GPS) Trajectories of Motorcycle Taxis in Sigomre Area, Siaya County, Kenya
ISPRS Int. J. Geo-Inf. 2018, 7(8), 309; https://doi.org/10.3390/ijgi7080309
Received: 25 June 2018 / Revised: 17 July 2018 / Accepted: 30 July 2018 / Published: 1 August 2018
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Abstract
Effective transport infrastructure is an essential component of economic integration, accessibility to vital social services and a means of mitigation in times of emergency. Rural areas in Africa are largely characterized by poor transport infrastructure. This poor state of rural road networks contributes [...] Read more.
Effective transport infrastructure is an essential component of economic integration, accessibility to vital social services and a means of mitigation in times of emergency. Rural areas in Africa are largely characterized by poor transport infrastructure. This poor state of rural road networks contributes to the vulnerability of communities in developing countries by hampering access to vital social services and opportunities. In addition, maps of road networks are incomplete, and not up-to-date. Lack of accurate maps of village-level road networks hinders determination of access to social services and timely response to emergencies in remote locations. In some countries in sub-Saharan Africa, communities in rural areas and some in urban areas have devised an alternative mode of public transport system that is reliant on motorcycle taxis. This new mode of transport has improved local mobility and has created a vibrant economy that depends on the motorcycle taxi business. The taxi system also offers an opportunity for understanding local-level mobility and the characterization of the underlying transport infrastructure. By capturing the spatial and temporal characteristics of the taxis, we could design detailed maps of rural infrastructure and reveal the human mobility patterns that are associated with the motorcycle taxi system. In this study, we tracked motorcycle taxis in a rural area in Kenya by tagging volunteer riders with Global Positioning System (GPS) data loggers. A semi-automatic method was applied on the resulting trajectories to map rural-level road networks. The results showed that GPS trajectories from motorcycle taxis could potentially improve the maps of rural roads and augment other mapping initiatives like OpenStreetMap. Full article
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Open AccessArticle Analyzing Spatial and Temporal User Behavior in Participatory Sensing
ISPRS Int. J. Geo-Inf. 2018, 7(9), 344; https://doi.org/10.3390/ijgi7090344
Received: 30 June 2018 / Revised: 12 August 2018 / Accepted: 21 August 2018 / Published: 23 August 2018
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Abstract
The large number of mobile devices and their increasingly powerful computing and sensing capabilities have enabled the participatory sensing concept. Participatory sensing applications are now able to effectively collect a variety of information types with high accuracy. Success, nevertheless, depends largely on the [...] Read more.
The large number of mobile devices and their increasingly powerful computing and sensing capabilities have enabled the participatory sensing concept. Participatory sensing applications are now able to effectively collect a variety of information types with high accuracy. Success, nevertheless, depends largely on the active participation of the users. In this article, we seek to understand spatial and temporal user behaviors in participatory sensing. To do so, we conduct a large-scale deployment of Citizense, a multi-purpose participatory sensing framework, in which 359 participants of demographically different backgrounds were simultaneously exposed to 44 participatory sensing campaigns of various types and contents. This deployment has successfully gathered various types of urban information and at the same time portrayed the participants’ different spatial, temporal and behavioral patterns. From this deployment, we can conclude that (i) the Citizense framework can effectively help participants to design data collecting processes and collect the required data, (ii) data collectors primarily contribute in their free time during the working week; much fewer submissions are done during the weekend, (iii) the decision to respond and complete a particular participatory sensing campaign seems to be correlated to the campaign’s geographical context and/or the recency of the data collectors’ activities, and (iv) data collectors can be divided into two groups according to their behaviors: a smaller group of active data collectors who frequently perform participatory sensing activities and a larger group of regular data collectors who exhibit more intermittent behaviors. These identified user behaviors open avenues to improve the design and operation of future participatory sensing applications. Full article
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Open AccessArticle Trends in Citizen-Generated and Collaborative Urban Infrastructure Feedback Data: Toward Citizen-Oriented Infrastructure Management in Japan
ISPRS Int. J. Geo-Inf. 2019, 8(3), 115; https://doi.org/10.3390/ijgi8030115
Received: 31 December 2018 / Revised: 14 February 2019 / Accepted: 23 February 2019 / Published: 28 February 2019
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Abstract
Infrastructure management has become a serious problem in many cities. However, the monitoring of daily urban infrastructure requires active feedback, not only by municipal government officers, but also by citizens. In this study, we analyzed Chiba City’s ‘Chiba-repo’ platform to measure citizen feedback [...] Read more.
Infrastructure management has become a serious problem in many cities. However, the monitoring of daily urban infrastructure requires active feedback, not only by municipal government officers, but also by citizens. In this study, we analyzed Chiba City’s ‘Chiba-repo’ platform to measure citizen feedback and collaboration in urban infrastructure maintenance. We compiled data on over 40,000 citizen-generated reports of infrastructure issues during the period from September 2014 to December 2016 through the Chiba-repo platform and analyzed the geographical distribution and text mining by categorizing the reports. The most frequent report was about road issues, representing 93.8% of the total. As a result, many reports were received from citizens from a time-consuming report like light repairs (average 24.4 days); also, road issues were revealed to be a major town problem. On the other hand, the unsolved issue rate is lower (3.7%) compared with telephone correspondence and counter contact, since posting through the web application allows for a detailed report that includes position information and photographs. The research also predicted that many infrastructure problems would occur on narrow roads and in areas with many elderly people, and that road issue reports are regularly needed in areas that cannot be found or patrolled by administrative staff. Full article
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Open AccessArticle The Geography of Taste: Using Yelp to Study Urban Culture
ISPRS Int. J. Geo-Inf. 2018, 7(9), 376; https://doi.org/10.3390/ijgi7090376
Received: 24 June 2018 / Revised: 25 August 2018 / Accepted: 29 August 2018 / Published: 13 September 2018
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Abstract
This study aims to put forth a new method to study the sociospatial boundaries by using georeferenced community-authored reviews for restaurants. In this study, we show that food choice, drink choice, and restaurant ambience can be good indicators of socioeconomic status of the [...] Read more.
This study aims to put forth a new method to study the sociospatial boundaries by using georeferenced community-authored reviews for restaurants. In this study, we show that food choice, drink choice, and restaurant ambience can be good indicators of socioeconomic status of the ambient population in different neighborhoods. To this end, we use Yelp user reviews to distinguish different neighborhoods in terms of their food purchases and identify resultant boundaries in 10 North American metropolitan areas. This dataset includes restaurant reviews as well as a limited number of user check-ins and rating in those cities. We use Natural Language Processing (NLP) techniques to select a set of potential features pertaining to food, drink and ambience from Yelp user comments for each geolocated restaurant. We then select those features which determine one’s choice of restaurant and the rating that he/she provides for that restaurant. After identifying these features, we identify neighborhoods where similar taste is practiced. We show that neighborhoods identified through our method show statistically significant differences based on demographic factors such as income, racial composition, and education. We suggest that this method helps urban planners to understand the social dynamics of contemporary cities in absence of information on service-oriented cultural characteristics of urban communities. Full article
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Open AccessArticle Collecting Typhoon Disaster Information from Twitter Based on Query Expansion
ISPRS Int. J. Geo-Inf. 2018, 7(4), 139; https://doi.org/10.3390/ijgi7040139
Received: 2 February 2018 / Revised: 27 March 2018 / Accepted: 29 March 2018 / Published: 2 April 2018
Cited by 1 | PDF Full-text (2286 KB) | HTML Full-text | XML Full-text
Abstract
Social media is a popular source of volunteered geographic information owing to its massive real-time data; however, the use of social media data in the context of geospatial analysis is challenging because complex semantic filters are required for the aggregation of geographic messages [...] Read more.
Social media is a popular source of volunteered geographic information owing to its massive real-time data; however, the use of social media data in the context of geospatial analysis is challenging because complex semantic filters are required for the aggregation of geographic messages from the data streams. This article proposes a new query expansion method for social media streams which updates the query keywords periodically by the words extracted from the preceding search results. The proposed method has optimized the trade-off between precision and coverage of geographical messages by factoring in the influences of the keyword number and refresh cycle in the query process, and some improvements on the classic Term Frequency-Inverse Document Frequency (TF-IDF) method for short texts were achieved. Furthermore, a number of filters based upon relevance to the target topic were established and tested. This method was tested on a dataset from Twitter within the geographic extent of Macau in August 2017 during two consecutive typhoon hits. The result supports its effectiveness with a controllable precision and considerable increment of relevant information. Moreover, the query keywords can adjust themselves to the local language environment by discovering new keywords. To conclude, this query expansion method is able to provide a reliable method for social media-based information retrieval. Full article
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Open AccessArticle Integrated Participatory and Collaborative Risk Mapping for Enhancing Disaster Resilience
ISPRS Int. J. Geo-Inf. 2018, 7(2), 68; https://doi.org/10.3390/ijgi7020068
Received: 29 November 2017 / Revised: 22 January 2018 / Accepted: 17 February 2018 / Published: 21 February 2018
Cited by 4 | PDF Full-text (34118 KB) | HTML Full-text | XML Full-text
Abstract
Critical knowledge gaps seriously hinder efforts for building disaster resilience at all levels, especially in disaster-prone least developed countries. Information deficiency is most serious at local levels, especially in terms of spatial information on risk, resources, and capacities of communities. To tackle this [...] Read more.
Critical knowledge gaps seriously hinder efforts for building disaster resilience at all levels, especially in disaster-prone least developed countries. Information deficiency is most serious at local levels, especially in terms of spatial information on risk, resources, and capacities of communities. To tackle this challenge, we develop a general methodological approach that integrates community-based participatory mapping processes, one that has been widely used by governments and non-government organizations in the fields of natural resources management, disaster risk reduction and rural development, with emerging collaborative digital mapping techniques. We demonstrate the value and potential of this integrated participatory and collaborative mapping approach by conducting a pilot study in the flood-prone lower Karnali river basin in Western Nepal. The process engaged a wide range of stakeholders and non-stakeholder citizens to co-produce locally relevant geographic information on resources, capacities, and flood risks of selected communities. The new digital community maps are richer in content, more accurate, and easier to update and share than those produced by conventional Vulnerability and Capacity Assessments (VCAs), a variant of Participatory Rural Appraisal (PRA), that is widely used by various government and non-government organizations. We discuss how this integrated mapping approach may provide an effective link between coordinating and implementing local disaster risk reduction and resilience building interventions to designing and informing regional development plans, as well as its limitations in terms of technological barrier, map ownership, and empowerment potential. Full article
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